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http://dx.doi.org/10.3745/JIPS.04.0014

Personalizing Information Using Users' Online Social Networks: A Case Study of CiteULike  

Lee, Danielle (Computing and Software Systems Program, University of Washington)
Publication Information
Journal of Information Processing Systems / v.11, no.1, 2015 , pp. 1-21 More about this Journal
Abstract
This paper aims to assess the feasibility of a new and less-focused type of online sociability (the watching network) as a useful information source for personalized recommendations. In this paper, we recommend scientific articles of interests by using the shared interests between target users and their watching connections. Our recommendations are based on one typical social bookmarking system, CiteULike. The watching network-based recommendations, which use a much smaller size of user data, produces suggestions that are as good as the conventional Collaborative Filtering technique. The results demonstrate that the watching network is a useful information source and a feasible foundation for information personalization. Furthermore, the watching network is substitutable for anonymous peers of the Collaborative Filtering recommendations. This study shows the expandability of social network-based recommendations to the new type of online social networks.
Keywords
CiteULike; Homophily; Information Personalization; Online Social Networks; Social Network-based Recommendations;
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1 P. Bonhard, M. A. Sasse, and C. Harries, "The devil you know knows best: how online recommendations can benefit from social networking," in Proceedings of the 21st British HCI Group Annual Conference on People and Computers: HCI... but not as we know it (BCS HCI 2007), University of Lancaster, UK, 2007, pp. 77-86.
2 S. Bourke, K. McCarthy, and B. Smyth, "Power to the people: exploring neighbourhood formations in social recommender system," in Proceedings of the 5th ACM Conference on Recommender Systems, Chicago, IL, 2011, pp. 337-340.
3 M. S. Pera and Y. K. Ng, "With a little help from my friends: generating personalized book recommendations using data extracted from a social website," in Proceedings of the 2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology, Lyon, France, 2011, pp. 96-99.
4 R. R. Sinha and K. Swearingen, "Comparing recommendations made by online systems and friends," in Proceedings of DELOS Workshop: Personalisation and Recommender Systems in Digital Libraries, Dublin, Ireland, 2001.
5 I. Konstas, V. Stathopoulos, and J. M. Jose, "On social networks and collaborative recommendation," in Proceedings of the 32nd International ACM SIGIR Conference on Research and Development in Information Retrieval, Boston, MA, 2009, pp. 195-202.
6 G. Groh and C. Ehmig, "Recommendations in taste related domains: collaborative filtering vs. social filtering," in Proceedings of the 2007 International ACM Conference on Supporting Group Work, Sanibel Island, FL, 2007, pp. 127-136.
7 F. Liu and H. J. Lee, "Use of social network information to enhance collaborative filtering performance," Expert Systems with Applications, vol. 37, no. 7, pp. 4772-4778, 2010.   DOI   ScienceOn
8 Q. Yuan, L. Chen, and S. Zhao, S. "Factorization vs. regularization: fusing heterogeneous social relationships in top-n recommendation," in Proceedings of the 5th ACM Conference on Recommender Systems, Chicago, IL, 2011, pp. 245-252.
9 J. Brown, A. J. Broderick, and N. Lee, "Word of mouth communication within online communities: conceptualizing the online social network," Journal of Interactive Marketing, vol. 21, no. 3, pp. 2-20, 2007.   DOI
10 M. Jandel and M. Elahi, "Tribal taste: mobile multiagent recommender system," in Proceedings of the 14th International Conference on Intelligent User Interfaces, Sanibel Island, FL, 2009, pp. 489-490.
11 J. Preece and D. Maloney-Krichmar, "Online communities: focusing on sociability and usability," in The Human-Computer Interaction Handbook. Mahwah, NJ: Lawrence Erlbaum Associate, 2003, pp. 596-620.
12 B. Wellman, "Computer networks as social networks," Science, vol. 293, no. 5537, pp. 2031-2034, 2001.   DOI   ScienceOn
13 D. Lee, "How to measure the information similarity in unilateral relations: the case study of Delicious," in Proceedings of the International Workshop on Modeling Social Media, Toronto, Canada, 2010.
14 D. H. Lee and P. Brusilovsky, "Does trust influence information similarity?" in Proceedings of the ACM RecSys Workshop on Recommender Systems & the Social Web, New York, NY, 2009, pp. 71-74.
15 D. H. Lee and P. Brusilovsky, "Social networks and interest similarity: the case of CiteULike," in Proceedings of the 21st ACM Conference on Hypertext and Hypermedia, Toronto, Canada, 2010, pp. 151-156.
16 P. R. Monge and N. S. Contractor, "Homophily, proximity, and social support theories," in Theories of Communication Networks. Oxford: Oxford University Press, 2003, pp. 223-239.
17 A. Java, X. Song, T. Finin, and B. Tseng, "Why we twitter: understanding microblogging usage and communities," in Proceedings of the 9th WebKDD and 1st SNA-KDD 2007 Workshop on Web Mining and Social Network Analysis, San Jose, CA, 2007, pp. 56-65.
18 P. R. Monge and N. S. Contractor, "Network concepts, measures, and the multitheoretical, multilevel analytic framework," in Theories of Communication Networks. Oxford: Oxford University Press, 2003, pp. 29-77.
19 J. Breslin, "Social semantic information spaces," in Semantic Digital Libraries, S. R. Kruk and B. McDaniel, Eds., Heldelberg: Springer, 2009, pp. 55-68.
20 J. Breslin and S. Decker, "The future of social networks on the internet: the need for semantics," IEEE Internet Computing, vol. 11, no. 6, pp. 86-90, 2007.   DOI
21 X. Lin, J. E. Beaudoin, Y. Bui, and K. Desai, "Exploring characteristics of social classification," in Proceedings of the 17th Annual ASIS&T SIG/CR Classification Research Workshop, Austin, TX, 2006, pp. 1-19.
22 Y. Koren, R. Bell, and C. Volinsky, "Matrix factorization techniques for recommender systems," Computer, vol. 42, no. 8, pp. 30-37, 2009.   DOI
23 X. Zhou, Y. Xu, Y. Li, A. Josang, and C. Cox, "The state-of-the-art in personalized recommender systems for social networking," Artificial Intelligence Review, vol. 37, no. 2, pp. 119-132, 2012.   DOI
24 D. Kalman, "A singularly valuable decomposition: the SVD of a matrix," The College Mathematics Journal, vol. 27, no. 1, pp. 2-23, 1996.   DOI   ScienceOn
25 D. H. Lee and P. Brusilovsky, "Social networks and interest similarity: the case of CiteULike," in Proceedings of the 21st ACM Conference on Hypertext and Hypermedia, Toronto, Canada, 2010, pp. 151-156.
26 R. Burke, "Hybrid web recommender systems," in The Adaptive Web. Heidelberg: Springer, 2007, pp. 377-408.
27 M. Brand, "Fast low-rank modifications of the thin singular value decomposition," Linear Algebra and Its Applications, vol. 415, no. 1, pp. 20-30, 2006.   DOI   ScienceOn
28 B. Sarwar, G. Karypis, J. Konstan, and J. Riedl, "Incremental singular value decomposition algorithms for highly scalable recommender systems," in Proceedings of the 5th International Conference on Computer and Information Technology, 2002.
29 S. Zhang, W. Wang, J. Ford, F. Makedon, and J. Pearlman, "Using singular value decomposition approximation for collaborative filtering," in Proceedings of the 7th IEEE International Conference on E-Commerce Technology (CEC), Munich, Germany, 2005, pp. 257-264.
30 C. Au Yeung and T. Iwata, "Capturing implicit user influence in online social sharing," in Proceedings of the 21st ACM Conference on Hypertext and Hypermedia, Toronto, Canada, 2010, pp. 245-254.
31 G. Salton, A. Wong, and C. S. Yang, "A vector space model for automatic indexing," Communications of the ACM, vol. 18, no. 11, pp. 613-620, 1975.   DOI   ScienceOn
32 B. Liu, "Informational retrieval and web search," in Web Data Mining: Exploring Hyperlinks, Contents, and Usage Data. Heidelberg: Springer, 2007, pp. 183-236.
33 P. Lops, M. De Gemmis, and G. Semeraro, "Content-based recommender systems: state of the art and trends," in Recommender Systems Handbook. New York: Springer, 2011, pp. 73-105.
34 D. Jannach, M. Zanker, A. Felfernig, and G. Friedrich, Recommender Systems: An Introduction. New York: Cambridge University Press, 2011.
35 R. B. Cialdini and N. J. Goldstein, "Social influence: compliance and conformity," Annual Review of Psychology, vol. 55, pp. 591-621, 2004.   DOI   ScienceOn
36 J. Mori, T. Tsujishita, Y. Matsuo, and M. Ishizuka, "Extracting relations in social networks from the web using similarity between collective contexts," in Proceedings of the 5th International Semantic Web Conference (ISWC), Athens, GA, 2006, pp. 487-500.
37 J. Golbeck, "Introduction to computing with social trust," in Computing with Social Trust. London: Springer, 2009, pp. 1-5.
38 J. B. Schafer, D. Frankowski, J. Herlocker, and S. Sen, "Collaborative filtering recommender systems," in The Adaptive Web. Heidelberg: Springer, 2007, pp. 291-324.
39 A. Anagnostopoulos, R. Kumar, and M. Mahdian, "Influence and correlation in social networks," in Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Las Vegas, NV, 2008, pp. 7-15.
40 E. Bakshy, B. Karrer, and L. A. Adamic, "Social influence and the diffusion of user-created content," in Proceedings of the 10th ACM Conference on Electronic Commerce, Stanford, CA, 2009, pp. 325-334.
41 K. Carley, "A theory of group stability," American Sociological Review, vol. 56, no. 3, pp. 331-354, 1991.   DOI   ScienceOn
42 S. R. Marks, "Intimacy in the public realm: the case of co-workers," Social Forces, vol. 72, no. 3, pp. 843-858, 1994.   DOI
43 J. C. Turner and K. J. Reynolds, "Self-categorization theory," in The Handbook of Theories in Social Psychology (Volume 2). Los Angeles, CA: SAGE Publications, 2012, pp. 399-417.
44 S. K. Lam and J. Riedl, "Shilling recommender systems for fun and profit," in Proceedings of the 13th International Conference on World Wide Web, New York, NY, 2004 pp. 393-402.
45 G. Adomavicius and A. Tuzhilin, "Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions," IEEE Transactions on Knowledge and Data Engineering, vol. 17, no. 6, pp. 734-749, 2005.   DOI   ScienceOn
46 P. Massa and P. Avesani, "Trust-aware recommender systems," in Proceedings of the 2007 ACM Conference on Recommender Systems, Minneapolis, MN, 2007, pp. 17-24.
47 B. Mehta, T. Hofmann, and W. Nejdl, "Robust collaborative filtering," in Proceedings of the 2007 ACM Conference on Recommender Systems, Minneapolis, MN, 2007 pp. 49-56.
48 J. O'Donovan and B. Smyth, "Trust in recommender systems," in Proceedings of the 10th International Conference on Intelligent User Interfaces, San Diego, CA, 2005, pp. 167-174.
49 P. Melville, R. J. Mooney, and R. Nagarajan, "Content-boosted collaborative filtering for improved recommendations," in Proceedings of the 8th National Conference on Artificial Intelligence (AAAI-02), Edmonton, Canada, 2002, pp. 187-192.
50 P. Massa and P. Avesani, "Trust-aware collaborative filtering for recommender systems," in On the Move to Meaningful Internet Systems 2004: CoopIS, DOA, and ODBASE. Heidelberg: Springer, 2004, pp. 492-508.
51 P. Bonhard and M. A. Sasse, "Knowing me, knowing you-using profiles and social networking to improve recommender systems," BT Technology Journal, vol. 24, no. 3, pp. 84-98, 2006.   DOI
52 I. Guy, N. Zwerdling, D. Carmel, I. Ronen, E. Uziel, S. Yogev, and S. Ofek-Koifman, "Personalized recommendation of social software items based on social relations," in Proceedings of the 3rd ACM Conference on Recommender Systems, New York, NY, 2009, pp. 53-60.
53 P. Avesani, P. Massa, and R. Tiella, "A trust-enhanced recommender system application: Moleskiing," in Proceedings of the 2005 ACM Symposium on Applied Computing, Santa Fe, NM, 2005, pp. 1589-1593.
54 D. H. Lee and P. Brusilovsky, "Improving recommendations using Watching Networks in a social tagging system," in Proceedings of the 2011 iConference, Seattle, WA, 2011, pp. 33-39.
55 D. H. Lee and P. Brusilovsky, "Using self-defined group activities for improving recommendations in collaborative tagging systems," in Proceedings of the 4th ACM Conference on Recommender Systems, Barcelona, Spain, 2010, pp. 221-224.
56 D. W. McDonald, "Recommending collaboration with social networks: a comparative evaluation," in Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, Lauderdale, FL, 2003, pp. 593-600.
57 J. Al-Sharawneh and M. A. Williams, "Credibility-aware Web-based social network recommender: follow the leader," in Proceedings of the 2nd Workshop on Recommender Systems and the Social Web (RSWeb), Barcelona, Spain, 2010, pp. 1-8.
58 P. H. Chia and G. Pitsilis, "Exploring the use of explicit trust links for filtering recommenders: a study on Epinions.com," Information and Media Technologies, vol. 6, no. 3, pp. 871-883, 2011.
59 T. DuBois, J. Golbeck, J. Kleint, and A. Srinivasan, "Improving recommendation accuracy by clustering social networks with trust," in Proceedings of ACM Workshop on Recommender Systems & the Social Web (RSWeb), New York, NY, 2009, pp. 1-8.
60 J. Golbeck and J. Hendler, "Filmtrust: movie recommendations using trust in web-based social networks," in Proceedings of the 3rd IEEE Consumer Communications and Networking Conference (CCNC), Las Vegas, NV, 2006, pp. 282-286.
61 H. Ma, H. Yang, M. R. Lyu, and I. King, "SoRec: social recommendation using probabilistic matrix factorization," in Proceedings of the 17th ACM Conference on Information and Knowledge Management, Napa Valley, CA, 2008, pp. 931-940.
62 G. Guo, J. Zhang, and D. Thalmann, "A simple but effective method to incorporate trusted neighbors in recommender systems," in User Modeling, Adaptation, and Personalization. Heidelberg: Springer, 2012, pp. 114-125.
63 M. Jamali and M. Ester, "Trustwalker: a random walk model for combining trust-based and item-based recommendation," in Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Paris, 2009, pp. 397-406.
64 M. Jamali and M. Ester, "A matrix factorization technique with trust propagation for recommendation in social networks," in Proceedings of the 4th ACM Conference on Recommender Systems, Barcelona, Spain, 2010, pp. 135-142.
65 Y. Matsuo and H. Yamamoto, "Diffusion of recommendation through a trust network," in Proceedings of International Conference on Weblogs and Social Media (ICWSM), Boulder, CO, 2007.
66 S. Magureanu, N. Dokoohaki, S. Mokarizadeh, and M. Matskin, "Design and analysis of a Gossip-based decentralized trust recommender system," in Proceedings of the 4th ACM RecSys Workshop on Recommender Systems and the Social Web, Dublin, Ireland, 2012, pp. 1-8.
67 D. O'Doherty, S. Jouili, and P. Van Roy, "Trust-based recommendation: an empirical analysis," in Proceedings of the 6th ACM SIGKDD Workshop on Social Network Mining and Analysis (SNA-KDD), Beijing, China, 2012.
68 F. E. Walter, S. Battiston, and F. Schweitzer, "Personalised and dynamic trust in social networks," in Proceedings of the 3rd ACM Conference on Recommender Systems, New York, NY, 2009, pp. 197-204.