Abstract:
Many content systems (e.g., social networks) present to a user a set of content items posted by other individuals. The user may selectively view content items that reinforce and are consistent with the user&#39;s perspective, creating an “echo chamber” effect. Conversely, content systems that selectively expose users to content items exhibiting contrary perspectives, and from individuals with no connection with the user, may alienate the user. Presented herein are techniques for recommending content items that present a different perspective from that of the user, and from individuals who share a similar profile to the user (e.g., alternative opinions from other individuals within the user&#39;s social circle or community). Optionally, opinions may be selected that do not directly oppose the user&#39;s perspective, but that are orthogonal with it. Such selective recommendations may persuade the user to consider contrary viewpoints that may alter the user&#39;s perspective while reducing user alienation.

Description:
BACKGROUND 
       [0001]    Within the field of computing, many scenarios involve a content system that presents, to one or more users, content items authored by other users, such as stories and opinions written by contacts in the user&#39;s social network, and comments provided in a comment network. The user may browse an index of content items, such as the headlines of a set of news articles or the titles of user opinions, and may selectively choose to view only the content items that are of particular interest to the user. Some content systems may simply present the entire set of recent content items to the user, while other content systems may proactively recommend content items that may be of interest to the user. Such predicted interest may be based, e.g., upon other content items that the user has chosen to view, and/or upon the contents of the user profile of the user. 
       SUMMARY 
       [0002]    While the recommendation of content items may generally facilitate the user&#39;s engagement with content items that are of predictable interest to the user, such recommendations may disproportionately select content items that are consistent with the user&#39;s perspectives. As a first such example, for many users, content items that are similar to the user&#39;s perspectives may be of predictably higher interest than content items that conflict with such perspectives, and a predictive model may disproportionately select such content items for presentation to the user. As a second such example, if content items are selected for recommendation that are similar to previously viewed content items by the same user, and if the user preferentially views content items that are consistent with the user&#39;s perspectives, then the user is not exposed to alternative perspectives. Such scenarios may create an “echo chamber” effect, where the user is not exposed to, familiar with, or even aware of alternative perspectives, or even of the existing diversity of perspectives. 
         [0003]    Other techniques for presenting content items to the user may be designed that may reduce the “echo chamber” effect. For example, content items may be selected for recommendation that present perspectives opposing those of the user. However, the user may tend to disregard such recommendations based on the background of the individuals posting such opposing perspectives. As a first example, a user with a first cultural background may be presented a recommendation of a content item that was created and/or recommended by an individual of a second cultural background, but the user may dismiss the content item as not relevant or interesting to any individuals with the first cultural background. A content system that preferentially presents such recommendations may therefore alienate the user by presenting content items that the user deems to be irrelevant to the user&#39;s cultural background and interests. As a second example, a content system that recommends content items exhibiting perspectives that directly oppose the user&#39;s perspectives may be readily dismissed by the user. 
         [0004]    Presented herein are techniques for presenting content items to a user that may alter the user&#39;s perspectives while reducing the alienation of the user. In accordance with such techniques, a content system may identify associates of the user who have user profiles that are similar to the user, such as individuals within the user&#39;s community or social network; individuals whose interests are similar to those of the user; and individuals who have shared experiences that are similar to those of the user. The content system may identify content items of such associates that is different from the user perspective of the user, and may recommend such content items to the user. For example, a recommendation for a food type that the user may not typically find appealing may be of greater interest to the user if the source of the recommendation is a contact within the user&#39;s social network than if the source is an individual of a different cultural background. Additionally, the content system may also preferentially recommend content items that do not directly oppose the user perspective of the user, but that are orthogonal with the user perspective. For example, if the user finds a particular food type to be unpalatable (e.g., if the user does not like coffee), the content system may not recommend content items that exhort the palatability of the food type (such as coffee recipes or recommendations of nearby cafés), but, rather, content items that exhort other beneficial effects of the food type (e.g., the health benefits of drinking coffee regularly, and/or the socioeconomic promotion of local coffee farmers). By selectively recommending to the user content items that differ from the user perspective and that are from associates with a similar user profile in accordance with the techniques presented herein, a content system may persuade the user to consider alternative perspectives, expand the user&#39;s exposure to a range of perspectives, and reduce the “echo chamber” effect. 
     
    
     
       DESCRIPTION OF THE DRAWINGS 
         [0005]    While the techniques presented herein may be embodied in alternative forms, the particular embodiments shown in the drawings are only a few such examples that are supplemental of the description provided herein. These embodiments are not to be interpreted as limiting any aspect of the invention, which is defined by the claims appended hereto. 
           [0006]      FIG. 1  is an illustration of a scenario involving various examples of networks that may connect servers and clients. 
           [0007]      FIG. 2  is an illustration of a scenario involving an example configuration of a server that may utilize at least a portion of the techniques presented herein. 
           [0008]      FIG. 3  is an illustration of a scenario involving an example configuration of a client that may utilize at least a portion of the techniques presented herein. 
           [0009]      FIG. 4  is an illustration of a scenario involving a content delivery network (CDN) that may be utilized in conjunction with the techniques presented herein. 
           [0010]      FIG. 5  is an illustration of a scenario involving a content provider that presents content item recommendations to a user. 
           [0011]      FIG. 6  is an illustration of a scenario featuring a content provider that presents content item recommendations to a user in accordance with the techniques presented herein. 
           [0012]      FIG. 7  is an illustration of a scenario featuring an example method of presenting recommendations of content items to a user in accordance with the techniques presented herein. 
           [0013]      FIG. 8  is an illustration of a scenario featuring an example server that presents recommendations of content items to a user in accordance with the techniques presented herein. 
           [0014]      FIG. 9  is an illustration of a scenario featuring an example nontransitory memory device that causes a device to present recommendations of content items to a user in accordance with the techniques presented herein. 
           [0015]      FIG. 10  is an illustration of a scenario featuring a clustering of individuals in order to infer the user perspectives of a user in accordance with the techniques presented herein. 
           [0016]      FIG. 11  is an illustration of a scenario featuring a selection of user perspectives of a user in order to present recommendations of content items to the user in accordance with the techniques presented herein. 
           [0017]      FIG. 12  is an illustration of a scenario featuring a ranking of content items according to content item ratings in accordance with the techniques presented herein. 
           [0018]      FIG. 13  is an illustration of a scenario featuring a presentation of a layout of topics and associated word clouds for recommending and presenting content items to a user in accordance with the techniques presented herein. 
       
    
    
     DETAILED DESCRIPTION 
       [0019]    Subject matter will now be described more fully hereinafter with reference to the accompanying drawings, which form a part hereof, and which show, by way of illustration, specific example embodiments. This description is not intended as an extensive or detailed discussion of known concepts. Details that are known generally to those of ordinary skill in the relevant art may have been omitted, or may be handled in summary fashion. 
         [0020]    The following subject matter may be embodied in a variety of different forms, such as methods, devices, components, and systems. Accordingly, this subject matter is not intended to be construed as limited to any example embodiments set forth herein; example embodiments are provided merely to be illustrative. Such embodiments may, for example, take the form of hardware, software, firmware or any combination thereof (other than software per se). A reasonably broad scope for claimed or covered subject matter is intended. 
       1. Computing Scenario 
       [0021]    The following provides a discussion of some types of computing scenarios in which the disclosed subject matter may be utilized and/or implemented. 
       1.1. Networking 
       [0022]      FIG. 1  is an interaction diagram of a scenario  100  illustrating a service  102  provided by a set of servers  104  to a set of client devices  110  via various types of networks. The servers  104  and/or client devices  110  may be capable of transmitting, receiving, processing, and/or storing many types of signals, such as in memory as physical memory states. 
         [0023]    The servers  104  of the service  102  may be internally connected via a local area network  106  (LAN), such as a wired network where network adapters on the respective servers  104  are interconnected via cables (e.g., coaxial and/or fiber optic cabling), and may be connected in various topologies (e.g., buses, token rings, meshes, and/or trees). The servers  104  may also be interconnected directly, or through one or more other networking devices, such as routers, switches, and repeaters. The servers  104  may utilize a variety of physical networking protocols (e.g., Ethernet and/or Fibre Channel) and/or logical networking protocols (e.g., variants of an Internet Protocol (IP), a Transmission Control Protocol (TCP), and/or a User Datagram Protocol (UDP). The local area network  106  may also include, e.g., analog telephone lines, such as a twisted wire pair, a coaxial cable, full or fractional digital lines including T1, T2, T3, or T4 type lines, Integrated Services Digital Networks (ISDNs), Digital Subscriber Lines (DSLs), wireless links including satellite links, or other communication links or channels, such as may be known to those skilled in the art. The local area network  106  may be organized according to one or more network architectures, such as server/client, peer-to-peer, and mesh architectures, and/or also a variety of roles, such as administrative servers, authentication servers, security monitor servers, data stores for objects such as files and databases, business logic servers, time synchronization servers, and front-end servers providing a user-facing interface to the service  102 . 
         [0024]    Likewise, the local area network  106  may comprise one or more sub-networks, such as may employ differing architectures or may be compliant or compatible with differing protocols, may interoperate within the local area network  106 . Additionally, a variety of local area networks  106  may be interconnected; e.g., a router may provide a link between otherwise separate and independent local area networks  106 . 
         [0025]    In the scenario  100  of  FIG. 1 , the local area network  106  of the service  102  is connected to a wide area network  108  (WAN) that allows the service  102  to exchange data with other services  102  and client devices  110 . The wide area network  108  may encompass various combinations of devices with varying levels of distribution and exposure, such as a public wide-area network (e.g., the Internet), or a private network (e.g., a virtual private network (VPN) of a distributed enterprise). 
         [0026]    In the scenario  100  of  FIG. 1 , the service  102  may be accessed via the wide area network  108  by a user  112  of a set of client devices  110 , such as a portable media player (e.g., an electronic text reader, an audio device, or a portable gaming, exercise, or navigation device); a portable communication device (e.g., a camera, a phone, or a text chatting device); a workstation; and a laptop form factor computer. The respective client devices  110  may communicate with the service  102  via various connections to the wide area network  108 . As a first such example, one or more client devices  110  may comprise a cellular communicator, and may connect to the wide area network  108  via a wireless local area network  106  provided by a cellular provider. As a second such example, one or more client devices  110  may communicate with the service  102  by connecting to the wide area network  108  via a wireless local area network  106  provided by a location such as the user&#39;s home or workplace (e.g., a WiFi network or a Bluetooth personal area network). In this manner, the servers  104  and the client devices  110  may communicate over various types of networks. Other types of networks that may be accessed by the servers  104  and/or client devices  110  include mass storage, such as network attached storage (NAS), a storage area network (SAN), or other forms of computer or machine readable media. 
       1.2. Server Configuration 
       [0027]      FIG. 2  presents a schematic architecture diagram  200  of a server  104  that may utilize at least a portion of the techniques provided herein. Such servers  104  may vary widely in configuration or capabilities, alone or in conjunction with other servers  104 , in order to provide a service  102 . 
         [0028]    A server  104  may comprise one or more processors  210  that process instructions. The one or more processors  210  may optionally include a plurality of cores; one or more coprocessors, such as a mathematics coprocessor or an integrated graphical processing unit (GPU); and/or one or more layers of local cache memory. A server  104  may also comprise a memory  202  storing various forms of applications, such as an operating system  204 ; one or more server applications  206 , such as a hypertext transport protocol (HTTP) server, a file transfer protocol (FTP) server, or a simple mail transport protocol (SMTP) server; and/or various forms of data, such as a database  208  or a file system. The server  104  may also comprise a variety of peripheral components, such as a wired and/or wireless network adapter  214  connectible to a local area network  106  and/or wide area network  108 ; one or more storage components  216 , such as a hard disk drive, a solid-state storage device (SSD), a flash memory device, and/or a magnetic and/or optical disk reader. The server  104  may also comprise a mainboard featuring one or more communication buses  212  that interconnect the processor  210 , the memory  202 , and various peripherals, using a variety of bus technologies, such as a variant of a serial or parallel AT Attachment (ATA) bus protocol; the Uniform Serial Bus (USB) protocol; and the Small Computer System Interface (SCI) bus protocol. In a multibus scenario, a communication bus  212  may interconnect the server  104  with at least one other server  104 . Other components that may optionally be included with the server  104  (though not shown in the schematic diagram  200  of  FIG. 2 ) include a display; a display adapter, such as a graphical processing unit (GPU); input peripherals, such as a keyboard and/or mouse; and a flash memory device that may store a basic input/output system (BIOS) routine that facilitates booting the server  104  to a state of readiness. 
         [0029]    A server  104  may also operate in various physical enclosures, such as a desktop or tower, and/or may be integrated with a display as an “all-in-one” device. A server  104  may also be mounted horizontally and/or in a cabinet or rack, and/or may simply comprise an interconnected set of components. A server  104  may also comprise a dedicated and/or shared power supply  218  that supplies and regulates power for the other components. The server  104  may also provide power to and/or receive power from another server  104  and/or other devices. The server  104  may also comprise a shared and/or dedicated climate control unit  220  that regulates climate properties, such as temperature, humidity, and airflow. Many such servers  104  may be configured and/or adapted to utilize at least a portion of the techniques presented herein. 
       1.3. Client Device Configuration 
       [0030]      FIG. 3  presents a schematic architecture diagram  300  of a client device  110  operable by a user  112 , whereupon at least a portion of the techniques presented herein may be implemented. Such client devices  110  may vary widely in configuration or capabilities, in order to provide a variety of functionality to the user  112 . A client device  110  may be provided in a variety of form factors, such as a desktop or tower workstation; an “all-in-one” device integrated with a display  308 ; a laptop, tablet, convertible tablet, or palmtop device; a wearable device mountable in a headset, eyeglass, earpiece, and/or wristwatch, and/or integrated with an article of clothing; and a component of a piece of furniture, such as a tabletop, and/or of another device, such as a vehicle or residence. A client device  110  may also serve the user  112  in a variety of roles, such as a workstation, kiosk, media player, gaming device, and/or appliance. 
         [0031]    A client device  110  may comprise one or more processors  210  that process instructions. The one or more processors  210  may optionally include a plurality of cores; one or more coprocessors, such as a mathematics coprocessor or an integrated graphical processing unit (GPU); and/or one or more layers of local cache memory. A client device  110  may also comprise a memory  202  storing various forms of applications, such as an operating system  204 ; one or more user applications  302 , such as document applications, media applications, file and data access applications, communication applications such as web browsers and email clients, utilities, and games; and drivers for various peripherals. A client device  110  may also comprise a variety of peripheral components, such as a wired and/or wireless network adapter  214  connectible to a local area network  106  and/or wide area network  108 ; one or more output components, such as a display  308  coupled with a display adapter (optionally including a graphical processing unit (GPU)), a sound adapter coupled with a speaker, and a printer; input devices for receiving input from the user  112 , such as a keyboard  310 , a mouse, a microphone, a camera, and/or a touch-sensitive component of the display  308 ; and/or environmental sensors, such as a global positioning system (GPS) receiver  312  that detects the location, velocity, and/or acceleration of the client device  110 , and/or an compass, accelerometer, and/or gyroscope that detects a physical orientation of the client device  110 . Other components that may optionally be included with the client device  110  (though not shown in the schematic diagram  300  of  FIG. 3 ) include one or more storage components  216 , such as a hard disk drive, a solid-state storage device (SSD), a flash memory device, and/or a magnetic and/or optical disk reader; and/or a flash memory device that may store a basic input/output system (BIOS) routine that facilitates booting the client device  110  to a state of readiness; and a climate control unit that regulates climate properties, such as temperature, humidity, and airflow. 
         [0032]    A client device  110  may comprise a mainboard featuring one or more communication buses  212  that interconnect the processor  210 , the memory  202 , and various peripherals, using a variety of bus technologies, such as a variant of a serial or parallel AT Attachment (ATA) bus protocol; the Uniform Serial Bus (USB) protocol; and the Small Computer System Interface (SCI) bus protocol. A client device  110  may also comprise a dedicated and/or shared power supply  218  that supplies and regulates power for the other components, and/or a battery  304  that stores power for use while the client device  110  is not connected to a power source via the power supply  218 . The client device  110  may also provide power to and/or receive power from other client devices  110 . 
         [0033]    In some scenarios, as a user  112  interacts with a software application on a client device  110  (e.g., an instant messenger and/or electronic mail application), descriptive content in the form of signals or stored physical states within memory (e.g., an email address, instant messenger identifier, phone number, postal address, message content, date, and/or time) may be identified. Descriptive content may be stored, typically along with contextual content. For example, the source of a phone number (e.g., a communication received from another user  112  via an instant messenger application) may be stored as contextual content associated with the phone number. Contextual content, therefore, may identify circumstances surrounding receipt of a phone number (e.g., the date or time that the phone number was received), and may be associated with descriptive content. Contextual content, may, for example, be used to subsequently search for associated descriptive content. For example, a search for phone numbers received from specific individuals, received via an instant messenger application or at a given date or time, may be initiated. The client device  110  may also include one or more servers that may locally serve the client device  110  and/or other client devices  110  of the user  112  and other individuals. For example, a locally installed webserver may provide web content in response to locally submitted web requests. Many such client devices  110  may be configured and/or adapted to utilize at least a portion of the techniques presented herein. 
       1.4. Content Delivery Network 
       [0034]      FIG. 4  is an interaction diagram of a scenario  400  featuring a content delivery network, also sometimes referred to as a content distribution network or CDN. These terms generally refer to a distributed content delivery system that comprises a collection of computers or computing devices linked by a network or networks. A CDN may employ software, systems, protocols or techniques to facilitate various services, such as storage, caching, communication of content, or streaming media or applications. Services may also make use of ancillary technologies including, but not limited to, “cloud computing,” distributed storage, DNS request handling, provisioning, signal monitoring and reporting, content targeting, personalization, or business intelligence. A CDN may also enable an entity to operate or manage another&#39;s site infrastructure, in whole or in part. 
         [0035]    In the scenario  400  of  FIG. 4 , a set of content services  402  respectively comprise a content server  404  that provides access to a set of content items  406 , such as text articles, pictures, video, audio, applications, data files, and output from devices such as cameras. A content provider  408  is provided, comprising a content provider server  410  that interacts with the content services  402  over a wide area network  108 , such as the Internet, to index the content items  406  provided thereby. For example, the content provider server  410  may utilize a content crawler  412  that iteratively explores the content services  402  and generates a content index  414 . The content provider  408  may be deployed in a distributed manner across at least two content provider servers  410 , which may be organized by role (e.g., a first content provider server  410  maintaining the content index  414 , and a content provider server  410  interacting with users  112  and/or client devices  110 ) and/or geographically (e.g., various content provider servers  410  may be provided to service client devices  110  in different physical locations). Components may be duplicated within the content provider  408 ; e.g., two or more content provider servers  410  may be provided to facilitate the reliability, response time, and/or scalability of the content provider  408 . 
         [0036]    As further illustrated in the scenario  400  of  FIG. 4 , a user  112  of a client device  110  may engage in an interaction  416  with the content provider  408  and/or content services  402  in the following manner. For example, the client device  110  may present the content index  414  to the user  112 , e.g., as a set of categories of topics that may be of interest to the user  112 , such as articles about news stories, movies, music, or books. The user  112  may, through the client device  110 , initiate a content request  418 , such as a selection of a category from the content index  414 . The content provider  408  may examine the content index  414  to select content items  406  responsive to the content request  418 , and may generate a content response  420  including the selected content items  422  for presentation to the user  112 . The content provider  408  may also utilize other techniques and/or components, such as an index storage component, a search component, a ranking component, a cache, a profile storage component, a logon component, a profile builder, and one or more application program interfaces (APIs). Many such content providers  408  may be provided, and may variously utilize the techniques presented herein. 
         [0037]    In techniques such as those presented herein, content providers  408  may provide content stored by the same content provider  408  (e.g., a content provider  408  for a locally stored file system, database, or content library); for content stored by other content services  402 ; and/or for content stored by one or more client devices  110  (e.g., a cloud indexing service that indicates the availability of data objects on a distributed set of client devices  110  of the user  112 ). Additionally, such content providers  408  may provide a variety of content, including messages generated by and/or sent to the user  112 ; text articles; fiction and/or nonfiction stories; facts about topics such as individuals, companies, place; pictures; audio and video recordings; applications; data objects such as files and databases; and products or services. 
         [0038]    Content providers  408  may receive and process content requests  418  specified in a variety of modalities, including text, handwriting, speech, verbal cues or keywords, gestures, and body language. The content requests  418  may also be specified in a variety of organizational formats, such as a group of keywords, a Boolean logical structure or expression tree, or a natural-language speech. Additionally, the content provider  408  may select content items  406  that are responsive to the content request  418  in various ways, such as a hyperlink to a uniform resource identifier (URI) of the content item  406 ; a description of the content item  406 , such as the title, file type, generation date, synopsis, and/or preview version of the content item  406 ; and/or a copy of the full content item  406 . The content response  420  may also be presented to the user  112  in many ways, such as in the same presentation as a search interface (e.g., presented in the same web page as the search interface, as in above, below, aside, or in place of the search interface); in a second presentation that is distinct from but related to the search interface (e.g., presented in a second web page or popup window); and/or in a second presentation that is unrelated to the search interface, such as a separate application (e.g., receiving a content request  418  through a web browser and presenting the content response  420  in a second application) and/or a different modality as the search interface (e.g., receiving a content request  418  provided in a web page, and presenting to the user  112  an audially presented set of content items  422 ). 
       1.5. Content Item Recommendations 
       [0039]      FIG. 5  presents a scenario  500  featuring a second example of a content provider  408  in a content delivery network, wherein the content provider  408  presents content item recommendations  512  of content items  422  to the user  112 . In this scenario  500 , a set of individuals  502  may be associated with content items  422  about a particular topic  504  (e.g., articles, messages, or options that the individual  502  has generated, authored, referenced, and/or approved). While some content providers  408  may present all discovered content items  422  to the user  112  in an equivalent manner, other content providers  408  may be configured to present to the user  112  content item recommendations  512  of content items  422  that are of predicted interest to the user  112 . As a first such example, the content item recommendations  512  may be presented based on content item ratings by various individuals  502  (e.g., content items  512  that the entire body of individuals  502  have rated as most interesting). As a second such example, the content provider  408  may group the content items  422  according to an individual perspective  506  of the individual  502  about the topic  504 ; e.g., for a set of content items  422  about coffee, the content provider  408  may identify which content items  422  are associated with individuals  502  who exhibit a dislike of coffee and therefore express a negative perspective  506  about coffee, and which content items  402  are associated with individuals  502  who exhibit an appreciation of coffee and therefore express a positive perspective  506  about coffee. A user profile  508  of the user  112  may indicate a user perspective  510  of the user  112  about the topic  504  (e.g., that the user  112  exhibits a dislike of coffee), and the content provider  408  may compare the user perspective  510  of the user  112  with the individual perspectives  506  of the individuals  502  in order to select content items  422  as content item recommendations  512 . The selected content items  422  may be transmitted to a client device  110  of the user  112  (e.g., as a web page featuring the content item recommendations  512  as a title, preview, or summary of each selected content item  422 ), which the user  112  may select in order to view the full content item  422 . 
         [0040]    While the technique illustrated in the exemplary scenario  500  of  FIG. 5  may enable the presentation of content item recommendations  512  based on the user perspective  510  of the user  112 , some disadvantages may arise from this technique. 
         [0041]    As a first such example, a selection of content items  422  about a topic  504 , from individuals  502  whose individual perspective  506  about the topic  504  match the user perspective  510  of the user  112 , may result in a preferential exposure to the user  112  only of individual perspectives  506  that are consistent with the user perspective  510  of the user  112 , and that limits or eliminates exposure of the user  112  to alternative individual perspectives  506  about the topic  504 . Such altered exposure may create an “echo chamber” effect that disproportionately reinforces or strengthens the user perspective  510  of the user  112 , wherein the user  112  does not understand, is not familiar with, and perhaps is not even aware of alternative individual perspectives  506  about the topic  504 . 
         [0042]    As a second such example, the restriction of content item recommendations  512  to the user  112  that preferentially selects individual perspectives  506  about a topic  504  that are consistent with the user perspectives  510  of the user  112  about the topic  504  may be interesting some users  112 , but may not be interesting to more open-minded users  112  who appreciate a range of alternative individual perspectives  506  about various topics  504 . For example, a user  112  may not actually seek or appreciate reinforcement of the user perspectives  510  currently held by the user  112  about a topic  504 , but may seek exposure to new topics  504  and individual perspectives  506  that the user  112  has not previously considered. Accordingly, the presentation of content item recommendations  512  to such a user  112  may result in the presentation of content items  422  of diminished appeal to the user  112 . 
         [0043]    Conversely, the content provider  408  may present to the user  112  content item recommendations  512  for a topic  504  that feature content items  422  that present contrary individual perspectives  506  about the topic  504  to the user perspective  510  of the user  112  about the topic  504 . However, such content item recommendations  512  may alienate users  112  who are not open to contrary individual perspectives  506 . As a first such example, for a user  112  who expresses distaste for coffee, presenting a set of content items  422  that present an individual perspective  506  of appreciation for the taste of coffee may not be of interest to the user  112 , since the user  112  may not be persuaded to change his or her views about the taste of coffee simply through exposure to contrary individual perspectives  506 . As a second such example, if the content items  422  that are presented to the user  112  exhibit not only contrary individual perspectives  506  but also are associated with much different types of individuals  502  than the user  112  (e.g., as the opinions of individuals  502  from a much different age, culture, religion, political orientation, education level, and/or socioeconomic status than the user  112 ), the user  112  may be inclined to dismiss the contrary individual perspectives  506  outright, and/or to disregard the content item recommendations  512  as having no relevance to the user  112 . As a third such example, a user  112  may feel strongly about a topic  504 , such that the presentation of content items  42  exhibiting a directly opposite individual perspective  506  may prompt a negative response from the user  112  and an instinctive dismissal of the content item recommendations  512 . For these and other reasons, differences between the user perspectives  510  of the user  112  individual perspectives  506  of the individuals  502  associated with the content item recommendations  512  may cause some users  112  to feel alienated by the content item recommendations  512  of the content provider  408 . 
       2. Presented Techniques 
       [0044]      FIG. 6  is an illustration of a scenario  600  involving an alternative technique for presenting content item recommendations  512  to a user  112  in accordance with the techniques presented herein. 
         [0045]    In this scenario  600 , for a particular topic  504 , a content provider  408  receives a set of content items  422  that are respectively associated with an individual  502  who exhibits an individual perspective  506  about the topic  504 . The content provider  408  may therefore group the content items  422  according to the individual perspectives  506  about the topic  502 , and may utilize such groupings in the selection of content items  422  as content item recommendations  512  to be transmitted to a client device  110  for presentation to a user  112 . 
         [0046]    However, the selection of content items  422  as content item recommendations  512  may also involve a comparison of an individual background  602  of each individual  502  with a user background  604  of the user  112  (e.g., according to user background  604  about the user  112  stored in a user profile  508 ). For example, the comparison may involve the ages of the individuals  502  and the user  112 ; the professions of the individuals  502  and the user  112 ; the geographic locations of the individuals  502  and the user  112 ; the education level and/or socioeconomic status of the individuals  502  and the user  112 ; the affiliation of the individuals  502  and the user  112  with various organizations; and the sets of skills, hobbies, and/or topical interests of the individuals  502  and the user  112 . Among such individuals  502 , a selection may be performed of individuals  502  whose individual backgrounds  602  are most similar to that of the user background  604  of the user  112 . Then, among the selected individuals  502 , an identification may be performed of content items  422  that involve an individual perspective  506  about the topic  504  of the content item  422  that differ from the user perspective  510  of the user  112 . That is, the content provider  408  may identify content items  422  that were created, referenced, and/or approved by individuals  502  who have closely similar individual backgrounds  602  to the user background  604  of the user  112  (e.g., members of the same community or social network), and yet that express divergent individual perspectives  506  about a topic  604  than the user perspective  510  of the user  112  about the topic  604 . Such content items  422  may be transmitted by the content provider  408  to the client device  110  for presentation to the user  112  as content item recommendations  512 . 
       3. Technical Effect 
       [0047]    The techniques presented herein and illustrated in the scenario  600  of  FIG. 6  may provide a variety of technical effects for the client device  110  and/or the content provider server  410 . 
         [0048]    As a first technical effect, the identification and presentation of such content items  422  to the user  112  as content item recommendations  512  may be interesting, and possibly persuasive, to the user  112  for a variety of reasons. As a first such example, the user  112  may find interest in the fact that individuals  502  having very similar individual backgrounds  602  to the user background  604  of the user  112  hold divergent individual perspectives  506  about the topic  504  than the user perspective  510  of the user  112 , and may be persuaded to reconsider individual perspectives  506  that the user  112  might have otherwise disregarded as irrelevant to the user  112 . As a second such example, the user  112  may be interested in understanding the individual perspectives  506  about various topics  504  that are held by individuals  602  who are very similar to the user  112 . For instance, a member of a social group, such as a member of an organization such as a student body of a university, may feel compelled to understand the tastes and opinions of other individuals  502  within the social group, e.g., in order to fit in with and/or respect the opinions of the social group, and/or to identify conversation topics with other individuals  502  within the social group. Accordingly, such selectivity may improve the engagement of users  112  with the content provider  408 , e.g., by increasing the predicted interest and appeal of content item recommendations  512  that are presented to the user  112 . 
         [0049]    As a second technical effect, the identification of content item recommendations  512  in accordance with the techniques presented herein may improve the efficiency of the content provider  408  in presenting content items  422  to users  112 . For example, users  112  are often inclined to scroll through a continuous set of content item recommendations  512  until finding a content item  422  that is of interest to the user  112 , and may then select the content item  422  for viewing (e.g., “clicking through” from the content provider  408  to the content service  402  that hosts the content item  406 ). In such scenarios, each content item  406  that is presented to the user  112 , but that the user  112  skips over and does not select for viewing, represents a waste of resources on the part of the content provider  408  in selecting and transmitting the content item  406  to the user  112 . That is, presenting ten content item recommendations  406  to the user  112  that result in two “click-through” responses from the user  112  is more efficient than presenting fifty content item recommendations  406  that result in the same two “click-through” responses from the user  112 . In addition to promoting user engagement of the user  112  with the content provider  408 , such improvements in efficiency may conserve the resources of the content provider  408  in reducing the number of content item recommendations  512  that are not of interest to the user  112 . Such efficiency improvements may also promote the scalability of the content provider  408  to serve a larger number of users  112 . 
         [0050]    As a third technical effect, the use of the techniques presented herein may facilitate the efficiency of the client device  110 . For example, many client devices  110 , such as mobile phones, feature only a small display  308 , a limited-capacity network connection, and/or a limited-capacity battery  304 . The use of the techniques presented herein to reduce the set of content item recommendations  512  to a smaller set that is of greater probable interest to the user  112  may reduce the inefficient consumption of the resources of the client device  110  in presenting other content item recommendations  512  that are not of interest to the user  112 . These and other technical effects may be achievable through the selection of content item recommendations  512  in accordance with the techniques presented herein. 
       4. Example Embodiments 
       [0051]      FIG. 7  presents an illustration of a first example embodiment of the techniques presented herein, illustrated as an example method  700  of presenting a content item recommendation  512  to a user  112  having a user background  604 . The example method  700  may be implemented, e.g., as instructions stored in a memory (e.g., a hard disk drive, a solid-state storage device such as a flash memory device, or a magnetic or optical disc) that, when executed on a processor  210  of a computer such as a client device  112  and/or a server  104 , cause the computer to operate according to at least a portion of the techniques presented herein. The example method  700  begins at  702  and comprises identifying  704  a user perspective  510  of the user  112  about a topic  504 . The example method  700  further comprises selecting  706 , from an individual set, an individual  502  having an individual background  602  that is similar to the user background  604  of the user  112 . The example method  700  further comprises identifying  708  a content item  422  that is associated with the individual  502 , and that presents an individual perspective  506  about the topic  504  that differs from the user perspective  510  of the user  112  about the topic  504 . The example method  700  further comprises presenting  710  the content item  422  to the user  112 . In this manner, the example method  700  achieves the presentation of the content item recommendation  512  to the user  112  in accordance with the techniques presented herein, and so ends at  712 . 
         [0052]      FIG. 8  presents an illustration of a scenario  800  involving a second example embodiment of the techniques presented herein, comprising a server  802  that presents a content item recommendation  512  of a content item  422  to a user  112 . The server  802  may comprise a processor  210 , and a memory (e.g., a hard disk drive, a solid-state storage device such as a flash memory device, or a magnetic or optical disc) storing a user profile  508  of the user  112  that includes a user background  604  (e.g., information about the user&#39;s demographics, skills, interests, and experiences), and instructions that provide the components of an example system  804  that causes the server  802  to present a content item recommendation  512  to a user  112 . In particular, the example system  804  comprises a user perspective determiner  806  that identifies a user perspective  510  of the user  112  about a topic  504 . The example system  804  also comprises a content item recommender  808  that selects, from an individual set, an individual  502  having an individual background  602  that is similar to the user background  604  of the user  112 , and identifies a content item  422  that is associated with the individual  502  and that presents an individual perspective  506  about the topic  504  that differs from the user perspective  510  of the user  112  about the topic  504 . The example system  804  also comprises a content item presenter  810  that presents the content item  422  to the user  112  (e.g., by transmitting the content item recommendations  512  to the client device  110  for presentation to the user  112 ). In this manner, the server  802  in the scenario  800  of  FIG. 8  presents content item recommendations  512  to the user  112  in accordance with the techniques presented herein. 
         [0053]      FIG. 9  is an illustration of a scenario  900  involving a third example embodiment of the techniques presented herein, comprising an example nontransitory memory device  902 , such as a memory semiconductor (e.g., a semiconductor utilizing static random access memory (SRAM), dynamic random access memory (DRAM), and/or synchronous dynamic random access memory (SDRAM) technologies), a platter of a hard disk drive, a flash memory device, or a magnetic or optical disc (such as a CD, DVD, or floppy disk). The example nontransitory memory device  902  stores computer-readable data  904  that, when subjected to reading  906  by a reader  901  of a device  908  (e.g., a read head of a hard disk drive, or a read operation invoked on a solid-state storage device), express processor-executable instructions  912 . The processor-executable instructions  912 , when executed on a processor  916  of the device  908 , cause the device  908  to present a content item recommendation  512  to a user  112 . In particular, the processor-executable instructions  912  cause the device  908  to identify  704  a user perspective  510  of the user  112  about a topic  504 . The processor-executable instructions  912  also cause the device  908  to select,  706 , from an individual set, an individual  502  having an individual background  602  that is similar to the user background  604  of the user  112 . The processor-executable instructions  912  also cause the device  908  to identify  708  a content item  422  that is associated with the individual  502 , and that presents an individual perspective  506  about the topic  504  that differs from the user perspective  510  of the user  112  about the topic  504 . The processor-executable instructions  912  also cause the device  908  to present  710  the content item  422  to the user  112 . In this manner, the example nontransitory memory device  902  causes the device  908  to present the content item recommendation  512  to the user  112  in accordance with the techniques presented herein. 
       5. Variations 
       [0054]    The techniques discussed herein may be devised with variations in many aspects, and some variations may present additional advantages and/or reduce disadvantages with respect to other variations of these and other techniques. Moreover, some variations may be implemented in combination, and some combinations may feature additional advantages and/or reduced disadvantages through synergistic cooperation. The variations may be incorporated in various embodiments (e.g., the example method  700  of  FIG. 7 ; the example system  804  of  FIG. 8 ; and the example nontransitory memory device  902  of  FIG. 9 ) to confer individual and/or synergistic advantages upon such embodiments. 
       5.1. Identifying User Perspectives 
       [0055]    A first aspect that may vary among embodiments of the presented techniques involves the manner of identifying the user perspectives  510  of the user  112  about various topics  504 . 
         [0056]    As a first variation of this first aspect, the user perspectives  510  of the user  112  may be detected by explicit statements by and/or descriptors of the user  112 . For example, the user  112  may specify one or more user perspectives  510  in a message, such as an email message, a chat message, or a post on a social network or a web forum. 
         [0057]    As a second variation of this first aspect, the user perspectives  510  of the user  112  may be inferred from other information in the user background  604  of the user  112 . 
         [0058]    As a first example of this second variation of this first aspect, correlation of the demographics of various individuals  502  with individual perspectives  506  that are frequently held by individuals  502  with such demographics (e.g., age, culture, educational and/or professional history, income level, geographic location of residence, skills, experiences, and/or interests) may enable an inference of the user perspectives  510  of the user  112  based on the demographics of the user  112 . 
         [0059]    As a first example of this second variation of this first aspect, an identification of the individual perspectives  506  that are frequently held by a user set that includes the user  112  (e.g., the user&#39;s social network, or an organization with which the user  112  is affiliated, such as a business, school, or community) may enable an evaluation of the individual perspectives  506  of the individuals  502  comprising the user set, and thus an inference of the user perspectives  510  of the user  112 . For example, respective messages that are expressed by the members of the user set may be evaluated to identify at least one identifier in the message (e.g., a name, term, phrase, URL, or hashtag that often arises in the messages expressed by individuals  502  having a particular user perspective  510 ), and the identifiers may be correlated with a user perspective  510  of the member about the topic. 
         [0060]      FIG. 10  is an illustration of a scenario  1000  featuring an application of this first example of this second variation of this first aspect. In this scenario  1000 , individuals  502  are clustered according to various demographics, which are depicted as a first axis  1002  representing the ages of the individuals  502  and a second axis  1002  representing the educational levels of the individuals  502 . Additional axes  1002  (not illustrated) may be utilized to map the individuals  1004  in higher dimensions, such as a third axis  1002  representing cultures, and a fourth axis  1002  representing income levels. A cluster  1004  of individuals  502  may be identified, comprising individuals  502  that share a proximity when mapped according to the axes  1002 . A first individual perspective  506  about a topic  504  that is shared  1006  by many individuals  502  may be identified, and may be imputed to a user  112  that is also within the cluster  1004 . Additionally, if a second user perspective  510  about the topic  504  is identified that differs from the first user perspective  501  is associated with and/or expressed by another individual  502  of the cluster  1004 , the second user perspective  510  may be selected for presentation to the user  112 . 
         [0061]    As a third variation of this first aspect, among the user perspectives  510  of the user  112 , particular user perspectives  510  may be selected as amenable to the presentation of differing individual perspectives  506  in accordance with the techniques presented herein. As a first such example, identifying the user perspective  510  of the user  112  may comprise, the respective topics  504  that are associated with a user perspective  510  of the user  112  may be ranked according to a user perspective score of the user perspective  510  about the topic  504 , e.g., the level of interest and/or the strength of the opinion of the user  112  about the user perspective  510  and/or the topic  504 . A representative user perspective subset of the user  112  may be selected according to the user perspective scores of the user perspectives  510  about the topic  504 , about which differing individual perspectives  504  may be identified and presented to the user  112 . As a first further variation, selecting the representative user perspective subset may involve excluding an excluded user perspective  510  that has a user perspective score about the topic  504  that is above a maximum user perspective score threshold (e.g., if the user  112  holds a particularly strong opinion and/or knowledge about a topic  504 , presenting differing individual perspectives  504  may have a greater likelihood of alienating the user  112 ). As a second further variation, selecting the representative user perspective subset may involve excluding an excluded user perspective  510  that has a user perspective score about the topic  504  that is below a minimum user perspective score (e.g., if the user  112  is particularly uninterested in, uninformed about, and/or apathetic about a particular topic  504 , presenting differing individual perspectives  504  from other individuals  502  may not be of significant interest to the user  112 ). 
         [0062]      FIG. 11  presents an illustration of a scenario  1100  featuring one such technique for selecting  1108  a subset of user perspective  510  of a user  112 . In this scenario  1100 , the user perspectives  510  of the user  112  about various topics  504  may be assigned a user perspective score  1102  (e.g., a metric of the user&#39;s polarity, knowledge, and/or interest in a particular topic  504 ), which may be assessed, e.g., according to how often the user  112  refers to the topic  504  in conversation; the tone of expressions of the user  112  while discussing the topic  504  and/or the user perspective  510 ; and/or the user background  604  of the user  112 . Sorting  1104  by user perspective scores  1102  may be applied to the user perspectives  510 , and a maximum user perspective score threshold  1106  may be applied to remove a user perspective  510  about which the user  112  is so polarized that the presentation of differing individual perspectives  504  may be undesirable. A selection  1108  of the topic two user perspectives  510  among the remaining user perspectives  510  may enable an identification of the topics  504  about which differing individual perspectives  504  of other individuals  502  may be desirably identified and selected in accordance with the techniques presented herein. 
       5.2. Identifying Individuals and Content Items 
       [0063]    A second aspect that may vary among embodiments of the presented techniques involves the manner of selecting individuals  502  based on a similarity of the background individual background  602  of the individual  502  to the user background  604  of the user  112 , and choosing the content items  422  associated with a selected individual  502  for presentation to the user  112 . 
         [0064]    As a first variation of this second aspect, the individual  502  may be selected by comparing respective individual background details of the individual background  602  of the individual  502  to the user background  604  of the user  112  to determine the similarity of the individual background  602  and the user background  604 . For example, a clustering technique, such as provided in the scenario  1000  of  FIG. 10 , may be utilized to determine a cluster  1004  of individuals  502  that are similar to the user  112 . In some such variations, a similarity score may be generated that quantifies the similarity of the respective individuals  502  to the user  112 , and the individuals  502  may be ranked according to the similarity score. 
         [0065]    As a second variation of this second aspect, an individual  502  may be selected according to a network distance of the individual  502  and the user  112  within an individual set, such as the proximity of the user  112  and the individual  502  within a family tree, an organizational hierarchy, and/or a social network. 
         [0066]    As a third variation of this second aspect, the individual perspectives  506  associated with various content items  422  of a selected individual  502  may be determined in various ways in the context of determining a degree of perspective difference between the user perspective  510  of the user  112  and the individual perspective  506  of the individuals  502  in order to select a content item  422  presenting a perspective difference. In a first such variation, a perspective score may be generated that quantifies the individual perspective  506  of the individual  502  and/or the content item  422 . For example, an evaluation of various sources of discussion of a topic  504 , such as a political issue, may enable the identification of keywords that are correlated with various individual perspectives  506  (e.g., individuals  502  discussing the topic  504  from a first individual perspective  506  may commonly use a first set of terms, while individuals  502  discussing the topic  504  from a second individual perspective  506  may commonly use a second set of terms). The frequencies of the terms used in a content item  422  may therefore enable a calculation of a perspective score indicating the strength and/or confidence of the correlation of the content item  422  and/or the individual  502  with a particular individual perspective  506 . As a further such variation, a perspective difference score may be calculated between the individual perspective  506  of the individual  502  and/or the content item  42 , and the user perspective  510  of the user  112 ; and among a set of content items  422 , a particular content item  422  may be selected that has a perspective difference score within a perspective difference score range (e.g., at least 50% different from the user perspective  510  of the user  112 , but less than 80% different from the user perspective  510  of the user  112 , as presenting a content item  422  from a strongly conflicting individual perspective  506  on a highly polarized topic  504  may alienate the user  112 ). 
         [0067]    As a fourth variation of this second aspect, the user  112  may be evaluated to determine the openness and/or interest of the user  112  in receiving recommendations of content items  422  exhibiting individual perspective  506  that present varying degrees of difference from the user perspective  510  of the user  112 . For example, some users  112  may be receptive to highly differing individual perspectives  506 , while others may be only interested in modest differences. Conversely, some users  112  may be interested in content items  422  that are modestly different from the user perspective  510  of the user  112  (e.g., those that add subtlety, nuance, or qualifications to the user perspective  510  of the user  112 ), while other users  112  may not be interested in content items  422  that exhibit individual perspectives  506  that are too similar to the user perspective  510  of the user  112  (e.g., users  112  who are eager to avoid the “echo chamber” effect). Accordingly, in one such variation, the user  112  is associated with a diversity score, and the perspective difference score between the individual perspective  506  of the respective content items  422  and the user perspective  510  of the user  112  about the topic  504  may be calculated, and compared with the diversity score in order to select content items  422  for recommendation to the user  112 . 
         [0068]    As a fifth variation of this second aspect, a content item  422  may be identified and selected that presents an individual perspective  506  that differs from the user perspective  510  of the user  112  about the topic  504 , but that does not oppose the user perspective  510  of the user  112  about the topic  504 . That is, on a particular topic  504 , such as coffee, various content items  422  may be associated with individual perspectives  506  that are aligned across a variety of perspective axes, such as the taste of coffee (tastes good vs. tastes bad); the health consequences of drinking coffee (improves health vs. debilitates health); the social implications of drinking coffee (coffee is stylish vs. coffee is tacky); and the economic implications of drinking coffee (purchasing coffee is economically beneficial vs. purchasing coffee is economically damaging). If a user  112  has developed a strong user perspective  510  about a topic  504  along a first axis, the user  112  might not be interested in content items  422  exhibiting an individual perspective  506  that directly conflicts with the user perspective  510 , but may be interested in content items  422  that exhibit an individual perspective  506  along a different axis that the user  112  has not previously considered. 
         [0069]    As a sixth variation of this second aspect, a content item  422  may be identified and selected according to user ratings of the content item  422 . For example, upon receiving, from a first user  112 , at least one user rating of the content item  422 , an embodiment may store the user rating of the content item  422 , and may identify a content item  422  for presentation to a second user  112  according to the user ratings stored for the content item  422  (e.g., selecting a content item  422  that is not only associated with an individual  502  having a similar individual background  602  to the user background  604  of the user  112  and that presents an individual perspective  506  that differs from the user perspective  510  of the user  112 , but that also is highly rated among a set of users  112 ). Such user ratings may reflect, e.g., the novelty of an individual perspective  506  that is expressed by the content item  422 ; the persuasiveness and/or coherence with which the content item  422  expresses the individual perspective  506  of a user  502 ; and/or the accuracy and/or precision with which a content item  422  expresses the individual perspective  506  of a particular individual  502 . 
         [0070]      FIG. 12  presents an illustration of a scenario  1200  featuring the selection of content items  422  for topics  502  based on a user rating  1202 . In this scenario  1200 , a set of individuals  502  may rate the individual perspectives  506  of various content items  422 , e.g., as an individual perspective rating  1202  comprising the ratio of the number of individuals  502  who express approval or appreciation of a particular content item  422  and the number of individuals  502  who express disapproval or dislike of the content item  422 . An individual perspective rating threshold may be applied to avoid selecting content items  422  having a comparatively low individual perspective rating  1202 , and a selection  1008  may be applied to the content items  422  presenting a comparatively high individual perspective rating  1202 . These and other techniques may be utilized to select the individuals  502  and the content items  422  associated therewith in accordance with the techniques presented herein. 
       5.3. User Interface 
       [0071]    A third aspect that may vary among embodiments of the presented techniques involves the user interface whereby a user  112  is recommended a set of content items  422  that relate to various topics  504 , and through which the user  112  may select a content item  422  for presentation. 
         [0072]    As a first variation of this third aspect, a user interface my present to the user  112  a collection of topics  504  about which at least one content item  422  is available that is associated with an individual  502  having an individual background  602  that is similar to the user background  604  of the user  112 , and that presents an individual perspective  506  that is different from the user perspective  510  of the user  112  about the topic  504 ). Upon receiving form the user  112  a selection of a topic  504 , the user interface may recommend the content items  422  that are associated with the selected topic  504 ; and upon receiving a selection of a recommended content item  422 , the user interface may present the selected content item  422  to the user  112 . 
         [0073]    As a second variation of this third aspect, a user interface may present the content items  422  and/or topics  504  to the user  112  in the form of a visual cloud, such as a word cloud of the topics  504  represented by various content items  422 . Alternatively or additionally, a user interface may select a center coordinate, and may present respective content items  422  by calculating a polar offset of the content item  422  (e.g., according to the age of the content item  422 , a perspective difference score between the individual perspective  506  of the content item  422  and the user perspective  510  of the user  112 , and/or the individual perspective rating  1202  of the content item  422 ). As one example, the polar coordinate may be calculated according to the formulae: 
         [0000]        r=c√{square root over (n)};θ=n ×φ,
 
         [0074]    wherein r is the distance of the content item  422  from the center coordinate; 
         [0075]    c is a constant defining the spatial separation of the content items  422  presented in the radial interface; 
         [0076]    n is the age of the content item  422  (e.g., in hours or days since creation and/or publication); 
       θ is the radial offset of the content item  422 ; and 
       [0077]    φ is a constant such as the golden ratio (defined as approximately 1.618). 
         [0078]    The user interface may then present the content item  422  at the polar offset with respect to the center coordinate. In a still further variation, respective topics  504  may be presented peripherally to the visual cloud of the content items  422 , optionally with a Bezier curve connecting sets of content items  422  with the peripherally presented topic  504  that is associated with the content items  422 . Alternatively or additionally, a visual style may be selected for the respective topics  504 , and the user interface may present the content items  422  in the visual style that has been selected for the topic  504  of the content item  422 . Alternatively or additionally, at the polar coordinate, the user interface may present a preview of the selected content item  422 ; and upon receiving from the user  112  an activation of a particular content item  422 , the user interface may present the activated content item  422  to the user  112 . 
         [0079]      FIG. 13  presents an illustration of a scenario  1300  featuring an example user interface  1302  for presenting a set of content items  422  to a user  112 . In this scenario  1300 , the user interface  1302  is centered around a center coordinate  1304 , and for various content items  422 , a circle  1306  is depicted representing the content item  422 . The circles  1306  are arrayed along Bezier curves that radiate outward toward a peripherally presented word cloud  1308  that indicates the topic  504  of the circles  1306  along each Bezier curve. A selection  1310  of a circle  1306  causes a presentation of the content item  422  recommended to the user  112 . In this manner, the user interface  1302  may present a topically oriented arrangement of recommended content items  422  to the user  112  in accordance with the techniques presented herein. 
       6. Usage of Terms 
       [0080]    Although the subject matter has been described in language specific to structural features and/or methodological acts, the subject matter defined in the appended claims is not necessarily limited to the specific features or acts described above. Rather, the specific features and acts described above are disclosed as example implementations of the claims. 
         [0081]    Although the disclosed subject matter has been shown and described with respect to one or more implementations, equivalent alterations and modifications may occur to others skilled in the art based upon a reading and understanding of this specification and the annexed drawings. The disclosure includes all such modifications and alterations and is limited only by the scope of the following claims. In particular regard to the various functions performed by the above described components (e.g., elements, resources, etc.), the terms used to describe such components are intended to correspond, unless otherwise indicated, to any component which performs the specified function of the described component (e.g., that is functionally equivalent), even though not structurally equivalent to the disclosed structure which performs the function in the herein illustrated example implementations of the disclosure. In addition, while a particular feature of the disclosure may have been disclosed with respect to only one of several implementations, such feature may be combined with one or more other features of the other implementations as may be desired and advantageous for any given or particular application. 
         [0082]    The claimed subject matter may be implemented in various ways, such as a method, an apparatus, or an article of manufacture. Each such implementation may utilize standard programming and/or engineering techniques to produce software, firmware, hardware, or any combination thereof to control a computer to implement the disclosed subject matter. Of course, those skilled in the art will recognize many modifications may be made to this configuration without departing from the scope or spirit of the claimed subject matter. 
         [0083]    Various operations of embodiments are provided herein. In one embodiment, one or more of the operations described may constitute computer readable instructions stored on one or more computer readable media, which if executed by a computing device, will cause the computing device to perform the operations described. The order in which some or all of the operations are described should not be construed as to imply that these operations are necessarily order dependent. Alternative ordering will be appreciated by one skilled in the art having the benefit of this description. Further, it will be understood that not all operations are necessarily present in each embodiment provided herein. 
         [0084]    As used herein and unless specified otherwise or clear from context, terms such as “and”, “or”, or “and/or,” may include a variety of meanings that may depend at least in part upon the context in which such terms are used. Typically, “or” if used to associate a list, such as A, B or C, is intended to mean A, B, and C, here used in the inclusive sense, as well as A, B or C, here used in the exclusive sense. In addition, the term “one or more” as used herein, depending at least in part upon context, may be used to describe any feature, structure, or characteristic in a singular sense or may be used to describe combinations of features, structures or characteristics in a plural sense. 
         [0085]    As used herein and unless specified otherwise or clear from context, the term “or” is intended to mean an inclusive “or” rather than an exclusive “or”. 
         [0086]    As used herein and unless specified otherwise or clear from context, the terms “a,” “an,” or “the” may convey either a singular usage or a plural usage. 
         [0087]    As used herein and unless specified otherwise or clear from context, the terms “first,” “second,” etc. are not intended to imply a temporal aspect, a spatial aspect, an ordering, etc. Rather, such terms are merely used as identifiers, names, etc. for features, elements, items, etc. For example, the terms “a first object” and “a second object” generally correspond to object A and object B, or two different objects, or two identical objects, or the same object. 
         [0088]    As used herein and unless specified otherwise or clear from context, the terms “includes”, “having”, “has”, “with”, and variants thereof are used in either the detailed description or the claims, such terms are intended to be inclusive in a manner similar to the term “comprising.” 
         [0089]    As used herein and unless specified otherwise or clear from context, the phrase “at least one of,” such as “at least one of A and B,” generally means A, or B, or both A and B. 
         [0090]    As used herein and unless specified otherwise or clear from context, the term “example” is used herein to mean serving as an example, instance, illustration, etc., and not necessarily as advantageous. Any aspect or design described herein as “example” is not necessarily to be construed as advantageous over other aspects or designs. Rather, use of the word example is intended to present concepts in a concrete fashion. 
         [0091]    As used herein and unless specified otherwise or clear from context, the term “based on” may be understood as not necessarily intended to convey an exclusive set of factors and may, instead, allow for existence of additional factors not necessarily expressly described, again, depending at least in part on context. 
         [0092]    As used herein and unless specified otherwise or clear from context, the terms “component,” “module,” “system”, “interface”, and the like are generally intended to refer to a computer-related entity, either hardware, a combination of hardware and software, software, or software in execution. For example, a component may be, but is not limited to being, a process running on a processor, a processor, an object, an executable, a thread of execution, a program, and/or a computer. By way of illustration, both an application running on a controller and the controller can be a component. One or more components may reside within a process and/or thread of execution and a component may be localized on one computer and/or distributed between two or more computers. 
         [0093]    As used herein and unless specified otherwise or clear from context, the term “article of manufacture” as used herein is intended to encompass a computer program accessible from any computer-readable device, carrier, or media.