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Implicit Many-to-one Communication in Online Communities

This is the presentation I made at the Third International Conference on Communities and Technologies held in Michigan State University on June 27 to 30, 2007.

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Implicit Many-to-one Communication in Online Communities

  1. 1. Implicit Many-to-One Communication in Online Communities Mu Xia University of Illinois at Urbana-Champaign (with Wenjing Duan@GWU, Yun Huang and Andy Whinston@UT Austin)
  2. 2. Agenda <ul><li>Growth of online sharing communities </li></ul><ul><li>Definition of Ballot-box Communications </li></ul><ul><li>How BBC differs from CMC </li></ul><ul><li>A case study of BBC </li></ul><ul><li>Challenges in understanding BBC communities </li></ul>
  3. 3. What Do These Sites Have in Common?
  4. 4. What Do These Sites Have in Common? <ul><li>Web 2.0 technologies </li></ul><ul><li>Social computing concepts </li></ul><ul><ul><li>Aggregation of common experience and opinions </li></ul></ul><ul><ul><li>User communication choice is often non-message-based and limited </li></ul></ul>
  5. 5. Aggregation and Simplification <ul><li>Access statistics (YouTube, Last.fm): </li></ul><ul><ul><li>Total views, total comments, number of unique visitors </li></ul></ul><ul><li>Rating/Voting (Digg, Reddit): </li></ul><ul><ul><li>Revealing aggregate user opinions </li></ul></ul><ul><li>Tagging/Folksonomy (Flickr, Del.icio.us): </li></ul><ul><ul><li>Metadata from individuals and published as tag clouds, or search results </li></ul></ul><ul><li>Social Searching (Jookster, Newstrove): </li></ul><ul><ul><li>Recommending the most relevant results based on other people’s searches and feedback </li></ul></ul>
  6. 6. A New Way to Participate <ul><li>Ballot-box Communication: user aggregation mechanism enabled by new technologies </li></ul><ul><li>Before, two extremes of participation: </li></ul><ul><ul><li>Contribute: upload/comment </li></ul></ul><ul><ul><ul><li>“ Play in the game” </li></ul></ul></ul><ul><ul><li>Watch/lurk: no communication </li></ul></ul><ul><ul><ul><li>“ Watch from sidelines” </li></ul></ul></ul><ul><li>Now, you can express your opinion through BBC and the collective preferences can be heard: </li></ul><ul><ul><li>“ Shouting from the stands” </li></ul></ul><ul><li>A special case of Computer-Mediated Collective Action (Marc Smith 2007) </li></ul>
  7. 7. Characteristics of BBC (1) <ul><li>Simplifying web-based communication: </li></ul><ul><ul><li>Users communicate through preconfigured technologies </li></ul></ul><ul><ul><ul><li>Interaction options are limited </li></ul></ul></ul><ul><ul><ul><li>Cost of participation is lower </li></ul></ul></ul><ul><ul><ul><li>The communication is more detached—low communication cost </li></ul></ul></ul><ul><ul><li>The information acquisition cost for the audience is also lower </li></ul></ul><ul><ul><ul><li>No need to go through each posting: aggregation is already done </li></ul></ul></ul><ul><ul><ul><li>“ Voice of the crowd” </li></ul></ul></ul><ul><ul><li>Both the production and consumption of information get easier </li></ul></ul>
  8. 8. Characteristics of BBC (2) <ul><li>Many-to-one communication </li></ul><ul><ul><li>Multiple users’ input is aggregated into a single voice: high level of aggregation </li></ul></ul><ul><ul><ul><li>Compared to blog, email, and IM </li></ul></ul></ul><ul><ul><li>Low level of interaction: </li></ul></ul><ul><ul><ul><li>Compared to online forum, and email </li></ul></ul></ul>
  9. 9. Four Types of Unstructured Communication individual aggregate low high Level of interactivity Many-to-one (Ranking, Voting Tagging, Searching) Many-to-many (Wiki, Online forum, ListServ) One-to-many (Professional review Blog) One-to-one (Email, Instant Messaging)
  10. 10. Characteristics of BBC (3) <ul><li>Implicit influence on users: </li></ul><ul><ul><li>Individual users can be swayed by aggregate trend </li></ul></ul><ul><ul><ul><li>Most viewed, top-rated, expert votes </li></ul></ul></ul><ul><ul><ul><li>User’s own action will heighten the effect: a positive feedback </li></ul></ul></ul>
  11. 11. BBC and CMC <ul><li>BBC offers new benefits over Computer-mediated Communication (CMC): </li></ul><ul><ul><li>By reducing information richness, BBC alleviates information overloading, allowing more participation from more people </li></ul></ul><ul><ul><li>Technology is used to reduce the barrier of participation instead of managing messages </li></ul></ul><ul><ul><li>Influence on users is through actions and is implicit </li></ul></ul>
  12. 12. Traditional Definition of Communities <ul><li>Whittaker et al. (1997): “ intense interactions, strong emotional ties and shared activities” with members having “shared context of social conventions, language, and protocols”. </li></ul><ul><li>Preece (2000): “group of people with a common purpose whose interaction is mediated and supported by technology and governed by formal and informal policies” </li></ul>
  13. 13. Implicit Online Communities <ul><li>BBC – new type of user interaction </li></ul><ul><ul><li>Light weight aggregation </li></ul></ul><ul><li>Implicit individual influence </li></ul><ul><ul><li>Non message-based communication </li></ul></ul><ul><ul><li>Weakened social connections </li></ul></ul><ul><ul><li>Disappearing network structure </li></ul></ul><ul><li>New challenges on social network analysis </li></ul>
  14. 14. BBC in P2P Music Sharing Communities: A Case Study <ul><li>P2P music sharing is the most popular form of online communities </li></ul><ul><li>We use IRC music sharing data to study whether P2P music sharing exhibits BBC characteristics </li></ul><ul><ul><li>Users are identified by a username </li></ul></ul><ul><ul><li>Music is made available by users </li></ul></ul><ul><ul><li>There is very little chatting </li></ul></ul>
  15. 15. Data Description: IRC <ul><li>Internet Relay Chat (IRC) </li></ul><ul><ul><li>Real-time Internet chat protocol </li></ul></ul><ul><ul><li>Users run an IRC client (such as mIRC) to log on and chat </li></ul></ul><ul><ul><li>Topic-oriented channels (chat rooms) </li></ul></ul><ul><ul><li>Some channels are for file sharing (depot channels) </li></ul></ul><ul><li>#mp3passion </li></ul><ul><ul><li>One of the most popular MP3 sharing channels </li></ul></ul>
  16. 16. File Sharing Channels in IRC <ul><li>A user can set up his own file server using a script </li></ul><ul><li>Sharing mechanism is similar to the original Napster model </li></ul><ul><li>Centralized and observable commands: </li></ul><ul><ul><li>All the commands are text-based and are sent to the channel </li></ul></ul><ul><ul><li>Commands: search, browse, download, announcement, etc. </li></ul></ul>
  17. 17. Screen Shot of mIRC
  18. 18. Is this BBC? <ul><li>The first two characteristics are satisfied: </li></ul><ul><ul><li>Sharers cast their “vote” by making certain music available for download, a simplification over recommending music in a review </li></ul></ul><ul><ul><li>Many-to-one: </li></ul></ul><ul><ul><ul><li>A user can “feel” the popularity of a song when searching for it, as the more popular ones would have more return results </li></ul></ul></ul><ul><li>Does implicit influence on users exist? </li></ul>
  19. 19. Analysis of Aggregate Music Preference Change <ul><li>We choose five major music genres: Rock, R&B, Rap, Country, and Jazz </li></ul><ul><li>We find all music by 298 well-known artists and calculate the ratio of songs in each genre over all songs identified </li></ul><ul><li>We aggregate all demand (download) and supply (files made available). </li></ul>
  20. 20. Yearly Ratios of Sharing and Downloading Volumes (By Genre)
  21. 21. Analysis of Individual Music Preference Change <ul><li>A case study of one individual user, “John Doe”, during a five-week period in 2006 </li></ul>11 22 (0) 47 (10) 6 (1) 5 84 32 (79) 61 (163) 10 (9) 4 28 33 (14) 45 (62) 5 (0) 3 162 47 (94) 91 (224) 18 (16) 2 165 55 (100) 119 (246) 28 (26) 1 Files kept Browses of Sharer A (Downloads) Browses (Downloads) Searches (Downloads) Week
  22. 22. Three Pieces of Evidence of BBC <ul><li>Browse commands lead to most of the downloads: implicit influence of users </li></ul><ul><li>Users “endorse” the content by keeping and sharing files (implicit voting by John Doe himself) </li></ul><ul><li>Small set of sharers to download from </li></ul><ul><ul><li>Again, implicit influence of small set of users: 30% from Sharer A </li></ul></ul>
  23. 24. Building BBC-Enabled Communities <ul><li>Sustainability is a challenge for Web 2.0 companies: </li></ul><ul><ul><li>Interaction between users is implicit, therefore the collective behavior is hard to predict </li></ul></ul><ul><ul><li>Individual interactions, as simplifications of real complex user opinions, provide a poor base for prediction </li></ul></ul><ul><ul><li>Low cost of participation creates large degree of randomness </li></ul></ul>
  24. 25. Challenges in Understanding BBC <ul><li>The level of impact of user actions on other users is unclear </li></ul><ul><li>BBC’s influence may also be a function of the ever-evolving technologies, in addition to users and the community </li></ul><ul><li>Many BBC communities are for-profit, with the operators having a lot of power </li></ul><ul><li>A lot of new questions need to be answered </li></ul>
  25. 26. Our Related Research <ul><li>Empirical analysis of user actions </li></ul><ul><li>Factors that drive user action in implicit communities </li></ul><ul><li>Social network analysis of implicit relationships and their evolution </li></ul>

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