Abstract:
A method may include identifying a content item associated with a contributor. Users may be invited to review the content item. A survey adapted to estimate engagement with the content item by a plurality of the users may be provided to the users. Results of the survey may be received from the plurality of the users. Popularity of the content item with respect to the plurality of the users may be determined from the results of the survey. At least a subset of the plurality of the users may be categorized based on the popularity of the content item with respect to the plurality of the users.

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
       [0001]    This application is a continuation of U.S. patent application Ser. No. 12/589,807, filed Oct. 27, 2009 and entitled “Content Management,” now U.S. Pat. No. 8,533,013, which claims priority to U.S. Provisional Patent Application Ser. No. 61/108,847, filed Oct. 27, 2008 and entitled “Blogging,” which are incorporated herein by reference. 
     
    
     BACKGROUND 
       [0002]    Demand for Internet content such as videos, images, news articles, tweets, and weblogs is limited by the time that people have to review such content. The supply of such content is growing exponentially and to a point where Internet search engines such as Google struggle to respond with results directing users to relevant content. In many cases results can include hundreds or thousands of references to content that may or may not be relevant to the immediate interests of the user. Helping people find quality content on-line that is relevant to their interests continues to be an overwhelming and complex process. Also, lack of relevancy combined with an overwhelming amount of on-line content increases the costs and complexities involved for advertiser that wish to target users with offerings relevant to their interests, or needs. 
         [0003]    Internet content aggregators commonly referred to as “news aggregators” have emerged to address the growing issue of overwhelming content. A goal of these Internet services is to manage less, but more popular, content in one place in ways that make review easier and more interesting for users while improving the advertiser&#39;s ability to target offerings that are relevant to the user&#39;s interests. Users can refer what they believe to be popular content from any website to an aggregation hub so that other users may review the content, leave comments in reference to the content, and rank the content according to their likes and dislikes. If a user likes the content they give it a positive rating. This action results in improved visibility of the content and an increase in popularity. Conversely if users provide negative ratings this results in less visibility of the content and subsequently a decrease in popularity. 
         [0004]    Many content aggregation websites have emerged. However, the growing volume of Internet content is now overwhelming these aggregators because the more users refer content to them the more overwhelming searching and reviewing content becomes for their other users. Moreover, some users have also learned how to manipulate rating systems provided by aggregators. For example, a small group of users can use rating features to bury popular content, which results in less visibility. 
         [0005]    As explained on wikipedia.com in reference to Digg.com “the existence of the “bury” option has also been criticized as undemocratic and due to its anonymous nature, unaccountable, which often leads to expungement of criticism of hotbed topics that do not mesh with the prevailing view of the community,” and goes on to explain that, “Certain Digg users have been accused of operating a ‘Bury Brigade’ that tags news articles with which they disagree as spam, thus attempting to bury stories.” In other words, a minority of users that may be negatively affected by certain content can reduce exposure of such content by using the bury feature. Therefore, visibility of content that is potentially valuable to the broader community can be reduced, or eliminated, and without accountability. 
         [0006]    During the 2008 United States Presidential election the Los Angeles Times published an article dated Aug. 11, 2008 that stated, “A close look at campaign-oriented stories on Digg shows that, in the last 30 days, at least 28 stories critical of GOP Sen. John McCain have been mysteriously “buried”—meaning enough Digg users have voted against a story that the submission may no longer appear on the site&#39;s high-traffic front page.” 
         [0007]    As another example of how the “bury” option can be used to reduce visibility of content; when users rise up and post content on a news aggregator such as Digg.com relating to a complaint about a company&#39;s products or services, representatives from that company can bury it. This “bury” capability dilutes the value of centralized content aggregation for the user community majority because it reduces or eliminates exposure of the most controversial and compelling subject matter. Moreover, due to the “bury” issue the journalist, or blogger, or referring user that represents the controversial subject matter is left feeling helpless and discouraged in much the same way as people did prior to when consumer advocacy groups and class-action lawsuits formed to overcome such behavior off-line. Ultimately this issue negatively affects users as described herein as well as other participants that could benefit from the increased attention that centralized content with a high degree of user feedback could provide such as companies that desire to compete with better services, advertisers that wish to improve their ability to target users in relation to relevant subject matter, and publishers who are always looking for ways to engage users with compelling content. 
         [0008]    Today most websites provide features enabling users to post their own comments in relation to published on-line content such as videos, images, news articles, tweets, and weblogs. Additionally, the use of RSS commonly translated as “Really Simple Syndication” or sometimes “Rich Site Summary” is a set of web feed formats used to publish frequently updated works. For example when a user subscribes to on-line content such as a news article that user will be notified when another user posts a comment related to the article. As described by wikipedia.com, “An RSS document (which is called a “feed”, “web feed”, or “channel”) includes full or summarized text, plus metadata such as publishing dates and authorship,” and goes on to explain that, “web feeds benefit readers who want to subscribe to timely updates from many sites into one place.” Users have learned how to manipulate the comment and RSS features to spread unsolicited bulk offers e.g. spam, or propaganda in an effort to skew public opinion. 
         [0009]    Using our previous example “when users rise up and post content relating to a complaint about a company&#39;s products or services on a website that,” provides comment features; representatives from that company can easily and effectively skew public opinion by posting comments designed to mislead, or shift public opinion in relation to the complaint. It should be noted that the Internet allows users to voice their opinions with complete anonymity by using pseudonyms to hide their identity. Therefore, comment features enable anyone including those employed by the subject company to post comments that may be completely inaccurate and without accountability. 
         [0010]    Additionally, the use of RSS features in relation to content comment features has become widespread on-line. Using the same example “when users rise up and post content relating to a complaint about a company&#39;s products or services on a website that,” provides RSS features; representatives from that company can easily and effectively skew public opinion by posting comments designed to mislead, or shift public opinion in relation to the complaint then leveraging the RSS process that notifies all users that subscribed to the subject content that a comment has been added. This allows a minority of users to skew public opinion within the minority group effectively, quickly, and without accountability. Soon interest in the posted complaint dies. 
         [0011]    In each of these examples the users representing the subject company who took action to skew public opinion simultaneously reduced their chances to collect valuable information as to how consumers view their company and how best to adjust their products, or services in relation to consumer needs. Moreover, due to the user controlled “comment and RSS” issues the journalist, or blogger, or referring user that represents the controversial content is left to feel helpless and discouraged in much the same way as people did prior to when consumer advocacy groups and class-action lawsuits formed to overcome such behavior off-line. Ultimately this issue negatively affects users as described herein as well as other participants that could benefit from the increased attention that centralized content with a high degree of user feedback could provide such as companies that desire to compete with better services, advertisers that wish to improve their ability to target users in relation to relevant subject matter, and publishers who are always looking for ways to engage users with compelling content. 
         [0012]    The examples expressed herein indicate how people try to manipulate on-line systems for personal and corporate gain, but they also do so for notoriety. However, polling systems both on and off line can be used to shift the power of public opinion away from user minorities that attempt to skew public opinion towards the user majority that collectively acts in favor of the broader community. 
         [0013]    For example, In 2007 Famous radio personality and host, Howard Stern, working in conjunction with the website votefortheworst.com tried to manipulate the voting process for the popular TV show American Idol. FOX has dominated primetime TV for many years with their hit show, American Idol, in which singers compete in a talent show format and the general public casts votes. Contestants that earn the most votes continue while those with less votes are rejected from further competition. American Idol supports a voting process whereby viewers can submit their votes on-line, or use mobile devices to vote by text message for example, or by calling an American Idol representative to cast their vote. Mr. Stern tried to rally his millions of radio listeners in an effort to get them to vote for the worst American Idol performer to win and, thereby, skew the voting outcome. This prompted a statement from a Fox spokeswoman who explained; “efforts like Mr. Stern&#39;s do not affect the results. With 30 million votes every week, and hundreds of millions of votes over the season, the power of true fans of ‘American Idol’ dwarfs any attempt of people trying to gain notoriety.” In the end the best performer won because the American Idol fan base majority had a system in place to overrule the fan minority who were swayed by Howard Stern. 
         [0014]    American Idol represents an example as to how the Internet, mobile devices, and widespread polling associated with a voting process can be used effectively to engage the viewer majority and subsequently over rule the agenda of a user minority when provided with a system enabling them to quickly and efficiently express their opinions in a structured manner. 
         [0015]    Numerous Internet services exist today that enable users to submit their own content such as blogs, or refer published content to a central aggregation hub such as, and to comment in reference to such content. Numerous websites also exist that enable users to express opinions about products and services such as Yelp.com. Yelp enables users to read customer reviews of local businesses such as restaurants. Another site, epinions.com, allows users to write product reviews. Numerous websites exist that poll users with questions on a per topic basis. Other services such as YahooAnswers.com allow users to ask questions for other users to answer. Then there are social-network providers such as Facebook.com, which enable users to connect based on pre-existing relationships, manage these relationships, and form affinity groups. The trend with regard to attracting interest to Internet content and engaging users is clearly towards enabling them to control the content. However, all of these services and others existing within the art provide features that can be manipulated by a user minority without oversight or accountability. 
         [0016]    Nothing available within the existing art enables users to express themselves in relation to content in ways that can enable large scale response from the user majority within an Internet community quickly, and efficiently. The features they provide require a significant amount of time and attention from their users on an ongoing basis. As a result, an estimated 90% of users don&#39;t contribute directly they only review content referred, or published by a minority set of users, and do so within a highly fragmented and easily abused Internet services environment. 
         [0017]    As a result of the issues expressed herein advertisers continue to struggle with complexities related to targeting their desired audience with offerings that are relevant to the user&#39;s interests or needs. This issue reduces user engagement and related revenues not just for advertisers, but for Internet content publishers, and other contributors such as journalists or bloggers as well. As a result Internet advertising networks resort to highly sophisticated methods of tracking user behavior on websites to improve their abilities to increase user engagement per ad. This frequently leads to an invasion of user privacy. Currently there are very few ways to target Internet advertisements with a high degree of relevancy based on the needs of Internet users, and fewer ways to do so without invading their privacy. 
         [0018]    Despite the advances in Internet services designed to publish, or aggregate content such as videos, images, news articles, tweets, and weblogs, and for users to interact with such content there is a need for an Internet service that mitigates issues associated with user group minorities “burying” content for their benefit and without accountability by providing a system that highlights all popular content, especially the most controversial, and with a rating system that ranks content based on user attention whether that attention is positive, or negative. 
         [0019]    There is a need to mitigate issues relating to a user minority leveraging Internet “comment and RSS” features to spread unsolicited offers e.g. spam, or to mislead or skew public opinion for their own benefit by providing a system designed to engage the broader user community e.g. majority and enable these users to work together on a large scale through collective oversight to quickly and efficiently express their opinions concerning topics of interest and the actions of the user minority. 
         [0020]    There is a need for a system that can engage the broader user community in ways that enable the user majority to overrule a user minority regardless of the use of pseudonyms to protect identity, and for the benefit of the overall user community. 
         [0021]    There is a need to mitigate issues relating to targeted advertising and user privacy invasion by collecting consumer feedback in the form of answers to survey questions relating to the subject matter of popular content on a scale large enough to make this data meaningful to advertisers, and organized into general categories based on the subject matter of the content so that advertisers can create campaigns based on how users responded to surveys in relation to content instead of continuing to collect the user&#39;s personal data. 
         [0022]    There is a need for a system that can streamline and bring structure to the process of engaging the broader user community e.g. majority in ways that enable them to respond to controversial topics on a large scale quickly, efficiently, and effectively not only to provide the majority over-ruling the minority dynamic, but to enable users to form affinity groups in relation to controversial topics and mobilize in ways that benefit communities through driving organized change similar to how consumer advocates and class-action lawsuits leverage the combined interests of people. 
         [0023]    These and other needs are addressed in this paper. 
       SUMMARY 
       [0024]    A content management system can have one or more of an aggregation engine, a survey engine, a polling engine, an apparent-interest engine, an explicit-interest engine, and a results processing engine. A content aggregation engine enables users such as journalists or bloggers to publish content to a central hub, or users can refer on-line published content from third party websites such as videos, images, news articles, tweets, and weblogs to a central hub for other users to search, review, and interact with. 
         [0025]    A survey engine enables a user that refers or publishes content to the hub to create their own survey questions pertaining to the published, or referred content (such as videos, images, news articles, tweets, and weblogs) so that other community members can quickly, efficiently, and effectively respond by answering the survey questions. By identifying popular content and polling the user community the system increases exposure of the content thereby benefiting publishers. By enabling the broader user community to rally around topics of interest on a large scale in a structured and efficient manner these users can work together to effectively address issues based on shared topics of interest. Additionally, the user survey data generated during polling enables advertisers to improve how they target their desired audience, and for publishers and journalists to earn revenues related to these enhanced advertisements. 
         [0026]    A polling engine enables notification to the broader user community membership e.g. majority using methods such as email, or Short Message Service (SMS), or by changing indicia on a web browser to alert users to invite them to review subject matter and answer survey questions pertaining to the most popular content in a manner that is structured, efficient, and effective. This can enable users to participate in the polls and answer survey questions using devices such as a mobile phone, a Personal Data Assistant (PDA), a personal computer, or some other convenient device. 
         [0027]    An apparent-interest engine enables identification of popular content, such as videos, images, news articles, tweets, and weblogs in ways that increases exposure for the referring users, publishers, journalists, and bloggers without allowing a user minority to bury such content thereby removing it from popular exposure. 
         [0028]    An explicit-interest engine enables polled users to Identify the most popular content, such as videos, images, news articles, tweets, and weblogs as vetted by the interactions of the users; thereby qualifying the related subject matter for polling and to make answering related survey questions more efficient. 
         [0029]    A results-processing engine enables compilation of user survey data whether generated over time regarding any survey, or during polling regarding the most popular content in ways that enable advertisers to improve how they target their desired audience, for publishers and journalists to earn revenues related to these enhanced advertisements, and/or for users to form affinity groups in relation to controversial topics and mobilize in ways that benefit communities through driving organized change similar to how consumer advocates and class-action lawsuits leverage the combined interests of people. 
     
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         [0030]      FIG. 1  depicts an example of a majority-interest content management system. 
           [0031]      FIG. 2  depicts an example of a system including a content management system and a content contributor. 
           [0032]      FIG. 3  depicts an example of a content aggregation system. 
           [0033]      FIG. 4  depicts an example of a survey engine. 
           [0034]      FIG. 5  depicts an example of an apparent-interest engine. 
           [0035]      FIG. 6  depicts an example of a polling engine. 
           [0036]      FIG. 7  depicts an example of a results processing engine. 
           [0037]      FIG. 8  depicts an example of an explicit-interest engine. 
           [0038]      FIG. 9  depicts an example of system in which a website can partner with a poll server. 
           [0039]      FIG. 10  depicts a flowchart of an example of a method for content vetting. 
       
    
    
     DETAILED DESCRIPTION 
       [0040]      FIG. 1  depicts an example of a majority-interest content management system  100 . The system  100  includes a network  102 , a majority-interest server  104 , and clients  106 - 1  to  106 -N (collectively, clients  106 ). 
         [0041]    In the example of  FIG. 1 , the network  102  can include a wired system or a wireless system. The wired system may consist of an individual wire, a LAN or, a WAN. The LAN and WAN may consist of any network topology available such as bus, token-ring, partial mesh, or fully meshed network. The LAN and WAN protocols may support any variety of protocols including Ethernet, TCP/IP, ATM, Frame Relay, 802.11, PPP and any OSI-based protocol. The network  102  can include a networked system that includes several computer systems coupled together, such as the Internet. The term “Internet” as used herein refers to a network of networks that uses certain protocols, such as the TCP/IP protocol, and possibly other protocols such as the hypertext transfer protocol (HTTP) for hypertext markup language (HTML) documents that make up the World Wide Web (the web). Content is often provided by content servers, which are referred to as being “on” the Internet. A web server, which is one type of content server, is typically at least one computer system which operates as a server computer system and is configured to operate with the protocols of the World Wide Web and is coupled to the Internet. The physical connections of the Internet and the protocols and communication procedures of the Internet and the web are well known to those of skill in the relevant art. For illustrative purposes, it is assumed the network  102  broadly includes, as understood from relevant context, anything from a minimalist coupling of the components, or a subset of the components, illustrated in the example of  FIG. 1 , to every component of the Internet and networks coupled to the Internet. 
         [0042]    A computer system, as used in this paper, is intended to be construed broadly. In general, a computer system will include a processor, memory, non-volatile storage, and an interface. A typical computer system will usually include at least a processor, memory, and a device (e.g., a bus) coupling the memory to the processor. The processor can be, for example, a general-purpose central processing unit (CPU), such as a microprocessor, or a special-purpose processor, such as a microcontroller. 
         [0043]    The memory can include, by way of example but not limitation, random access memory (RAM), such as dynamic RAM (DRAM) and static RAM (SRAM). The memory can be local, remote, or distributed. As used in this paper, the term “computer-readable storage medium” is intended to include only physical media, such as memory. As used in this paper, a computer-readable medium is intended to include all mediums that are statutory (e.g., in the United States, under 35 U.S.C. 101), and to specifically exclude all mediums that are non-statutory in nature to the extent that the exclusion is necessary for a claim that includes the computer-readable medium to be valid. Known statutory computer-readable mediums include hardware (e.g., registers, random access memory (RAM), non-volatile (NV) storage, to name a few), but may or may not be limited to hardware. 
         [0044]    The bus can also couple the processor to the non-volatile storage. The non-volatile storage is often a magnetic floppy or hard disk, a magnetic-optical disk, an optical disk, a read-only memory (ROM), such as a CD-ROM, EPROM, or EEPROM, a magnetic or optical card, or another form of storage for large amounts of data. Some of this data is often written, by a direct memory access process, into memory during execution of software on the computer system. The nonvolatile storage can be local, remote, or distributed. The non-volatile storage is optional because systems can be created with all applicable data available in memory. 
         [0045]    Software is typically stored in the non-volatile storage. Indeed, for large programs, it may not even be possible to store the entire program in the memory. Nevertheless, it should be understood that for software to run, if necessary, it is moved to a computer-readable location appropriate for processing, and for illustrative purposes, that location is referred to as the memory in this paper. Even when software is moved to the memory for execution, the processor will typically make use of hardware registers to store values associated with the software, and local cache that, ideally, serves to speed up execution. As used herein, a software program is assumed to be stored at any known or convenient location (from non-volatile storage to hardware registers) when the software program is referred to as “implemented in a computer-readable storage medium.” A processor is considered to be “configured to execute a program” when at least one value associated with the program is stored in a register readable by the processor. 
         [0046]    The bus can also couple the processor to the interface. The interface can include one or more of a modem or network interface. It will be appreciated that a modem or network interface can be considered to be part of the computer system. The interface can include an analog modem, isdn modem, cable modem, token ring interface, satellite transmission interface (e.g. “direct PC”), or other interfaces for coupling a computer system to other computer systems. The interface can include one or more input and/or output (I/O) devices. The I/O devices can include, by way of example but not limitation, a keyboard, a mouse or other pointing device, disk drives, printers, a scanner, and other I/O devices, including a display device. The display device can include, by way of example but not limitation, a cathode ray tube (CRT), liquid crystal display (LCD), or some other applicable known or convenient display device. 
         [0047]    In one example of operation, the computer system can be controlled by operating system software that includes a file management system, such as a disk operating system. One example of operating system software with associated file management system software is the family of operating systems known as Windows® from Microsoft Corporation of Redmond, Wash., and their associated file management systems. Another example of operating system software with its associated file management system software is the Linux operating system and its associated file management system. The file management system is typically stored in the non-volatile storage and causes the processor to execute the various acts required by the operating system to input and output data and to store data in the memory, including storing files on the non-volatile storage. 
         [0048]    Some portions of the detailed description may be presented in terms of algorithms and symbolic representations of operations on data bits within a computer memory. These algorithmic descriptions and representations are the means used by those skilled in the data processing arts to most effectively convey the substance of their work to others skilled in the art. An algorithm is here, and generally, conceived to be a self-consistent sequence of operations leading to a desired result. The operations are those requiring physical manipulations of physical quantities. Usually, though not necessarily, these quantities take the form of electrical or magnetic signals capable of being stored, transferred, combined, compared, and otherwise manipulated. The signals take on physical form when stored in a computer readable storage medium, such as memory or non-volatile storage, and can therefore, in operation, be referred to as physical quantities. It has proven convenient at times, principally for reasons of common usage, to refer to these signals as bits, values, elements, symbols, characters, terms, numbers, or the like. 
         [0049]    It should be borne in mind, however, that all of these and similar terms are to be associated with the appropriate physical quantities and are merely convenient labels applied to these quantities. Unless specifically stated otherwise as apparent from the following discussion, it should be appreciated that throughout the description, discussions utilizing terms such as “processing” or “computing” or “calculating” or “determining” or “displaying” or the like, refer to the action and processes of a computer system, or similar electronic computing device, that manipulates and transforms data represented as physical quantities within the computer system&#39;s registers and memories into other data similarly represented as physical quantities within the computer system memories or registers or other such information storage, transmission or display devices. 
         [0050]    The algorithms and displays presented herein are not necessarily inherently related to any particular computer or other apparatus. Various general purpose systems may be used with programs to configure the general purpose systems in a specific manner in accordance with the teachings herein, or it may prove convenient to construct specialized apparatus to perform the methods of some embodiments. The required structure for a variety of these systems will appear from the description below. Thus, a general purpose system can be specifically purposed by implementing appropriate programs. In addition, the techniques are not described with reference to any particular programming language, and various embodiments may thus be implemented using a variety of programming languages. 
         [0051]    Referring once again to the example of  FIG. 1 , in the example of  FIG. 1 , the majority-interest server  104  is coupled to the network  102 . Servers, as used in this paper, can be a single server or multiple servers, or a blade or multiple blades within a server. An individual server may run a plurality of operating systems such as UNIX, Linux, Windows, AIX, VMS/VAX, or similar system. The majority-interest server  104  can be implemented on a known or convenient computer system, specially purposed to provide majority-interest content management functionality or other functionality described in this paper (collectively, the “majority-interest functionality”). Examples of majority-interest functionality are described in this paper. The majority-interest server  104  is intended to illustrate a server that has the novel functionality, but partial functionality might be provided by a first server and partial functionality might be provided by a second server, where together the first and second server provide the full server functionality. 
         [0052]    Functionality of the majority-interest server  104  can be carried out by one or more engines. For example, the majority-interest server  104  can include one or more of an aggregation engine, a survey engine, a polling engine, an apparent-interest engine, an explicit-interest engine, and a results processing engine. As used in this paper, an engine includes a dedicated or shared processor and, hardware, firmware, or software modules that are executed by the processor. Each engine may reside on a single server or be distributed amongst a plurality of servers. An individual engine can also execute on a single sever or across multiple servers working in tandem with one another. Thus, depending upon implementation-specific or other considerations, an engine can be centralized or its functionality distributed. An engine can include special purpose hardware, firmware, or software embodied in a computer-readable medium for execution by the processor. As used in this paper, a computer-readable medium is intended to include all mediums that are statutory (e.g., in the United States, under 35 U.S.C. 101), and to specifically exclude all mediums that are non-statutory in nature to the extent that the exclusion is necessary for a claim that includes the computer-readable medium to be valid. Known statutory computer-readable mediums include hardware (e.g., registers, random access memory (RAM), non-volatile (NV) storage, to name a few), but may or may not be limited to hardware. 
         [0053]    Referring once again to the example of  FIG. 1 , in the example of  FIG. 1 , the clients  106  are coupled to the network  102 . A client can include one or more devices that communicate with a server. The clients  106  can be implemented on one or more known or convenient computer systems, such as a computer, telephone, smart phone, personal data assistant (PDA), or other device, electronic or otherwise, that can communicate with the majority interest server  104 . The clients  106  use the majority-interest functionality provided by the majority-interest server  104 . Depending upon the implementation and/or preferences, the clients  106  can also carry out majority-interest functionality. Depending upon the implementation and/or preferences, in addition to or instead of using the majority-interest functionality provided by the majority-interest server  104 , the clients  106  can provide or identify content or other useful data to the majority-interest server  104 . The clients  106  can also be majority-interest-agnostic, and take advantage of majority-interest functionality without implementing any novel functionality on their own. It may sometimes be useful to draw a distinction between a client that is a contributor and a client that is a consumer. However, it should be noted that any of the clients can provide data (e.g., by answering a survey), and that a contributor is typically intended to mean a provider or identifier of content for aggregation and/or survey questions associated with content. Contributors may or may not have a different “class” of membership, which can further differentiate them from consumers. For example, contributors may have a paid membership, whereas consumers can access content for free and/or anonymously. 
         [0054]      FIG. 2  depicts an example of a system  200  including a content management system and a content contributor. The system  200  includes a network  202 , a content repository  204 , a contributor  206 , and a content management system  208 . The network  202  can include any coupling of computer systems and is optional in the sense that the content repository  204 , contributor  206 , and content management system  208  could be implemented on a single device (though it is unlikely that all contributors, in an implementation that includes multiple contributors, will not be coupled to other components through the network  202 ). 
         [0055]    In the example of  FIG. 2 , the content repository  204  is coupled to the network  202 . A repository, as used in this paper, is intended to have the broadest reasonable meaning Thus, the repository includes any data storage that allows meaningful access to the data. Examples of repositories include conventional commercial databases, as well as comma-delimited data files (or other equivalents delimited files), practically any data structure (e.g., objects, tables, arrays, etc.), and any other applicable structure that facilitates convenient access to data. For illustrative convenience, databases are also assumed to have the appropriate database interfaces, if needed. A repository can be centralized or distributed, and the data stored in the repository can be maintained by a single entity or by the owners of the data (perhaps with restrictions). 
         [0056]    The content repository  204  can include videos, images, news articles, tweets, weblogs, and other content. It is expected that the content will normally be that which can be provided through a network, so the data will typically have an electronic format. Although it is theoretically possible to implement a system in which content includes a physical object or location (e.g., artwork in a museum) that has no electronic representation, in general the content will include at least some electronic data (e.g., a picture of the artwork in the museum). As used in this paper, the content is assumed to be the portion that can be provided through the network  202 , and excludes any portion that cannot be provided through the network  202 . 
         [0057]    A content server associated with the content repository  204  may or may not actually maintain a copy of the content. For example, it is possible to logically aggregate content from multiple third party sites without maintaining a copy of the content. Thus, the content repository  204  can be a repository for copies of content that is maintained by a single party, or it can be a repository of content that is maintained by multiple different parties but aggregated logically. To be of optimal use, the content repository  204  should act as a “central hub” for other users to search, review, and interact with, regardless of the physical characteristics of the device or devices that make up the content repository  204 . As such, the content can be thought of as “part of the content repository  204  regardless of the physical location of the content. 
         [0058]    In the example of  FIG. 2 , the contributor  206  is coupled to the network  202 . The contributor  206  can be referred to, depending upon the context, as a human or a device. In this paper, the contributor  206  is assumed to be hardware or a combination of hardware and software. Thus, where the contributor  206  appears to be anthropomorphized, it is done for readability and it should be understood that an artificial agent is translating preferences, actions (perhaps taken by a human), or other applicable dynamic or static stimuli into data and controls for use by other components of the system  200 . 
         [0059]    In operation, the contributor  206  refers or publishes content to the content repository  204 . The content, once referred or published, is at least logically located in the content repository  204 . Depending upon the implementation and/or configuration, the contributor  206  may be able to update the content dynamically when the content changes. There may be some restrictions to content updating to ensure that majority-interests are met. For example, the contributor  206  (or the owner of content that the contributor  206  refers) might be prohibited from changing content after consumers have judged the accuracy, relevance, or some other characteristic of the content if the change would cause the judgment to become invalid, inaccurate, confusing, or nonsensical. 
         [0060]    In the example of  FIG. 2 , the content management system  208  is coupled to the network  202 . The content management system  208  includes a content aggregation engine  210 , a survey engine  212 , a polling engine  214 , an apparent-interest engine  216 , an explicit-interest engine  218 , and a results processing engine  220 . 
         [0061]    The aggregation engine  210  aggregates the content provided by the contributor  206  into the content repository  204 . For example, the content aggregation engine  210  can enable the contributor  206  to publish content to the content repository  204 . Instead or in addition, the content aggregation engine  210  can enable the contributor  206  to refer on-line published content from third party websites to the content repository  204 . The aggregation engine  210  should be capable of making the content searchable and useful to consumers of the content, tying data associated with the content to the content, adjusting content characteristics based upon majority-interests, and/or providing the data associated with the content to appropriate parties. Depending upon the implementation, it may be possible for un-vetted (e.g., anonymous) users to provide content and surveys. 
         [0062]    The survey engine  212  enables a user that refers or publishes content to the hub to create their own survey questions pertaining to the published, or referred content (such as videos, images, news articles, tweets, and weblogs) so that other community members can quickly, efficiently, and effectively respond by answering the survey questions. The survey engine  212  can provide restrictions such as limiting question formats, limiting answer formats, limiting the number of questions in a survey, limiting one content item to one survey, requiring a minimum number of questions in a survey, moderating information (e.g., requiring approval of a survey), limiting the time or frequency of submissions, limiting content referrals such that only one URL pointing to referred content is allowed, or some combination. The survey engine  212  can also enable relatively free form survey creation, if desired. By identifying popular content and polling the user community the system increases exposure of the content thereby benefiting publishers. By enabling the broader user community to rally around topics of interest on a large scale in a structured and efficient manner these users can work together to effectively address issues based on shared topics of interest. Additionally, the user survey data generated during polling enables advertisers to improve how they target their desired audience, and for publishers and journalists to earn revenues related to these enhanced advertisements. 
         [0063]    The polling engine  214  notifies users including the broader user community membership e.g. majority using methods such as email, or Short Message Service (SMS), or by changing indicia on a web browser to alert users to invite them to review subject matter and answer survey questions pertaining to the most popular content in a manner that is structured, efficient, and effective. This can enable users to participate in the polls and answer survey questions using devices such as a mobile phone, a Personal Data Assistant (PDA), a personal computer, or some other convenient device. 
         [0064]    The apparent-interest engine  216  enables identification of popular content, such as videos, images, news articles, tweets, and weblogs in ways that increases exposure for the referring users, publishers, journalists, and bloggers without allowing a user minority to bury such content thereby removing it from popular exposure. In an embodiment, users can rate content items. Where there are multiple surveys per content item, users could also be allowed to rate surveys, which could have a bearing on which content-survey combination goes to the polling engine if there is sufficient apparent interest. In one embodiment, a contributor may be entitled to bypass the apparent interest engine  216  (and go straight to polling). In such an embodiment, it may be desirable to ensure that vetted users who participate in the poll are compensated in some way, such as by revenue sharing with the vetted users to compensate for participating in a vetted survey. 
         [0065]    The explicit-interest engine  218  enables polled users to Identify the most popular content, such as videos, images, news articles, tweets, and weblogs as vetted by the interactions of the users; thereby qualifying the related subject matter for polling and to make answering related survey questions more efficient. 
         [0066]    The results-processing engine  220  enables compilation of user survey data whether generated over time regarding any survey, or during polling regarding the most popular content in ways that enable advertisers to improve how they target their desired audience, for publishers and journalists to earn revenues related to these enhanced advertisements, and/or for users to form affinity groups in relation to controversial topics and mobilize in ways that benefit communities through driving organized change in a manner that is reminiscent of how consumer advocates and class-action lawsuits leverage the combined interests of people. In an embodiment, the results processing engine  220  can record how many survey participants were vetted as compared to un-vetted. For example, if un-vetted users respond to survey questions indicating displeasure with a company, the company may wish to change their ways or proclaim their innocence to the charges. The company can publish the changes or explanation and pay for a survey in which only vetted users participate to ensure that un-vetted (anonymous) users do not skew the results. 
         [0067]      FIG. 3  depicts an example of a content aggregation system  300 . In the example of  FIG. 3 , the content aggregation system  300  includes a contributors repository  302 , an authentication engine  304 , a contribution engine  306 , a content repository  308 , a content display engine  310 , and a content feed  312 . 
         [0068]    The contributors repository  302  can include data about authors, editors, or other content provisioning agents. The contributors repository  302  can include data associated with a contributor account, including personal information used to authenticate a user as a contributor, such as a username, password, or passphrase. The contributors repository  302  can also include financial data such as user account payment information, account credits (for advertising, contribution, etc.), and an account identifier for associating a contributor with content. 
         [0069]    The authentication engine  304  can use information provided by a contributor and the contributors repository  302  to authenticate a particular contributor. Depending upon the implementation and/or embodiment, authentication may be required to provide content for aggregation and evaluation by other users of the system, to associate content with survey data, or to provide content at all. Authentication need not be performed by the same party that aggregates content. For example, authentication could be performed through a third-party server coupled to the authentication engine  304  or at a non-local content server. Authentication can be accomplished through applicable known or convenient techniques, such as a username and password, secure token, pass phrase, PIN, biometric, key exchange, Needham-Schroeder protocol, IPSEC, KERBEROS, Microsoft Active Directory, or any available methodology to authenticate to a computer account. Once a contributor has been authenticated by the authentication engine  304 , the contributor may be granted certain capabilities, such as providing content, associating content with a survey, etc. 
         [0070]    In an embodiment, users must register in order to become contributors. Registration may include email, username, password, personal information (e.g., birth date, first name, last name) and preferences (e.g., keep real name private, display real name, notification when polls open, notification settings (email, SMS, RSS, etc.), and the like). Users may also be asked to accept terms, which may or may not be more stringent than for non-contributor users. The data can be stored in the contributors repository  302 . 
         [0071]    The contribution engine  306  can provide convenient tools for an authorized contributor to create or modify content, associate survey questions with content, view data associated with the content to ascertain popularity, relevance, income realized through the content, and the like. Depending upon the implementation, the contribution engine  306  can also offer tools for creating or managing content, such as blog creators, text editors, web page hosting, content display tools, multimedia composition tools, notification tools (e.g., to notify a contributor when a comment is received in association with provided content), survey question editors, and the like. 
         [0072]    In an embodiment, a contributor can copy content or a link to the content (e.g., a URL) to the contribution engine  306 . Depending upon the implementation, the contributor may also be prompted to enter a title, description of content, a category in which to place the content (e.g., from a choice of topics, by free association, etc.), or some other implementation- or configuration-specific data. The contributor may also be prompted to take other steps, such as checking other listings to make sure nobody has submitted similar content. Often, the contributor will be given the opportunity to preview the entry. The contributor may also be prompted to enter survey questions (see  FIG. 4 ), which may or may not be required to complete the submission. The contributor may be given additional options, such as the option to preview the content entry, preview survey questions associated with the content entry, notify friends regarding the new content, and the like. 
         [0073]    A contributor need not necessarily have any ownership of the content provided. For example, depending upon the implementation and/or configuration, a contributor could refer content from a third party with or without permission from the third party. Where content is provided without permission, it is advisable to be mindful of what constitutes fair use of content and to attribute content to the owner of the content. 
         [0074]    The content repository  308  includes content associated with the contributor. The content repository  308  can be distributed. For example, content could be stored remotely (e.g., in association with a website associated with the contributor), while data associated with the content could be stored locally. Thus, the content repository  308  could include records that include a content identifier (such as a pointer to content or a location of remote content) along with a contributor identifier, an apparent interest value, and other data associated with the content. 
         [0075]    The content display engine  310  can provide a framework for content in the content repository  308  to be organized in accordance with majority interest. New content will typically be associated with a poll question (see, e.g.,  FIG. 4 ), which may or may not be required initially, and an initial apparent-interest value. For simplicity, it is assumed that the initial apparent-interest value is zero. The apparent-interest value is most useful if it can represent a level of interest; so numbers or values that can be associated with numbers (e.g., whole numbers, integers, real numbers, alphanumeric characters, etc.) are the most obvious choices for apparent-interest values. The initial apparent-interest value need not be the lowest possible value. For example, some older content could be associated with lower apparent-interest than the initial value. Also, apparent interest can be initially set to different values for different content (e.g., an author that has a great deal of popular content could have an initial apparent interest value that is higher than an unknown author, current events could have greater initial apparent interest values than historical, etc.). On the other hand, there may be some interest in avoiding skewing results by initializing content to different apparent interest values. The decision is implementation- and/or configuration-specific. 
         [0076]    An apparent interest value can be associated with content and all associated survey questions. Alternatively, multiple apparent interest values can be associated with content and multiple surveys and related questions. It may be desirable to aggregate apparent interest values where there is more than one survey associated with a single item of content. It may be desirable to know which of a plurality of surveys and related questions associated with a content item detected the most apparent interest. For example, it might be desirable to offer the multiple surveys per content item as an optional survey choice, and then pick the survey and related questions that garners the most responses for a poll. 
         [0077]    The content display engine  310  can remove content items on the content feed  312  based on a triggered event or threshold being reached, such as low apparent-popularity as shown by the apparent interest, the passing of a certain amount of time in the content feed  312 , or an event associated with the passing of time. Removing items from the content feed  312  is not a requirement, but it may be desirable for implementation- and/or configuration-specific reasons. Of course, where the content feed  312  is a limited subset of all content items, it may be necessary to remove items to make the list manageable and/or easy to display. 
         [0078]    For illustrative purposes, the contributor is assumed to have no direct control over the content display engine  310 . While the contributor is able to provide content and data associated with the content, at least in some cases, the contributor cannot directly modify content display results with any greater effectiveness than any other user. This enables the content display engine  310  to operate in an objective manner to prevent burying or swaying results. 
         [0079]    The content feed  312  is a data structure that includes content submissions. The content feed  312  can be constructed using an applicable known or convenient technique, such as linked lists of content, an array of content identifiers, sorted objects, etc. 
         [0080]      FIG. 4  depicts an example of a survey engine  400 . In the example of  FIG. 4 , the survey engine  400  includes a questions repository  402 , a survey construction engine  404 , and a content repository  408 . 
         [0081]    The questions repository  402  can include a number of predefined questions, predefined formats with custom text, or custom questions. For example, the questions repository  402  can include the question: “What do you think of this content?” thumbs up/down/neutral, which a contributor could choose to apply to a submission. As another example, the questions repository  402  can include question formats, such as formats for yes/no, yes/no/maybe, date range, value range, dollar range, thumbs up/down/neutral, small/medium/large, vehicle type, etc., which a contributor could choose to apply to a submission along with custom text, such as “Would you change to a credit card company if they had fixed due dates?” As another example, the questions repository  402  can include questions of a custom question format and custom text, such as “Who is your favorite author?” and a list of several authors. 
         [0082]    The survey construction engine  404  enables a contributor to create survey questions associated with the submission. Depending upon the implementation and/or configuration, a contributor can select a question or question format and/or enter a question in association with a submission. Where the question is not predefined, the survey construction engine  404  can store the question in the questions repository  402 . A contributor may also have contributor-specific options, such as saved preferences for question formats, a list of custom questions created previously by the contributor, and the like. 
         [0083]    It is probably desirable to enable quick, efficient, and effective responses; so the survey construction engine  404  would ideally be designed to accomplish this goal. For example, the survey construction engine  404  could enable a contributor to see what a question will look like in a poll as a “preview.” In an embodiment, answers are checkboxes to facilitate easy tallying of results and to take as little response time as possible. However, it may also be desirable to let users enter a number (perhaps to be averaged with numbers entered by other respondents). In an embodiment, contributors could be given the option of moving the questions around or timing questions to correspond to content that is being played. For example, questions could be located near a relevant paragraph of a relatively long article or fade in during a relevant portion of a speech or song. 
         [0084]    The content repository  408  is much as described previously. The survey construction engine  404  may or may not store data in the content repository  408 , but the distinction is inconsequential because the questions repository  402  and the content repository  408  can be thought of as a single repository. However, it may be the case that questions are only stored in association with content and the questions repository  402  only includes predefined questions, if any, while all other questions are stored in content records in, e.g., a content database. 
         [0085]      FIG. 5  depicts an example of an apparent-interest engine  500 . The apparent-interest engine  216  enables identification of popular content, such as videos, images, news articles, tweets, and weblogs in ways that increases exposure for the referring users, publishers, journalists, and bloggers without allowing a user minority to bury such content thereby removing it from popular exposure. In the example of  FIG. 5 , the apparent-interest engine  500  includes a content feed  502 , a content display engine  504 , a hot topic ID engine  506 , and a hot topic list  508   
         [0086]    The content repository  501  includes the content and relevant associated data. The content feed  502  includes a list of content items, which can be a subset of the content in the content repository  501 . The content feed  502  does not have to be a “feed” in the technical sense, but is a list of content items that changes over time, generally but not necessarily based upon the age of the displayed content. 
         [0087]    The content display engine  504  can display the content items from the content repository  501  in the content feed  502  in association with viewing or ranking options. For example, the content items can be associated with options such as comments, share, report, like (i.e., thumbs up), more, link to a wiki, survey, contributors, and the like. A “more” option is frequently desirable because content cannot be displayed in a list if the content is relatively large, as is the case for blogs and text entries of more than a few lines. As selections are made in association with a content item, the apparent interest value of the item increases. Different interactions with the content may be weighted the same or differently. For example, sharing a content item might be given more weight than commenting, commenting on an item may be given more weight than clicking “like,” clicking “like” may be given more weight than clicking “more,” etc. Weight can also be given to, for example, clicks on “like” in association with comments (as opposed to clicks on “like” in direct association with the content item itself. The considerations of weight can be implementation-specific, and may depend on the type of content, the forum, or other considerations. In an embodiment, the content items are listed by date (with the most recent content items at the top), with an apparent-interest value displayed next to the content item. The content items could also be listed by interaction date such that most recent items are put at the top of the list, but interaction with older items moves them to the top of the list. In an embodiment, interacting with a contact item may cause the item to rise in the list rather than automatically moving it to the top, giving weight to both how recently the content item was posted and interactions with the content item. 
         [0088]    In an embodiment, the content display engine  504  can display survey questions in association with the content items. In another embodiment, a view can be provided that identifies contributors. Contributors can include not only the provider of the content item, but also those who interacted with the content item in some way. Advantageously, even though the user contributors are anonymous, it is possible to build a profile for the user based upon interest in various topics. So advertisers may be able to target such users even though they have access to no personal information. Moreover, vetted users can be identified by the system without necessarily disclosing any personal information. This may give their opinions more weight to other users, and the system could consider vetted user interaction with content to have greater weight than that of unvetted users. Moreover, it may be that vetted users are more invested in the system because providing personal information implies greater interest and trust. So vetted users might also be more likely to respond to polls. So weighing vetted user interaction with content more heavily could conceivably result in greater turnout in polls since hot topics are more likely to have more vetted users. 
         [0089]    The hot topic ID engine  506  can select a subset of the content items in the content feed  502  and survey questions associated with the content items. (It should be noted that the hot topic ID engine  506  conceptually selects content items from the content feed  502 , but might actually consider only entries in a content repository with, for example, the highest apparent interest values.) The selected subset can be thought of as content items that are promoted due to gaining the most attention through either direct promotion or indirect criteria. Negative attention can be weighted as heavily as positive attention to ensure that attempts to bury a content item with negative comments will not be successful, and can in fact cause the hot topic ID engine  506  to select the content item. It could be argued that in some cases it might even be desirable to weight negative attention more than neutral or positive attention, though this would be an implementation-specific consideration. 
         [0090]    The hot topic ID engine  506  can create the hot topic list  508  using the selected subset of content items in the content feed  502 . The hot topic list  508  is a data structure that includes content that has an apparent interest value, an apparent interest value that falls within a range, or an apparent interest value that qualifies for listing (e.g., the top 10 content items could be listed). The hot topic list  508  can be constructed using an applicable known or convenient technique, such as linked lists of content, an array of content identifiers, etc. The hot topic list  508  can include the content items with the highest apparent interest values (though the value could be used in a function that does not always result in a list that has the highest of the apparent interest values making the hot topic list  508 ). In this way, the hot topic list  508  could represent the top 10 hottest content items of a category or overall. The hot topic list  508  could be displayed in much the same manner as the content feed  502 . 
         [0091]      FIG. 6  depicts an example of a polling engine  600 . In the example of  FIG. 6 , the polling engine  600  includes a content repository  601 , a hot topic list  602 , a poll construction engine  604 , a poll notification engine  606 , a contributors repository  608 , and a survey  610 . 
         [0092]    The hot topic list  602  includes the content items from the content repository  601  having the highest apparent interest. 
         [0093]    The survey construction engine  604  constructs a survey periodically or aperiodically in accordance with implementation- and/or configuration-specific parameters. For example, the survey construction engine  604  could construct a survey once every week or once every month, the survey construction engine  604  could construct a survey when the hot topic list has a content item that exceeds a threshold or a combination of content items exceed a threshold, or the survey construction engine  604  could construct a survey using other considerations, such as relatively high or low apparent interest in other categories, recent interest in topics on other forums, or some other consideration. 
         [0094]    When the survey construction engine  604  constructs a survey, it matches the content items found in the hot topic list with survey questions. In an embodiment, the content or a link to the content and survey questions associated with the content are stored in the content repository  601 . The survey construction engine  604  can construct surveys into one or more applicable formats, such as would be appropriate for sending in an email, for display on a relatively small screen, such as a cell phone display, via SMS, web page display, or in some other convenient format. 
         [0095]    The poll notification engine  606  checks the contributors repository  608  for notification preferences. Notification preferences can include categories of interest, preferred format for surveys (e.g., email, SMS, changing indicia on a web browser to invite the user to an open poll, etc.), batch or individual survey delivery, and the like. It should be noted that contributors need not be content providers, and can be users who have an account that includes no personal information. In this context, they become contributors because they have their notification settings set such that they contribute survey responses. The poll notification engine  606  makes the survey  610  available in an appropriate format to each user having the appropriate notification settings. The users can then participate in polls and answer survey questions using devices such as a mobile phone, a PDA, a personal computer, or some other convenient device. 
         [0096]      FIG. 7  depicts an example of a results processing engine  700 . In the example of  FIG. 7 , the results processing engine  700  includes a survey results  702 , a results display engine  704 , a vetted topic list  706 , a contributors update engine  708 , a content repository  710 , and a contributors repository  712 . 
         [0097]    The survey results  702  are the results of surveys sent to applicable contributors. 
         [0098]    The results display engine  704  compiles the survey results  702  and outputs the results to the vetted topic list  706 . The vetted topic list  706  could replace the hot topic list ( FIG. 5 ), or it could be displayed as a stand-alone list. It may be desirable to present the hot topics and vetted topics list to enable users to see the difference between a vocal minority (the apparent interest list) and the (hopefully) majority. It may be desirable to remove the hot topics from the hot topics list (and keep them off of the hot topics list) to reduce the likelihood of polling the same topics repeatedly. If the hot topic list is updated as apparent interest changes, it may be desirable to maintain the vetted topics list  706  for historical purposes. In an embodiment, the vetted topics list  706  lists the most frequently answered questions first, or the questions could be organized in some other fashion (e.g., the most lopsided answers first, such as 95% yes, 1% no, 4% maybe). 
         [0099]    There is no particular time limit by which a user would necessarily have to respond, and the results display engine  704  could continue to compile results as they are received. At some point, however, it may be desirable to close the polls. In another embodiment it may be advantageous for polls to open and close in a relatively short period of time such as within one day or one week to encourage prompt participation by users. 
         [0100]    The contributors update engine  708  can update the content repository  710  with the vetted content information. Vetted content information is information that takes on added significance because it has been provided through a polling process that reduces the impact of vocal minorities. Contributors may then be able to access vetted information in association with the content they provided. The contributors update engine  708  can also update the contributors repository  712 . For example, users who participate in the survey could be associated with their responses to enable the building of a profile associated with the users without the use of any personal information. Users can also be ranked or earn credit based upon participation. 
         [0101]    Vetted users, as opposed to vetted content information are those users that can be associated with a real-world identity. The confidence required to consider a user vetted is implementation- or configuration-specific. For example, a system may require a real name and address that is tied to a credit card, a name and address tied to a telephone number, or some other information that establishes identity to some degree. Vetted users may be considered to have more weighty opinions in some cases. For example, a content contributor may care more about the opinions of users that are vetted than those that are not. In an embodiment, a user can be identified as vetted (such as by putting a star next to the user name) without necessarily disclosing any personal information. Alternatively, vetted users may wish to give their real name when providing opinions or contributing content if desired. In a system implementing techniques described in this paper, it is anticipated that protecting personal information will be a high priority to encourage participation. So the disclosure of personal information is likely to be by choice rather than by default. 
         [0102]      FIG. 8  depicts an example of an explicit-interest engine  800 . In the example of  FIG. 8 , the explicit-interest engine  800  includes a vetted topics list  802 , a content repository  804 , a contributors repository  806 , an interest reporting engine  808 , and a report  810 . 
         [0103]    The vetted topics list  802  can be displayed or archived for reporting purposes for a duration that is implementation- and/or configuration-specific. The content repository  804  can include content entries that are updated in accordance with apparent interest and vetted interest. The contributors repository  806  can include content contributors and data contributors that are update with each contribution, or a subset of the contributions. Advantageously, contributors who wish to provide no personal information can do so, while their contributions are still allocated to their accounts. The interest reporting engine  808  can use this data to determine what is of most interest to those who are viewing similar content, those who are most similar to other users who have indicated an interest in a topic. Some users may even wish to state explicitly where their interests lie by category or keyword. Then the interest reporting engine  808  can generate a report to inform a party requesting the report regarding actual views (vetted) rather than vocal minority views on a topic, what content is of greatest interest in general, which types of users prefer which types of content, and all with relative anonymity (at least for the majority users). 
         [0104]    The explicit-interest engine  800  enables polled users to identify the most popular content, such as videos, images, news articles, tweets, and weblogs as vetted by the interactions of the users; thereby qualifying the related subject matter for polling and to make answering related survey questions more efficient. By identifying popular content and polling the user community content that might otherwise have been buried can get increased exposure, thereby benefiting publishers. By enabling the broader user community to rally around topics of interest on a large scale in a structured and efficient manner these users can work together to effectively address issues based on shared topics of interest. Additionally, the user survey data generated during polling enables advertisers to improve how they target their desired audience, and for publishers and journalists to earn revenues related to these enhanced advertisements. 
         [0105]      FIG. 9  depicts an example of system  900  in which a website can partner with a poll server. In the example of  FIG. 9 , the system  900  includes a partner  902 , a poll server  904 , a referring client  906 , and a poll client  908 . 
         [0106]    The partner  902  can be a system that includes a content server at least for clients of the partner  902 , such as, in this example, the referring client  906 . The partner  902  includes a linking engine  910  and content  912 . The linking engine  910  can be provided by a party associated with the poll server  904  (e.g., an API), or it can be created by a party associated with the partner  902  to provide a link to the poll server  904 . The linking engine  910  can be made available to all clients of the partner  902  or a subset thereof, and it can be made available in association with all content provided by the partner  902  in its capacity as a content server, or a subset thereof. As indicated by the conceptual flow arrow  1 , the referring client  906  uses the linking engine  910  to establish a link to the poll server  904  through the conceptual flow arrow  2 . 
         [0107]    The poll server  904  can be a system that includes content aggregation and polling functionality at least for clients of the poll server  904 , which can include, at least to some degree, any user device that has the capability to go to a website of the poll server  904 . The poll server includes a registration engine  914 , an aggregation engine  916 , a survey engine  918 , an apparent interest engine  920 , a polling engine  922 , a results processing engine  924 , and an explicit interest engine  926 . The registration engine  914  registers the referring client  906  as a contributor. As indicated by the conceptual flow arrow  3 , control is then passed to the aggregation engine  916 . 
         [0108]    If the partner  902  is trusted, the referring client  906  could be given vetted status by the poll server  904  without receiving any personal information (or less personal information than would normally be required to have vested status) in association with the referring client  906 . Thus, the registration engine  914  can generate vested user accounts without needing to ask for personal information, which could conceivably have scared off users who trust the partner  902 , and have given the partner  902  their personal information, but who do not know the parties associated with the poll server  904 . It is likely that users who have provided personal information to any of the linked parties will be more invested in a system that treats them as vested even if no personal information is provided. Moreover, depending upon the implementation, content contributors may be required to provide certain information to the poll server  904 , but the partner  902  can essentially vouch for the referring client  906 , enabling the use of a user name to tie the referring client  906  to an account having details that are unknown to the poll server  904 , but that is sufficient to enable the poll server  904  to set up a vested account nevertheless. 
         [0109]    The aggregation engine  916  enables the referring client to identify refer the content  912  to the aggregation engine either by providing a URL, a copy, or through some other convenient technique. The conceptual flow arrow  4  illustrates the content  912  or a link to the content  912  being aggregated at the aggregation engine  916 . As illustrated by the conceptual flow arrow  5 , the aggregation engine  916  passes control to a survey engine  918  which obtains survey questions from the referring client  906  or an agent associated with the referring client  906 . The aggregation engine  916  and the survey engine  918  can conceptually be combined when aggregation is considered to include aggregation of both content and the associated data, and can actually be implemented to obtain the different types of data in any order or in parallel. 
         [0110]    When the content and associated data has been collected, control passes to the apparent interest engine  920  (conceptual flow arrow  6 ), which makes the content and some of the associated data available to clients, typically including unregistered clients (not shown) that are coupled to a website associated with the poll server  904  to view content. The apparent interest engine  920  gauges apparent interest in the content  912  (and other content) over time. If apparent interest in the content  912  passes an interest threshold, or is above a certain threshold when polling begins (conceptual flow arrow  7 ), the polling engine  922  sends survey data to poll client  908  (conceptual flow arrow  8 ). It is assumed for illustrative purposes that the poll client  908  responds to the survey (conceptual flow arrow  9 ), providing the results processing engine  924  with data. The results processing engine  924  stores the data in appropriate locations, such as contributors repositories, content repositories, vetted interest lists, etc. and control passes to the explicit interest engine  926  (conceptual flow arrow  10 ), which reports to the partner  902  (conceptual flow arrow  11 ) regarding explicit interest in the content, data about users interested in the client (though in an embodiment without sharing personal information), or the like. 
         [0111]    Advantageously, this can give the partner  902  greater visibility, a better understanding of user interest in content, and additional revenue if the business model includes a revenue sharing agreement with partners; a contributor associated with the referring client  906  can gain some economic benefit from advertisements displayed in association with the content, satisfaction from becoming a contributor, and access to other content at the poll server  904 ; the poll server site can gain additional contributors (such as the referring client  906 ), additional content (such as the content  912 ), and additional revenue from increased interest by advertisers thanks to increased traffic; the poll client  908  can stay on top of the highest interest content, gain satisfaction from contributing, and receive more targeted ads that may include products or services in which a contributor associated with the poll client  908  has an interest. 
         [0112]      FIG. 10  depicts a flowchart  1000  of an example of a method for content vetting. The method is organized as a sequence of modules in the flowchart  1000 . However, it should be understood that these and modules associated with other processes and methods described herein may be reordered for parallel execution or into different sequences of modules. 
         [0113]    In the example of  FIG. 10 , the flowchart  1000  starts at module  1002  with aggregating content in association with survey questions. The content, or an identification of or a link to the content, can be provided by a content contributor. The content contributor may or may not be the content creator or co-creator (e.g., an author, journalist, musician, artist, blogger, or other creator of content). The content contributor may or may not be the content provider. Indeed the content contributor might just be lucky enough to have stumbled across some interesting content and contributed with a link to the content. The content contributor may or may not also provide the survey questions with which the content is aggregated. In some implementations, the content contributor may have to provide the survey questions when contributing the content, but in other implementations the content contributor could have someone else provide the survey questions. 
         [0114]    In the example of  FIG. 10 , the flowchart  1000  continues to module  1003  with calculating apparent interest as a function of interaction with the content. Apparent interest can be calculated in a number of ways. One convenient technique involves allowing users to answer the survey questions. This is convenient because the survey questions were already provided in association with the content; so it is easy to display the questions in an effort to garner responses. Answering survey questions about content is also often a clear signal of interest in the content, whether positive or negative. Other techniques may include clicking on anything associated with the content on a content display. For example, if a user clicks “more” to view more of the content than is displayed, then that could be given some weight in gauging apparent interest. Users could also indicate they “like” the content, share the content, or interact with the content in some other way. 
         [0115]    Each of the interactions can be given the same weights or different weights depending upon the implementation. It should be noted that “no weight” is considered a weight in this context. For example, if a user interacts with the content but it is somehow possible to determine that the interaction was accidental, then the interaction might be given no weight. 
         [0116]    A simple function for calculating apparent interest is a sum of equally weighted interactions. The function could include any manipulation of values, though it may be desirable to implement a function that is convenient for a computer to calculate. Different types of interaction with the content may be weighted differently, and it may even be desirable to weight positive and negative interaction differently in some cases. However, as the state of the art shows, weighing positive and negative interest differently can result in bias. 
         [0117]    Negative interest is not disinterest. It is relatively well-known that in ranking sites almost anywhere on the Internet, negative reviews can be used to drag content down. The “bury brigades” of digg.com are but one example. On amazon.com, fans of a particular author or game can mark dissent as not of interest to most (and you actually have to click on the review that was hidden to be able to see it). It takes a very small vocal minority to accomplish these goals. For this reason, interest is better calculated using both positive and negative interactions with content. In the amazon.com example, it might be worthwhile to know when hidden reviews are read because it could be indicative of a general distrust of the visible reviews. 
         [0118]    In the example of  FIG. 10 , the flowchart  1000  continues to module  1004  with ranking aggregated content in accordance with apparent interest. Rankings can fluctuate over time. So, if the highest rankings in a time period are to be polled, it may be desirable to maintain a top 10 list the includes only the highest apparent interest over a time period, rather than just the current top 10. That way, even if one of the content items drops to below the top 10 by the time a poll opens, it will be polled because it was at one time during the period higher than a current content item in the top 10. Alternatively, it may be desirable to simply poll the top 10 content items taken as a snapshot when the poll opens. As another alternative, the content items might only decrease (due to aging) at the time a poll opens so that the highest apparent interest over a period of time is the highest apparent interest at the time the poll opens. Another option with ranking is to not use aging at all (or with limits). This can enable content items that have continuous apparent interest to eventually float to the top even if they never reach a fever pitch of interest. 
         [0119]    In the example of  FIG. 10 , the flowchart  1000  continues to decision point  1006  with determining whether to poll. If it is determined not to poll ( 1006 -N) then the flowchart  1000  returns to module  1004  and continues as described above. Determining whether to poll is implementation-specific. For example, it may be desirable to poll based upon the passage of a certain amount of time. Daily polls might be interesting if only the hottest topics are polled, but otherwise it might be desirable to spread polls out over a longer time frame (weeks or even months). With a sufficiently large sample size, you could conceivably poll different topics with different users, or allow users to indicate how frequently they want to be involved in polls; some will almost certainly want to be involved in polling more often than others. The apparent interest across multiple content items could be a reason to accelerate polling. Real world cycles could increase or decrease the polling rate, could be another (e.g., in a politics forum, it might be desirable to increase the polling rate near election dates). If compensation is offered to those who participate in polls, the polling rate could probably be increased, as well. In some implementations, content contributors might be able to pay to have their content polled, which could trigger an immediate poll, and the users who respond to the poll might be compensated for their participation. 
         [0120]    If, on the other hand, it is determined to poll ( 1006 -Y), then the flowchart  1000  continues to module  1008  with polling clients. Depending upon the implementation and/or configuration, one or both of vetted (known) and un-vetted (anonymous) clients can be polled. Either type of client can have a profile built for it based upon responses to polls (and interactions with content items and ads). Since the content items to be polled have the highest apparent interest values, which means more users probably helped to increase the apparent interest value, users are more likely to be interested in the results of the poll. Also, if there was an attempt to bury the content with negative comments, or make posting comments of a certain nature unpleasant, which will tend to drive some users away from a content item (at least the comments section), then the negative interest will help float the content item to the top and give it a fresh start, perhaps by wiping the older comments. 
         [0121]    In the example of  FIG. 10 , the flowchart  1000  continues to module  1010  with processing poll results. Different parties will find different value in the poll results. The content contributor might be interested in how popular the topic is or how there was an unsuccessful attempt to bury the content (e.g., by providing negative feedback, thereby raising the apparent interest of the content item, triggering a poll). An advertiser might be interested in how successful the contributor is with garnering interest in content, or what categories of users are interested in particular content. A user might want to establish a profile so that ads are more appropriate or they get credit for contributions. 
         [0122]    In the example of  FIG. 10 , the flowchart  1000  continues to module  1012  with reporting results. The report can enable comparisons of content from the content contributor with other content from the content contributor, the number of stars assigned by a vocal minority with the number of start from the polled majority, the interest in poll contributors with other content, the interest of poll contributors with one another, majority opinions regarding a content item with subjective opinions, and other applicable comparisons.