Increasing Activity in Enterprise Online Communities Using Content Recommendation

Although online communities have become popular both on the web and within enterprises, many of them often experience low levels of activity and engagement from their members. Previous studies identified the important role of community leaders in maintaining the health and vitality of their communities. One of their key means for doing so is by contributing relevant content to the community. In this paper, we study the effects of recommending social media content on enterprise community leaders. We conducted a large-scale user survey with four recommendation rounds, in which community leaders indicated their willingness to share social media items with their communities. They also had the option to instantly share these items. Recommendations were generated based on seven types of community interest profiles that were member-based, content-based, or hybrid. Our results attest that providing content recommendations to leaders can help uplift activity within their communities.

[1]  Werner Geyer,et al.  Lessons learned from blog muse: audience-based inspiration for bloggers , 2010, CHI.

[2]  John Riedl,et al.  SuggestBot: using intelligent task routing to help people find work in wikipedia , 2007, IUI '07.

[3]  John Riedl,et al.  PolyLens: A recommender system for groups of user , 2001, ECSCW.

[4]  Amy Jo Kim,et al.  Community Building on the Web: Secret Strategies for Successful Online Communities , 2000 .

[5]  Ido Guy,et al.  Recommending social media content to community owners , 2014, SIGIR.

[6]  Sean M. McNee,et al.  Being accurate is not enough: how accuracy metrics have hurt recommender systems , 2006, CHI Extended Abstracts.

[7]  Bette Gray Informal Learning in an Online Community of Practice. , 2004 .

[8]  P. Resnick,et al.  Building Successful Online Communities: Evidence-Based Social Design , 2012 .

[9]  Shamsuddin Ahmed,et al.  Virtual R&D teams in small and medium enterprises: a literature review , 2009 .

[10]  Line Dubé,et al.  The Success of Virtual Communities of Practice : The Leadership Factor , 2005 .

[11]  S. Kiesler,et al.  Community Effort in Online Groups: Who Does the Work and Why? , 2007 .

[12]  Ido Guy,et al.  Games for Crowds: A Crowdsourcing Game Platform for the Enterprise , 2015, CSCW.

[13]  Anthony Jameson,et al.  More than the sum of its members: challenges for group recommender systems , 2004, AVI.

[14]  Tara Matthews,et al.  Beyond end user content to collaborative knowledge mapping: interrelations among community social tools , 2014, CSCW.

[15]  Ido Guy,et al.  Folksonomy-based term extraction for word cloud generation , 2011, CIKM 2011.

[16]  Brian S. Butler,et al.  Research Note - The Impact of Community Commitment on Participation in Online Communities , 2011, Inf. Syst. Res..

[17]  Ido Guy,et al.  Visual social network analytics for relationship discovery in the enterprise , 2011, 2011 IEEE Conference on Visual Analytics Science and Technology (VAST).

[18]  Ido Guy,et al.  What is Your Organization 'Like'?: A Study of Liking Activity in the Enterprise , 2016, CHI.

[19]  Joon Koh,et al.  Encouraging participation in virtual communities , 2007, CACM.

[20]  Ido Guy,et al.  Social networks and discovery in the enterprise (SaND) , 2009, SIGIR.

[21]  Douglas B. Terry,et al.  Using collaborative filtering to weave an information tapestry , 1992, CACM.

[22]  Michail N. Giannakos,et al.  Using social media for work: Losing your time or improving your work? , 2014, Comput. Hum. Behav..

[23]  Otis Gospodnetic,et al.  Lucene in Action, Second Edition: Covers Apache Lucene 3.0 , 2010 .

[24]  David Carmel,et al.  Social media recommendation based on people and tags , 2010, SIGIR.

[25]  Judith Masthoff,et al.  Group Modeling: Selecting a Sequence of Television Items to Suit a Group of Viewers , 2004, User Modeling and User-Adapted Interaction.

[26]  Robert E. Kraut,et al.  Encouraging contribution to online communities , 2008 .

[27]  Ritu Agarwal,et al.  Through a Glass Darkly: Information Technology Design, Identity Verification, and Knowledge Contribution in Online Communities , 2007, Inf. Syst. Res..

[28]  Jan Marco Leimeister,et al.  Success factors of virtual communities from the perspective of members and operators: an empirical study , 2004, 37th Annual Hawaii International Conference on System Sciences, 2004. Proceedings of the.

[29]  Christopher D. Manning,et al.  Introduction to Information Retrieval , 2010, J. Assoc. Inf. Sci. Technol..

[30]  William Snyder,et al.  Cultivating Communities of Practice: A Guide to Managing Knowledge , 2002 .

[31]  Marguerite Cronk,et al.  Using Gamification to Increase Student Engagement and Participation in Class Discussion , 2012 .

[32]  Sunanda Sangwan,et al.  Virtual Community Success: A Uses and Gratifications Perspective , 2005, Proceedings of the 38th Annual Hawaii International Conference on System Sciences.

[33]  J. Preece,et al.  Online communities: focusing on sociability and usability , 2002 .

[34]  Tara Matthews,et al.  CommunityCompare: visually comparing communities for online community leaders in the enterprise , 2013, CHI.

[35]  K. Gegenfurtner,et al.  Design Issues in Gaze Guidance Under review with ACM Transactions on Computer Human Interaction , 2009 .

[36]  Rosta Farzan,et al.  Results from deploying a participation incentive mechanism within the enterprise , 2008, CHI.

[37]  Dan Cosley,et al.  Think different: increasing online community participation using uniqueness and group dissimilarity , 2004, CHI.

[38]  Ido Guy,et al.  Increasing engagement through early recommender intervention , 2009, RecSys '09.

[39]  Haiyi Zhu,et al.  Goals and perceived success of online enterprise communities: what is important to leaders & members? , 2014, CHI.

[40]  Julita Vassileva,et al.  Social Visualization Encouraging Participation in Online Communities , 2006, CRIWG.

[41]  Shlomo Berkovsky,et al.  Group-based recipe recommendations: analysis of data aggregation strategies , 2010, RecSys '10.

[42]  Kate Ehrlich,et al.  Community insights: helping community leaders enhance the value of enterprise online communities , 2013, CHI.

[43]  John Kim,et al.  What makes users rate (share, tag, edit...)?: predicting patterns of participation in online communities , 2012, CSCW.

[44]  Kate Ehrlich,et al.  Diversity among enterprise online communities: collaborating, teaming, and innovating through social media , 2012, CHI.

[45]  Jennifer Preece,et al.  The top five reasons for lurking: improving community experiences for everyone , 2004, Comput. Hum. Behav..

[46]  David R. Millen,et al.  Dogear: Social bookmarking in the enterprise , 2006, CHI.

[47]  David M. Pennock,et al.  Categories and Subject Descriptors , 2001 .

[48]  L. Brown,et al.  Interval Estimation for a Binomial Proportion , 2001 .

[49]  Eric S. K. Yu,et al.  Modeling social media support for the elicitation of citizen opinion , 2010, MSM '10.

[50]  Michael J. Muller,et al.  Understanding the benefit and costs of communities of practice , 2002, CACM.

[51]  Robin D. Burke,et al.  Hybrid Recommender Systems: Survey and Experiments , 2002, User Modeling and User-Adapted Interaction.

[52]  David A. Huffaker,et al.  Dimensions of leadership and social influence in online communities , 2010 .

[53]  Michael J. Pazzani,et al.  Content-Based Recommendation Systems , 2007, The Adaptive Web.

[54]  Ido Guy,et al.  Swimming against the streamz: search and analytics over the enterprise activity stream , 2012, CIKM.

[55]  Kate Ehrlich,et al.  What motivates members to contribute to enterprise online communities? , 2014, CSCW Companion '14.

[56]  Haiyi Zhu,et al.  Selecting an effective niche: an ecological view of the success of online communities , 2014, CHI.