Skip to main content
SpringerLink
Log in

Towards Evolutionary Named Group Recommendations

  • Published:
Computer Supported Cooperative Work (CSCW) Aims and scope Submit manuscript

Abstract

When sharing information, a common tactic for reducing the cost of choosing recipients is to form named groups of users. These groups are then selected as recipients in lieu of or in addition to users. However, keeping named groups up to date is a difficult and error-prone task when conducted manually. Past schemes automating this task make different tradeoffs and can be distinguished based on several factors including the types of named groups they consider, whether they evolve a specific group or a set of multiple groups, and how integrated they are with techniques for predicting initial groups. We analyze these approaches and identify a design space of potential evolutionary approaches. Using this analysis, we introduce a novel approach for automatically suggesting a sub-type of evolution, evolutionary growth. This approach (a) requires no prior knowledge of which groups change, (b) composes, and therefore interoperates, with an existing engine for recommending named groups, and (c) extracts groups from the social graph of multiple types of applications regardless of whether the graph are explicit or derived implicitly from message communication. Our evaluation considers social graphs created using explicit and implicit connections, and identifies the conditions under which the approach outperforms baseline techniques.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
Figure 8
Figure 9
Figure 10

Similar content being viewed by others

References

  • 20 Newsgroups. (n.d.). http://kdd.ics.edu/databases/20newsgroups/20newsgroups.html

  • Amershi, Saleema; James Fogarty; and Daniel S. Weld. (2012). ReGroup: Interactive machine learning for on-demand group creation in social networks. In CHI ‘12. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. New York, NY, USA: ACM, pp. 21–30.

  • Backstrom, Lars; Dan Huttenlocher; Jon Kleinberg; and Xiangyang Lan. (2006). Group formation in large social networks: Membership, growth, and evolution. In KDD ‘06. Proceedings of the 12th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. New York, NY, USA: ACM, pp. 44–54.

  • Bacon, Kelli; and Prasun Dewan. (2011). Mixed-initiative friend-list creation. In ECSCW 2011: Proceedings of the 12th European conference on computer supported cooperative work, 24–28 September 2011, Aarhus Denmark. London: Springer, pp. 293–312.

  • Banerjee, Jay, Won Kim, Hyoung-Joo Kim, Henry F. Korth, (1987) Semantics and implementation of schema evolution in object-oriented databases.  In SIGMOD ’87. Proceedings of the 1987 ACM SIGMOD International Conference on Management of Data. New York, NY, USA: ACM, pp. 311–322.

  • Barabási, Albert-László; and Réka Albert. (1999). Emergence of scaling in random networks. Science, vol. 286, 1999, pp. 509–512.

  • Bartel, Jacob; and Prasun Dewan. (2012). Towards hierarchical email recipient prediction. In 8th International Conference on Collaborative Computing: Networking, Applications and Worksharing (CollaborateCom). Pittsburgh, PA: IEEE, pp. 50–59.

  • Bartel, Jacob W.; and Prasun Dewan. (2013). Evolving friend lists in social networks. In RecSys ‘13. Proceedings of the 7th ACM Conference on Recommender Systems. New York, NY, USA: ACM, pp. 435–438.

  • Burke, Moira; Robert Kraut; and Cameron Marlow. (2011). Social capital on Facebook: Differentiating uses and users. In CHI ‘11. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. New York, NY, USA: ACM, pp. 571–580.

  • Card, Stuart K.; Thomas P. Moran; and Allen Newell. (1980). The keystroke-level model for user performance time with interactive systems. Commun. ACM, vol. 23, no. 7, July 1980, pp. 396–410.

  • Carvalho, Vitor R.; and William W. Cohen. (2008). Ranking Users for Intelligent Message Addressing. In Lecture Notes in Computer Science. Advances in Information Retrieval. Presented at the European conference on information retrieval, springer, berlin, Heidelberg, pp. 321–333.

  • Daly, Elizabeth M.; Dominik Dahlem; and Daniele Quercia. (2014). The new blocs on the block: Using community forums to Foster new Neighbourhoods. In WebSci ‘14. Proceedings of the 2014 ACM Conference on Web Science. New York, NY, USA: ACM, pp. 52–61.

  • Dowell, L. Jonathan; and Michael Lee Bruno. (2001). Connectivity of Random Graphs and Mobile Networks: Validation of Monte Carlo Simulation Results. In SAC ’01. Proceedings of the 2001 ACM Symposium on Applied Computing. New York, NY, USA: ACM, pp. 77–81.

  • Elliott, W. David; Warren A. Potas; and Andries van Dam. (1971). Computer Assisted Tracing of Text Evolution. In AFIPS ’71 (Fall). Proceedings of the November 16-18, 1971, Fall Joint Computer Conference. New York, NY, USA: ACM, pp. 533–540.

  • Fisher, Danyel; and Paul Dourish. (2004). Social and temporal structures in everyday collaboration. In CHI ‘04. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. New York, NY, USA: ACM, pp. 551–558.

  • Friggeri, Adrien; Guillaume Chelius; and Eric Fleury. (2011). Triangles to capture social cohesion. In 2011 I.E. Third International Conference on Privacy, Security, Risk and Trust and 2011 I.E. Third International Conference on Social Computing. Boston, MA: IEEE, pp. 258–265.

  • Han, Jiawei; and Micheline Kamber. (2011). Data Mining: Concepts and Techniques. Elsevier.

  • Hannon, John; Mike Bennett; and Barry Smyth. (2010). Recommending twitter users to follow using content and collaborative filtering approaches. In RecSys ‘10. Proceedings of the Fourth ACM Conference on Recommender Systems. New York, NY, USA: ACM, pp. 199–206.

  • Kalman, Yoram M.; Lauren E. Scissors; Alastair J. Gill; and Darren Gergle. (2013). Online chronemics convey social information. Computers in Human Behavior, vol. 29, no. 3, May 2013, pp. 1260–1269.

  • Lampson, Butler W. (1974). Protection. SIGOPS Oper. Syst. Rev., vol. 8, no. 1, January 1974, pp. 18–24.

  • Levenshtein, V. I. (1966). Binary Codes Capable of Correcting Deletions, Insertions and Reversals. Soviet Physics Doklady, vol. 10, February 1966, pp. 707.

  • Liben-Nowell, David; Jasmine Novak; Ravi Kumar; Prabhakar Raghavan; and Andrew Tomkins. (2005). Geographic routing in social networks. Proceedings of the National Academy of Sciences, vol. 102, no. 33, August 2005, pp. 11623–11628.

  • MacLean, Diana; Sudheendra Hangal; Seng Keat Teh; Monica S. Lam; and Jeffrey Heer. (2011). Groups without tears: Mining social topologies from email. In IUI ‘11. Proceedings of the 16th International Conference on Intelligent User Interfaces. New York, NY, USA: ACM, pp. 83–92.

  • McAuley, Julian; and Jure Leskovec. (2012). Learning to discover social circles in Ego networks. In NIPS’12. Proceedings of the 25th International Conference on Neural Information Processing Systems - Volume 1. USA: Curran associates Inc., pp. 539–547.

  • Miller, George A. (1956). The magical number seven, plus or minus two: Some limits on our capacity for processing information. Psychological Review, vol. 63, no. 2, 1956, pp. 81–97.

  • Molloy, Tim. (2011, November 14). Michele Bachmann Rips CBS After E-Mail Gaffe Exposes Debate Slight. Reuters. Accessed 26 September 2013

  • Newman, Mark EJ. (2008). The mathematics of networks. The New Palgrave Encyclopedia of Economics, 2008.

  • Newman, Mark W.; Debra Lauterbach; Sean A. Munson; Paul Resnick; and Margaret E. Morris. (2011). “It’s not that I don’t have problems, I’m just not putting them on Facebook”: Challenges and opportunities in using online social networks for health. In CSCW ‘11. Proceedings of the ACM 2011 Conference on Computer Supported Cooperative Work. New York, NY, USA: ACM, pp. 341–350.

  • Pal, Aditya; F. Maxwell Harper; and Joseph A. Konstan. (2012). Exploring Question Selection Bias to Identify Experts and Potential Experts in Community Question Answering. ACM Transactions on Information Systems, vol. 30, no. 2, May 2012, pp. 10:1–10:28.

  • Palla, Gergely; Imre Der’enyi; Ille’s Farkas; and Tama’s Vicsek. (2005). Uncovering the overlapping community structure of complex networks in nature and society. Nature, vol. 435, 2005, pp. 814–818.

  • Peña, Jorge; and Nicholas Brody. (2014). Intentions to hide and unfriend Facebook connections based on perceptions of sender attractiveness and status updates. Computers in Human Behavior, vol. 31, February 2014, pp. 143–150.

  • Reeder, Robert W.; Lujo Bauer; Lorrie Faith Cranor; Michael K. Reiter; Kelli Bacon; Keisha How; and Heather Strong. (2008). Expandable grids for visualizing and authoring computer security policies. In CHI ‘08. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. New York, NY, USA: ACM, pp. 1473–1482.

  • Roth, Maayan; Assaf Ben-David; David Deutscher; Guy Flysher; Ilan Horn; Ari Leichtberg; et al. (2010). Suggesting friends using the implicit social graph. In KDD ‘10. Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. New York, NY, USA: ACM, pp. 233–242.

  • Scholz, Christoph; Martin Atzmueller; and Gerd Stumme. (2012). On the Predictability of Human Contacts: Influence Factors and the Strength of Stronger Ties. In SOCIALCOM-PASSAT ’12. Proceedings of the 2012 ASE/IEEE International Conference on Social Computing and 2012 ASE/IEEE International Conference on Privacy, Security, Risk and Trust. Washington, DC, USA: IEEE Computer Society, pp. 312–321

  • Shen, HongHai; and Prasun Dewan. (1992). Access control for collaborative environments. In CSCW ‘92. Proceedings of the 1992 ACM Conference on Computer-supported Cooperative Work. New York, NY, USA: ACM, pp. 51–58.

  • Soghoian, Chris. (2008, January 23). Exclusive: The next Facebook privacy scandal. CNET. http://news.cnet.com/8301-13739_3-9854409-46.html. Accessed 14 November 2013

  • Stack Exchange Data Dump. (2012, August). ClearBits. http://www.clearbits.net/creators/146-stack-exchange-data-dump

  • Tichy, Walter F. (1985). RCS—a System for Version Control. Software—Practice & Experience, vol. 15, no. 7, July 1985, pp. 637–654.

  • Vaidya, Jaideep; Vijayalakshmi Atluri; Qi Guo; and Nabil Adam. (2008). Migrating to optimal RBAC with minimal perturbation. In SACMAT ‘08. Proceedings of the 13th ACM Symposium on Access Control Models and Technologies. New York, NY, USA: ACM, pp. 11–20.

  • Wang, Dashun; Dino Pedreschi; Chaoming Song; Fosca Giannotti; and Albert-Laszlo Barabasi. (2011). Human Mobility, Social Ties, and Link Prediction. In KDD ’11. Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. New York, NY, USA: ACM, pp. 1100–1108.

Download references

Author information

Authors and Affiliations

  1. University of North Carolina at Chapel Hill, Chapel Hill, USA

    Jacob W. Bartel & Prasun Dewan

Authors
  1. Jacob W. Bartel
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Prasun Dewan
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jacob W. Bartel.

Additional information

Jacob W. Bartel is now at Google, Inc.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Bartel, J.W., Dewan, P. Towards Evolutionary Named Group Recommendations. Comput Supported Coop Work 27, 983–1018 (2018). https://doi.org/10.1007/s10606-018-9321-5

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10606-018-9321-5

Keywords

Search

Navigation