Dynamic inclusion thresholds for social network conversations

A social network conversation dynamic inclusion threshold is obtained that causes a first subset of social network group members of a social network group to be included in a social network conversation earlier than at least one other social network group member and that further causes the at least one other social network group member to be included in the social network conversation upon satisfaction of the obtained social network conversation dynamic inclusion threshold. In accordance with the obtained social network conversation dynamic inclusion threshold, social network posts of the social network conversation are contemporaneously distributed to the first subset of social network group members and delayed in distribution to the at least one other social network group member. Upon satisfaction of the social network conversation dynamic inclusion threshold, the social network posts of the social network conversation are distributed to the at least one other social network group member.

BACKGROUND

The present invention relates to social network communications. More particularly, the present invention relates to dynamic inclusion thresholds for social network conversations.

Social networks provide social network users with a way to communicate with one another in an online environment. The social network users may share photographs and stories, and may communicate with each other within the social network environment.

BRIEF SUMMARY

A computer-implemented method includes: obtaining a social network conversation dynamic inclusion threshold that causes a first subset of social network group members of a social network group to be included in a social network conversation earlier than at least one other social network group member and that further causes the at least one other social network group member to be included in the social network conversation responsive to satisfaction of the obtained social network conversation dynamic inclusion threshold; contemporaneously, in accordance with the obtained social network conversation dynamic inclusion threshold, each of distributing social network posts of the social network conversation to the first subset of social network group members and delaying distribution of the social network posts of the social network conversation to the at least one other social network group member; and distributing, in response to satisfaction of the social network conversation dynamic inclusion threshold, the social network posts of the social network conversation to the at least one other social network group member.

A system that performs the method and a computer program product that causes a computer to perform the method are also described.

DETAILED DESCRIPTION

The subject matter described herein provides dynamic inclusion thresholds for social network conversations. The technology described herein solves a recognized social network conversation problem by providing a new form of computing technology that dynamically includes social network users within social network conversations over time in accordance with social network conversation dynamic inclusion thresholds. The social network conversation problem was recognized as resulting from online communications lacking face-to-face feedback of how commentary is perceived by other group members. As a consequence certain social network group members may not post their contributions to social network conversations to avoid perceived contradiction of other members. This social network conversation problem was recognized to be compounded in circumstances where certain styles of commentary (e.g., a strong positive or negative opinion) are expressed by the other members early in an online conversation. This dynamic of social network conversations was determined to cause conversations to terminate earlier than they otherwise would terminate, with a coincident lack of sufficient diversity and objectivity of perspective to provide objective value to social network groups as a whole.

To solve this recognized problem, and to enhance diversity and objectivity of perspective in social network conversations, the present technology provides social network conversation dynamic inclusion thresholds (hereinafter “dynamic inclusion thresholds” for ease of reference). The dynamic inclusion thresholds may be configured to programmatically provide certain identified social network group members that otherwise may not contribute to social network conversations with an opportunity to contribute and be included in online conversations by delaying delivery of social network posts to social network group members that historically post commentary that may lack objective contribution/assistance to other members of the social network group. As such, the dynamic inclusion thresholds perform a dual role of operating to dynamically “include” members of social network groups that otherwise may not contribute to social network conversations, and by also contemporaneously operating to dynamically “include” members with particular styles of historical communication patterns to conversations over time. Both forms of inclusion may be dynamically adjusted in real time as social network conversations unfold within a social network. Accordingly, the present technology may facilitate more balanced, objective, and comprehensive social network conversations with an increased diversity of participants, commentary, and perspective.

In operation, a social network conversation dynamic inclusion threshold is obtained that causes a first subset of social network group members to be included in a social network conversation earlier than at least one other social network group member and that further causes the at least one other social network group member to be included in the social network conversation responsive to satisfaction of the configured social network dynamic inclusion threshold. In accordance with the configured social network conversation dynamic inclusion threshold, social network posts of the social network conversation are contemporaneously delivered to the first subset of social network group members while delivery is delayed to the at least one other social network group member. In response to satisfaction of the social network conversation dynamic inclusion threshold, the social network posts of the social network conversation are distributed to the at least one other social network group member.

The social network group members for which delivery of posts is delayed may be determined, for example by text analysis of social network conversations over time, to express a particular style of commentary (e.g., a strong opinion, un-objective commentary, etc.) that is also determined over time, again such as by text analysis of social network conversations, to deter commentary and contribution from other group members. The dynamic inclusion thresholds allow these other social network group members that first receive the social network posts to contribute to social network conversations without feeling like the conversation is already concluded and without feeling that commentary may be perceived as contradicting strong opinions of others expressed earlier in the online conversation. The social network group member with the particular style of commentary may be included in social network conversations after the configured dynamic inclusion threshold is satisfied or expired to ensure that all social network group members have an opportunity to contribute to the online conversation.

As described above and in more detail below, social network conversations of a social network group may be analyzed over time to recognize patterns of both communication and non-communication responsive to commentary by other group members. Trends of response rates may also be analyzed, such as response rates of social network users relative to one another. For example, the present technology may determine by analysis of social network conversations that certain social network group members contribute to conversations when provided with a reasonable opportunity (e.g., time period or other criteria) to contribute, but that these same social network group members do not contribute if a particular style of perspective has already been expressed/communicated. In such a circumstance, the present technology may infer that these social network group members interpret the conversation to be concluded or that commentary may be perceived as contradicting opinions of other, and may further infer that the group member with the particular style of perspective may feel a need to reiterate their perspective if any other commentary is added to the conversation. While this is a delicate situation among social network group members, the present technology operates programmatically to mitigate these types of potentially unintentional interactions that may be perceived to actually inhibit open communication and participation within social network groups over time. As such, the present technology implements the dynamic inclusion thresholds to attempt to foster and build coherence and to strengthen social network groups over time by ensuring that all group members have a chance to express their opinions and comment on issues that are relevant to the particular social network group.

As introduced above, a particular social network group member that, for example, dominates social network conversations may be inferred/determined by analytical recognition that other social network group members contribute to the social network conversations less often when the particular social network group member contributes with a particular style of commentary (e.g., such as by contributing early in the conversation with a positive or negative strong opinion). This tendency to express strong opinions earlier in conversations may be exacerbated where the dominant social network group member is online more often than other group members.

A social network conversation dynamic inclusion threshold may be configured that causes certain social network group members to be included earlier in future online conversations and that causes other social network group members to be included later in conversations (e.g., particular members may be deferred from initial inclusion in a future online conversation). As such, the present technology allows other social network group members to have an opportunity to contribute to the conversation before the conversation appears objectively to have been concluded without the added value of their contribution(s). Distribution of social network posts associated with the social network conversation may be deferred from delivery to the particular social network group member with stronger opinions in accordance with a configured social network conversation dynamic inclusion threshold, while the social network posts are delivered to other social network group members to provide them with an opportunity to contribute where they may not otherwise contribute if a strong opinion had been expressed early in the online conversation.

The social network posts associated with the social network conversation may be delivered to the particular social network group member in response to satisfaction or expiration of the social network conversation dynamic inclusion threshold, at which time the particular social network group member may contribute that user's particular style of commentary without squelching the conversation among the group. This form of dynamic inclusion of the particular social network group member further fosters a recognition among the social network group that the opinions and commentary of that particular social network group member are valued among the group, with the recognition that group members of stronger opinion should still embrace the opportunity to communicate with the group, whether earlier or later in a particular conversation.

An ordering of distribution of social network posts may be controlled within a social network to ensure that a balanced set of responses are available to users that post inquiries or comments within a social network. The present technology evaluates members of an online social network, and response histories of the respective members. Responsive to detection of a new post, the post is intercepted and a distribution list is created for the post in accordance with the members of the social network group. A first intended candidate subset of members of the group on the distribution list is selected in accordance with a configured dynamic inclusion threshold, and the post may be initially distributed to the selected subset of members of the group. The selected subset may be derived based upon members from which historical responses are determined to be lacking due potentially to dominant responses from other members of the group, based upon users being involved primarily with different aspects of a subject matter area within the group, or based upon other criteria as appropriate for a given implementation. The conversation (e.g., set of responses) may be monitored and compared to a dynamic inclusion threshold. When the conversation reaches a target point of diversity of opinion, time, or other factors that are configured for the dynamic inclusion threshold, such as responses appearing from the initial subset of members, the visibility of the post/conversation may be expanded to include more members of the social network group. Over time, other members of the group may be added from the distribution list and the post may be distributed to the added members for comment and/or response until all members have had a chance to view the post and comment and/or respond. As such, the dynamic inclusion thresholds may be altered over time, which allow other people to also be included in the conversation. By time shifting the potential for inclusion of stronger opinions to later in social network conversations, the present technology may provide more incentive to group members that are online less often to contribute to social network conversations.

The mixture of social network group members included in a social network conversation may include members with both positive and negative opinions, different interests, and other diversity of expressions, that are incorporated into the responses in a dynamic and systematic manner over time. The present technology may perform real-time monitoring and text analysis of social network conversations to determine whether differing opinions have been sufficiently expressed by a subset of members to reasonably diversify the particular conversation. The dynamic inclusion thresholds may be adjusted in real time in response to text analytics of the social network conversations. As such, where a particular user has been deferred from initial inclusion in a conversation, that particular user may be added to the conversation in response to analysis of the content of the conversation and the diversity of commentary that has already occurred in the conversation.

This commentary mixture over time allows more passive or neutral participants that may otherwise not participate at all in conversations to observe diversity of opinion (rather than one-sided commentary) that may attract commentary from those participants, and that may further allow those participants to contribute earlier in conversations, while still including participants with stronger opinions (positive or negative, and that would likely participate regardless of timing) to participate later in a conversation. Further, the timing of inclusion of group members may be dynamically adjusted as conversations unfold in a social network environment.

The present technology may leverage streamed post distribution techniques or hide date/time stamps to mask the inclusion thresholds so that all users appear to have a balanced opportunity to present their commentary. As such, the present technology allows social network conversations to be developed with a balanced set of opinions being expressed for consideration by the person that initiated the post, rather than just receiving one-sided responses (again either positive or negative).

The dynamic inclusion thresholds may be based upon a variety of different dynamic inclusion criteria. For example, the dynamic inclusion criteria may include an elapsed amount of time (e.g., a timeout, such as one minute, one hour, one day, etc.). Additional and/or alternative dynamic inclusion criteria may include quality and diversity of opinions expressed within responses, sentiment of responses, attainment of a meta-threshold (e.g., quantity of responses, such as that there have been ten new posts, specific social network group members have joined the conversation, etc.), a number of responses or rate of responses increasing or decreasing (e.g., a detected positive or negative change in a rate of responses), a sentiment threshold (more positive responses than negative responses, etc.), subject matter drift, negativity tolerance criteria, age of posts, thread size, or other threshold, as appropriate for a given implementation. The dynamic inclusion thresholds may be implemented as a combination of the various dynamic inclusion criteria. Further, many different forms of dynamic inclusion criteria are possible and all such possibilities are considered within the scope of the present technology.

The dynamic inclusion thresholds may be configured as dynamic inclusion rules that are evaluated in response to each post or each set of posts to a particular online conversation. The dynamic inclusion rules may be formed based upon, for example, the following criteria: “Include people with interest profiles that match subject X initially, and after 2 hours also include people with interest profiles that match subject Y.” Alternatively, the dynamic inclusion rules may be formed based upon, for example, the following criteria: “Include people that contribute less often initially, and after ten posts have been generated include other group members.” Many other variations of dynamic inclusion rules are possible, and all such variations are considered to be within the scope of the present technology.

The present technology may also apply to any electronic mail client. As such, electronic mail messages may also be processed as otherwise described herein with respect to social network posts.

Several additional aspects of the present technology relating to the inclusion or exclusion thresholds are described below, and each may be implemented as appropriate for a given implementation. For example, a request to repost or share the contents of a post may be detected, and because a reposting or sharing of the content may make the full post available for all to see without use of the technology described herein, the same access rules as utilized during the initial postings may be applied to the new post. The present technology may be activated only on peer review around social/collaborative artifacts. Further, a voting system may be implemented that allows participants to vote on whether to make the post visible to a wider audience, thus by majority (or other threshold vote) those who were previously excluded from the discussion thread may be included by consensus.

The technology described herein may be applied to sets of social network group members by combining multiple users' social network responses and/or commentaries. A system may be implemented to include sentiment metrics between pairs of users in the social network.

It should be noted that additional members may be added from the social network into a conversation randomly. Additionally, a user interface selection may be provided to allow marking of a conversation as complete or ready for full distribution.

A negative or positive perception within subsets of responses may also be identified and displayed. For example, if a social network user is interested in providing a comment on a hotel, the user may selectively see what other reviews have been posted with a similar sentiment of the post the user is interested in providing, which may assist with further enhancing diversity of commentary by allowing the user to augment, rather than repeat, the other postings of similar sentiment.

Further regarding response histories of the respective members, users may be added initially to the distribution list from a top percentage level (e.g., top quartile or other histogram) based upon their historical responses. Users may be added to the distribution of a response over time by adjusting the percentage level of users to be included in the distribution.

Users may additionally be added for distribution over time (e.g., initial distribution versus additional recipients) by use of a statistical confidence level in an expected form of response to a particular initial post. Use of a statistical confidence level may provide progressive access to additional participants over time.

Additionally, a temporary circle, distribution list, or group may be created and used for both initial and subsequent additions to the distribution of a post in a social network conversation. New social network groups may also be created to further distribute posts to other social network members (e.g., other than the core social network group) to elicit more commentary from other social network users or from other social networks. These calculated groups may be stored for reuse. Clustering or grouping of individuals may be achieved by any of the following methods: frequency of communication and “inner circle” sentiment of a prior communication, expertise related to the post, groupings of individual members of the group, personal sentiment related to the topic (e.g., really like or dislike the topic), predictability in response (e.g., predictability of either a positive or negative sentiment in the absence of expertise), prior combinations of responses, clusters of prior responses, likelihood of response, trust metrics, temporal aspects, and features of the message. It should be understood that the subject matter described herein is not limited to the listing above and that other approaches to clustering or grouping are possible and may be utilized as appropriate for the respective implementation.

It should be noted that conception of the present subject matter resulted from recognition of certain limitations associated with social network conversations. For example, it was observed that because social networks allow users to comment essentially at will during all hours of days and nights, social network users often engage in conversations that evolve by a first user that sees a post often being the first user to respond. This tendency was observed to result in a form of “first in, first out” (FIFO) messaging within a social network that, while potentially efficient for messaging mechanics, may lead to dissatisfaction among social network users if certain users are more active and thereby are able more often to comment first. It was observed that because of the social nature of social networks (e.g., a lack of face-to-face feedback of how commentary is actually perceived by other group members), certain social network users may not recognize how their commentary is perceived by other users, and as a result many other users may not express their opinions if more active users are perceived to have squelched a conversation. It was determined that this dynamic nature of social network communications may lead to a lack of participation among certain social network users that also have valuable knowledge or objective and insightful contributions but that hesitate to contribute once strong responses have been entered/posted. It was determined that new technology that addresses this problem may implement a dynamic threshold for inclusion of social network users in social network conversations, by which inclusion of social network users in social network conversations may be dynamically adjusted over time, to allow less active social network users to participate earlier in social network conversations to enhance idea sharing and to avoid one-sided conversations. The present subject matter improves social network conversations and information sharing within social networks by providing for improved social network conversation focus by dynamic alteration of a threshold of inclusion of group members into the social network conversations, as described above and in more detail below. As such, improved social network conversations may be obtained through use of the present technology.

The dynamic inclusion thresholds for social network conversations described herein may be performed in real time to allow prompt threshold-based inclusion of participants to social network conversations. For purposes of the present description, real time shall include any time frame of sufficiently short duration as to provide reasonable response time for information processing acceptable to a user of the subject matter described. Additionally, the term “real time” shall include what is commonly termed “near real time”—generally meaning any time frame of sufficiently short duration as to provide reasonable response time for on-demand information processing acceptable to a user of the subject matter described (e.g., within a portion of a second or within a few seconds). These terms, while difficult to precisely define are well understood by those skilled in the art.

FIG. 1is a block diagram of an example of an implementation of a system100for dynamic inclusion thresholds for social network conversations. A computing device_1102through a computing device_N104communicate via a network106with several other devices. The other devices include a server_1108through a server_M110, and a database112.

As will be described in more detail below in association withFIG. 2throughFIG. 5, the computing device_1102through the computing device_N104and/or the server_1108through the server_M110may each provide automated dynamic inclusion thresholds for social network conversations. The automated dynamic inclusion thresholds for social network conversations is based upon historical and real-time analysis of social network conversations to determine patterns of non-communication by certain group members and to increase diversity of social network conversations based upon this analysis by inclusion of group members that may otherwise not contribute to conversations under certain types of situations. The automated dynamic inclusion thresholds for social network conversations also operates to dynamically include different social network members with different or stronger opinions over time to avoid leaving those social network group members out of conversations. The present technology may be implemented at a user computing device or server device level, or by a combination of such devices as appropriate for a given implementation. A variety of possibilities exist for implementation of the present subject matter, and all such possibilities are considered within the scope of the present subject matter.

The network106may include any form of interconnection suitable for the intended purpose, including a private or public network such as an intranet or the Internet, respectively, direct inter-module interconnection, dial-up, wireless, or any other interconnection mechanism capable of interconnecting the respective devices.

The server_1108through the server_M110may include any device capable of providing data for consumption by a device, such as the computing device_1102through the computing device_N104, via a network, such as the network106. As such, the server_1108through the server_M110may each include a social network server, web server, application server, or other data server device.

The database112may include multiple different databases and may store social network conversation content for use by one or more social networks implemented by the server_1108through the server_M110. The database112may include a relational database, an object database, or any other storage type of device. As such, the database112may be implemented as appropriate for a given implementation.

FIG. 2is a block diagram of an example of an implementation of a core processing module200capable of performing dynamic inclusion thresholds for social network conversations. The core processing module200may be associated with either the computing device_1102through the computing device_N104or with the server_1108through the server_M110, as appropriate for a given implementation. As such, the core processing module200is described generally herein, though it is understood that many variations on implementation of the components within the core processing module200are possible and all such variations are within the scope of the present subject matter.

Further, the core processing module200may provide different and complementary processing of dynamic inclusion thresholds in association with each implementation. As such, for any of the examples below, it is understood that any aspect of functionality described with respect to any one device that is described in conjunction with another device (e.g., sends/sending, etc.) is to be understood to concurrently describe the functionality of the other respective device (e.g., receives/receiving, etc.).

A central processing unit (CPU)202(“processor”) provides hardware that performs computer instruction execution, computation, and other capabilities within the core processing module200. A display204provides visual information to a user of the core processing module200and an input device206provides input capabilities for the user.

The display204may include any display device, such as a cathode ray tube (CRT), liquid crystal display (LCD), light emitting diode (LED), electronic ink displays, projection, touchscreen, or other display element or panel. The input device206may include a computer keyboard, a keypad, a mouse, a pen, a joystick, touchscreen, voice command processing unit, or any other type of input device by which the user may interact with and respond to information on the display204.

It should be noted that the display204and the input device206may be optional components for the core processing module200for certain implementations/devices, or may be located remotely from the respective devices and hosted by another computing device that is in communication with the respective devices. Accordingly, the core processing module200may operate as a completely automated embedded device without direct user configurability or feedback. However, the core processing module200may also provide user feedback and configurability via the display204and the input device206, respectively, as appropriate for a given implementation.

A communication module208provides hardware, protocol stack processing, and interconnection capabilities that allow the core processing module200to communicate with other modules within the system100. The communication module208may include any electrical, protocol, and protocol conversion capabilities useable to provide interconnection capabilities, as appropriate for a given implementation. As such, the communication module208represents a communication device capable of carrying out communications with other devices.

A memory210includes a historical social network conversation patterns storage area212that stores within the core processing module200analytical information and metrics regarding social network conversation dynamics derived over time by analysis of social network conversations. The analytical information and metrics regarding social network conversation dynamics may include response rates (or non-response rates) and other information associated with social network group members under differing conversation circumstances and/or in response to commentary by different members of social network groups. As will be described in more detail below, the analytical information and metrics regarding social network conversation dynamics stored within the historical social network conversation patterns storage area212is used to configure social network conversation dynamic inclusion thresholds to both include more participants in social network conversations and to include participants over time to diversify the content expressed within social network conversations.

The memory210also includes a dynamic inclusion threshold configuration storage area214that stores configured and dynamically updated social network conversation dynamic inclusion thresholds for particular social network groups, conversations, or other granularities as appropriate for a given implementation. As described above and in more detail below, the configured and dynamically updated social network conversation dynamic inclusion thresholds operate to include both persons that may otherwise not contribute to social network conversations and to include other persons that are determined to be highly likely to contribute with stronger commentary over time. As described above, the configured and dynamically updated social network conversation dynamic inclusion thresholds perform a dual role of operating to “include” members of social network groups that may otherwise not contribute to social network conversations, and by also contemporaneously operating to “include” members with particular styles of historical communication patterns to conversations over time. Both forms of inclusion may be dynamically adjusted in real time as social network conversations unfold within a social network. Accordingly, the present technology may facilitate more balanced social network conversations with an increased diversity of participants, commentary, and perspective.

It is understood that the memory210may include any combination of volatile and non-volatile memory suitable for the intended purpose, distributed or localized as appropriate, and may include other memory segments not illustrated within the present example for ease of illustration purposes. For example, the memory210may include a code storage area, an operating system storage area, a code execution area, and a data area without departure from the scope of the present subject matter.

A social network conversation dynamic inclusion threshold module216is also illustrated. The social network conversation dynamic inclusion threshold module216provides historical and real-time social network conversation analysis for the core processing module200, as described above and in more detail below. The social network conversation dynamic inclusion threshold module216implements the automated dynamic inclusion thresholds for social network conversations of the core processing module200.

It should also be noted that the social network conversation dynamic inclusion threshold module216may form a portion of other circuitry described without departure from the scope of the present subject matter. Further, the social network conversation dynamic inclusion threshold module216may alternatively be implemented as an application stored within the memory210. In such an implementation, the social network conversation dynamic inclusion threshold module216may include instructions executed by the CPU202for performing the functionality described herein. The CPU202may execute these instructions to provide the processing capabilities described above and in more detail below for the core processing module200. The social network conversation dynamic inclusion threshold module216may form a portion of an interrupt service routine (ISR), a portion of an operating system, a portion of a browser application, or a portion of a separate application without departure from the scope of the present subject matter.

A timer/clock module218is illustrated and used to determine timing and date information, such as monitoring response timing of posts of social network conversations and satisfaction of time-based dynamic inclusion thresholds, as described above and in more detail below. As such, the social network conversation dynamic inclusion threshold module216may utilize information derived from the timer/clock module218for information processing activities, such as the dynamic inclusion thresholds for social network conversations.

The database112is again shown withinFIG. 2associated with the core processing module200. As such, the database112may be operatively coupled to the core processing module200without use of network connectivity, as appropriate for a given implementation.

The CPU202, the display204, the input device206, the communication module208, the memory210, the social network conversation dynamic inclusion threshold module216, the timer/clock module218, and the database112are interconnected via an interconnection220. The interconnection220may include a system bus, a network, or any other interconnection capable of providing the respective components with suitable interconnection for the respective purpose.

Though the different modules illustrated withinFIG. 2are illustrated as component-level modules for ease of illustration and description purposes, it should be noted that these modules may include any hardware, programmed processor(s), and memory used to carry out the functions of the respective modules as described above and in more detail below. For example, the modules may include additional controller circuitry in the form of application specific integrated circuits (ASICs), processors, antennas, and/or discrete integrated circuits and components for performing communication and electrical control activities associated with the respective modules. Additionally, the modules may include interrupt-level, stack-level, and application-level modules as appropriate. Furthermore, the modules may include any memory components used for storage, execution, and data processing for performing processing activities associated with the respective modules. The modules may also form a portion of other circuitry described or may be combined without departure from the scope of the present subject matter.

Additionally, while the core processing module200is illustrated with and has certain components described, other modules and components may be associated with the core processing module200without departure from the scope of the present subject matter. Additionally, it should be noted that, while the core processing module200is described as a single device for ease of illustration purposes, the components within the core processing module200may be co-located or distributed and interconnected via a network without departure from the scope of the present subject matter. For a distributed arrangement, the display204and the input device206may be located at a point of sale device, kiosk, or other location, while the CPU202and memory210may be located at a local or remote server. Many other possible arrangements for components of the core processing module200are possible and all are considered within the scope of the present subject matter. It should also be understood that, though the database112is illustrated as a separate component for purposes of example, the information stored within the database112may also/alternatively be stored within the memory210without departure from the scope of the present subject matter. Accordingly, the core processing module200may take many forms and may be associated with many platforms.

FIG. 3throughFIG. 5described below represent example processes that may be executed by devices, such as the core processing module200, to perform the automated dynamic inclusion thresholds for social network conversations associated with the present subject matter. Many other variations on the example processes are possible and all are considered within the scope of the present subject matter. The example processes may be performed by modules, such as the social network conversation dynamic inclusion threshold module216and/or executed by the CPU202, associated with such devices. It should be noted that time out procedures and other error control procedures are not illustrated within the example processes described below for ease of illustration purposes. However, it is understood that all such procedures are considered to be within the scope of the present subject matter. Further, the described processes may be combined, sequences of the processing described may be changed, and additional processing may be added or removed without departure from the scope of the present subject matter.

FIG. 3is a flow chart of an example of an implementation of a process300for dynamic inclusion thresholds for social network conversations. The process300represents a computer-implemented method of performing the dynamic inclusion thresholds for social network conversations described herein. At block302, the process300obtains a social network conversation dynamic inclusion threshold that causes a first subset of social network group members of a social network group to be included in a social network conversation earlier than at least one other social network group member and that further causes the at least one other social network group member to be included in the social network conversation responsive to satisfaction of the obtained social network conversation dynamic inclusion threshold. At block304, the process300contemporaneously, in accordance with the obtained social network conversation dynamic inclusion threshold, each of distributes social network posts of the social network conversation to the first subset of social network group members and delays distribution of the social network posts of the social network conversation to the at least one other social network group member. At block306, the process300distributes, in response to satisfaction of the social network conversation dynamic inclusion threshold, the social network posts of the social network conversation to the at least one other social network group member.

FIG. 4is a flow chart of an example of an implementation of a process400for configuration of dynamic inclusion thresholds for social network conversations. The process400represents a computer-implemented method of configuring the dynamic threshold-based inclusion for social network conversations described herein. At decision point402, the process400makes a determination as to whether a request to configure a social network conversation dynamic inclusion threshold has been detected. A request to configure a social network conversation dynamic inclusion threshold may be detected, for example, in response to a user request or otherwise as appropriate for a given implementation and may identify one or more social network groups for which to configure a social network conversation dynamic inclusion threshold. For purposes of the description below, it is presumed that one social network group has been identified for configuration of a social network conversation dynamic inclusion threshold, though additional processing to configure social network conversation dynamic inclusion thresholds for multiple social network groups may be performed by iteration through the appropriate processing steps described below and with any additional steps appropriate for a given implementation.

In response to determining that a request to configure a social network conversation dynamic inclusion threshold has been detected, the process400identifies members of the social network group for which the request to configure a social network conversation dynamic inclusion threshold has been detected at block404. At block406, the process400monitors social network conversations of the identified social network group members. It should be noted that the monitoring of conversations of the identified social network group members may be performed by analysis of previous social network conversations to expedite configuration of the social network conversation dynamic inclusion threshold, or may be performed by monitoring future conversations over time subsequent to the request to configure the social network conversation dynamic inclusion threshold.

At block408, the process400identifies response rates between members. The identification of the response rates between members may be further refined based upon topic, time of day, or other factors as appropriate for a given implementation to allow a determination of changes in response rates based upon opinions expressed during different conversations and other factors usable to configure the social network conversation dynamic inclusion threshold.

At decision point410, the process400makes a determination as to whether one or more lack of responses has been identified. The lack of response(s) may be identified across multiple conversations to determine whether one or more social network group members normally respond to social network conversations, but do not respond under certain identifiable situations/conditions. The respective identifiable situations/conditions that result in the group members not responding may also be identified, including relationships between individual group members and other situations/conditions.

In response to determining at decision point410that one or more lack of responses has not been identified, the process400returns to block406and continues monitoring the social network conversations of the social network group. Alternatively, in response to determining at decision point410that one or more lack of responses has been identified, the process400performs text analysis of posts to the social network conversation(s) with the detected lack of response(s) at block412. As described above, content of social network conversations that prematurely terminate may be suggestive of commentary that causes other group members not to comment or not to continue in a social network conversation. As such, the process400may identify these types of text commentary that result in social network conversations terminating without the intended amount of objective, diverse, and balanced commentary.

At block414, the process400determines a style of response and group member(s) that cause the lack of response(s) by the other group member(s). At block416, the process400configures a social network conversation dynamic inclusion threshold for one or more future social network conversation(s). The configured social network conversation dynamic inclusion threshold may be based upon a topic or subject of conversation(s), time, number of responses/non-responses, responses/non-responses by particular members, and other factors consistent with the present description.

At block418, the process400configures interception and evaluation of posts of future social network conversation(s) among the social network group using the configured social network conversation dynamic inclusion threshold. For purposes of the present description, posts to be intercepted and evaluated may include any form of messages including social network posts, emails, text messages, instant messages (IM), short message service (SMS) messages, blog posts, website posts associated with online social communities, news feeds, and other forms of messages as appropriate for a given implementation. The process400returns to decision point402and iterates as described above.

As such, the process400analyzes social network conversations, identifies situations in which certain group members do not respond where they would otherwise historically respond, and identifies these situations as a lack of response to be evaluated. The process400further performs text analysis of the identified lack of response, determines a style of response that caused the lack of response, and configures and deploys a social network conversation dynamic inclusion threshold.

FIG. 5is a flow chart of an example of an implementation of a process500for performing and dynamically adjusting dynamic inclusion thresholds for social network conversations. The process500represents a computer-implemented method of performing the dynamic threshold-based inclusion for social network conversations described herein. The process500is depicted and described as a per-conversation process, though additional processing to perform processing of multiple contemporaneous conversations (e.g., by multi-threaded operation) may be utilized as appropriate for a given implementation. Additionally, as described above, for purposes of the present description, posts to be intercepted and evaluated include any form of messages including social network posts, emails, text messages, and other forms of messages as appropriate for a given implementation. The post may additionally be considered a first post in a thread or any intermediate post for which a conversation has been configured with one or more social network conversation dynamic inclusion thresholds.

At decision point502, the process500make a determination as to whether a post associated with a social network conversation has been intercepted. In response to determining that a post has been intercepted, the process500makes a determination at decision point504as to whether a social network conversation dynamic inclusion threshold has been configured for the post, such as being configured in association with the social network group member that generated the post or with the social network group associated with the social network group member. In response to determining that a social network conversation dynamic inclusion threshold has not been configured for the post, the process500distributes the post to the social network group with which the post is associated at block506, and the process500returns to decision point502and iterates as described above.

Alternatively, in response to determining at decision point504that a social network conversation dynamic inclusion threshold has been configured for the post, the process500obtains the configured social network conversation dynamic inclusion threshold at block508. At block510, the process500creates a distribution list for the post in accordance with the respective social network group. Creation of the distribution list for the post in accordance with the respective social network group may be performed using options described above for clustering and grouping, or otherwise as appropriate for the given implementation. At block512, the process500identifies an initial distribution subset of social network group members to which the post may initially be distributed from the distribution list. The initial selected distribution subset of social network group members may be derived based upon group members from which historical responses are determined to be lacking (e.g., due potentially to dominant responses from other members of the group, based upon being users involved primarily with different aspects of a subject matter area within the group, etc.). Group members that are not in the initial selected distribution subset may be included in the social network conversation at a later time. As such, the initial selected distribution subset may be selected in accordance with differences in subject matter experience among the social network group members in the initial selected distribution subset of social network group members. Additionally, the initial selected distribution subset may be selected in accordance with similarities in subject matter interest, such as selection of the initial distribution subset according to group members with a first user interest profile that matches a first subject, with inclusion at a later time of users with a second user interest profile that matches a second subject.

At block514, the process500distributes the post to the initial distribution subset of group members on the distribution list. At block516, the process500monitors and analyzes text of additional intercepted posts of the social network conversation and distributes the additional intercepted posts to the initial distribution subset of group members.

At decision point518, the process500makes a determination, based upon the text analysis of the intercepted posts and/or other criteria (e.g., timeouts), as to whether a configured social network conversation dynamic inclusion threshold has been satisfied for the social network conversation. As described above, the configured social network conversation dynamic inclusion threshold may include an amount of time passing since the intercepted post (e.g., a timeout, such as one minute, one hour, one day, etc.), quality and diversity of responses, sentiment of responses, attainment of a meta-threshold (e.g., there have been ten new posts, specific people have joined the conversation, etc.), a number of responses or rate of responses increasing or decreasing, a sentiment threshold (more positive responses than negative responses, etc.), subject matter drift, negativity tolerance criteria, age of posts, thread size, or other threshold, as appropriate for a given implementation.

In response to determining that the configured social network conversation dynamic inclusion threshold has not been satisfied at decision point518, the process500makes a determination at decision point520as to whether to adjust the configured social network conversation dynamic inclusion threshold. Adjustment of the configured social network conversation dynamic inclusion threshold may be performed over time, for example, responsive to determining that the social network conversation dynamic inclusion threshold has not been satisfied in a reasonably timely manner, such as where the social network conversation has become idle prior to any configured timeout within the social network conversation dynamic inclusion threshold or where some other factor is suggestive that the social network conversation dynamic inclusion threshold has been over constrained. As such, adjusting the social network conversation dynamic inclusion threshold operates as a social network post distribution feedback mechanism to adjust distribution of social network posts and may assist with ensuring that intercepted posts get distributed to all group members in a timely manner in circumstances where a particular conversation becomes idle and the social network conversation dynamic inclusion threshold may not be reached or for other reasons as appropriate for a given implementation.

In response to determining not to adjust the configured social network conversation dynamic inclusion threshold at decision point520, the process500returns to block516and continues to monitor and analyze text of additional posts of the social network conversation. Alternatively, in response to determining to adjust the configured social network conversation dynamic inclusion threshold at decision point520, the process500adjusts the social network conversation dynamic inclusion threshold at block522, and returns to block516and continues to monitor and analyze text of additional posts of the social network conversation.

Returning to the description of decision point518, in response to determining that the configured social network conversation dynamic inclusion threshold has been satisfied, the process500distributes the posts of the social network conversation to the remaining one or more social network group members on the distribution list at block524. The process500returns to decision point502and iterates as described above.

As such, the process500operates to intercept either initial or intermediate social network conversation posts, and to identify an initial distribution subset of social network group members for initial inclusion in distribution of the post. The process500distributes the post to the initial distribution subset of group members, and intercepts and monitors over time additional posts posted responsive to the intercepted post. The posts are analyzed for content and distributed to the initial distribution subset of group members. The process500evaluates one or more configured social network conversation dynamic inclusion thresholds, and adjusts the configured thresholds as appropriate for the particular thresholds and subsequent post content. In response to one or more of the configured social network conversation dynamic inclusion thresholds being satisfied, the remaining social network group members on the distribution list are included in the social network conversation and all posts associated with the conversation are distributed to the remaining social network group members.

As described above in association withFIG. 1throughFIG. 5, the example systems and processes provide dynamic inclusion thresholds for social network conversations. Many other variations and additional activities associated with dynamic inclusion thresholds for social network conversations are possible and all are considered within the scope of the present subject matter.

Those skilled in the art will recognize, upon consideration of the above teachings, that certain of the above examples are based upon use of a programmed processor, such as the CPU202. However, the invention is not limited to such example embodiments, since other embodiments could be implemented using hardware component equivalents such as special purpose hardware and/or dedicated processors. Similarly, general purpose computers, microprocessor based computers, micro-controllers, optical computers, analog computers, dedicated processors, application specific circuits and/or dedicated hard wired logic may be used to construct alternative equivalent embodiments.