A. Acerbi, S. Ghirlanda, and M. Enquist, The Logic of Fashion Cycles, PLoS ONE, vol.81, issue.3, p.2012
DOI : 10.1371/journal.pone.0032541.s008

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, issue.6, 2005.
DOI : 10.1109/TKDE.2005.99

J. Allan, Introduction to Topic Detection and Tracking. In Topic Detection and Tracking: Event-Based Information Organization, 2002.

X. Amatriain, N. Lathia, J. Pujol, H. Kwak, and N. Oliver, The wisdom of the few, Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval, SIGIR '09, 2009.
DOI : 10.1145/1571941.1572033

X. Amatriain, J. Pujol, and N. Oliver, I Like It... I Like It Not: Evaluating User Ratings Noise in Recommender Systems. User Modeling, Adaptation, and Personalization, pp.247-258, 2009.

C. Anderson, The Long Tail: Why the Future of Business is Selling Less of More. Hyperion, 2008.

S. Aral and D. Walker, Identifying Influential and Susceptible Members of Social Networks, Science, vol.337, issue.6092, 2012.
DOI : 10.1126/science.1215842

B. A. Asur, G. Huberman, C. Szabo, and . Wang, Trends in Social Media: Persistence and Decay, Proceedings of the 5 th International AAAI Conference on Weblogs and Social Media (ICWSM), 2011.
DOI : 10.2139/ssrn.1755748

E. Bakshy, J. M. Hofman, W. A. Mason, and D. J. Watts, Everyone's an influencer, Proceedings of the fourth ACM international conference on Web search and data mining, WSDM '11, 2011.
DOI : 10.1145/1935826.1935845

M. Balabanovi´cbalabanovi´c and Y. Shoham, Fab: Content-Based, Collaborative Recommendation, Communications of the ACM, 1997.

A. Barabasi, The origin of bursts and heavy tails in human dynamics, Nature, vol.7, issue.7039, p.81, 2005.
DOI : 10.1038/44831

H. Becker, M. Naaman, and L. Gravano, Learning similarity metrics for event identification in social media, Proceedings of the third ACM international conference on Web search and data mining, WSDM '10, 2010.
DOI : 10.1145/1718487.1718524

H. Becker, M. Naaman, and L. Gravano, Beyond Trending Topics: Real-world Event Identification on Twitter, Proceedings of the 5 th International AAAI Conference on Weblogs and Social Media (ICWSM), 2011.

D. M. Blei and J. D. Lafferty, Dynamic topic models, Proceedings of the 23rd international conference on Machine learning , ICML '06, 2006.
DOI : 10.1145/1143844.1143859

D. M. Blei, A. Y. Ng, and M. I. Jordan, Latent dirichlet allocation, Journal of Machine Learning Research, 2003.

F. Bodendorf and C. Kaiser, Detecting opinion leaders and trends in online social networks, Proceeding of the 2nd ACM workshop on Social web search and mining, SWSM '09, 2009.
DOI : 10.1145/1651437.1651448

J. Borge-holthoefer, A. Rivero, I. García, E. Cauhé, A. Ferrer et al., Structural and Dynamical Patterns on Online Social Networks: The Spanish May 15th Movement as a Case Study, PLoS ONE, vol.96, issue.4, 2011.
DOI : 10.1371/journal.pone.0023883.t001

J. S. Breese, D. Heckerman, and C. Kadie, Empirical Analysis of Predictive Algorithms for Collaborative Filtering, Proceedings of the 14 th ACM Conference on Uncertainty in Artificial Intelligence (UAI), 1998.

R. Burt, The Social Capital of Opinion Leaders. The Annals of the, American Academy of Political and Social Science, vol.566, issue.1, 1999.

Ò. Celma and P. Herrera, A new approach to evaluating novel recommendations, Proceedings of the 2008 ACM conference on Recommender systems, RecSys '08, pp.179-186, 2008.
DOI : 10.1145/1454008.1454038

M. Cha, H. Haddadi, F. Benevenuto, and K. Gummadi, Measuring User Influence in Twitter: The Million Follower Fallacy, Proceedings of the 4 th International AAAI Conference on Weblogs and Social Media (ICWSM), 2010.

J. Chen, W. Geyer, C. Dugan, M. Muller, and I. Guy, Make new friends, but keep the old, Proceedings of the 27th international conference on Human factors in computing systems, CHI 09
DOI : 10.1145/1518701.1518735

W. Chen, J. Chu, J. Luan, H. Bai, Y. Wang et al., Collaborative filtering for orkut communities, Proceedings of the 18th international conference on World wide web, WWW '09, 2009.
DOI : 10.1145/1526709.1526801

Z. Cheng, J. Caverlee, and K. Lee, You are where you tweet, Proceedings of the 19th ACM international conference on Information and knowledge management, CIKM '10, 2010.
DOI : 10.1145/1871437.1871535

Z. Cheng, J. Caverlee, K. Lee, D. Sui, ]. E. Cho et al., Exploring Millions of Footprints in Location Sharing Services Friendship and Mobility: User Movement In Location-Based Social Networks, Proceedings of the 5 th International AAAI Conference on Weblogs and Social Media (ICWSM) Proceedings of the 17 th ACM International Conference on Knowledge Discovery and Data Mining (SIGKDD), 2011.

R. Crane and D. Sornette, Robust dynamic classes revealed by measuring the response function of a social system, Proceedings of the National Academy of Sciences of the United States of America (PNAS), 2008.
DOI : 10.1073/pnas.0803685105

. Boyd, The Future of Privacy: How Privacy Norms Can Inform Regulation, Invited Talk at the 32 nd International Conference of Data Protection and Privacy Commissioners, 2010.

A. Das, M. Datar, A. Garg, and S. Rajaram, Google news personalization, Proceedings of the 16th international conference on World Wide Web , WWW '07, 2007.
DOI : 10.1145/1242572.1242610

J. Davidson, B. Liebald, J. Liu, P. Nandy, T. Van-vleet et al., The YouTube video recommendation system, Proceedings of the fourth ACM conference on Recommender systems, RecSys '10, 2010.
DOI : 10.1145/1864708.1864770

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.434.9301

P. De-lauwe, Paris et l'agglomération parisienne, Presses Universitaires de France, 1952.

J. Delgado and N. Ishii, Memory-Based Weighted Majority Prediction, Proceedings of the 22 nd ACM International Conference on Research and Development in Information Retrieval (SIGIR) -workshop on recommender systems, 1999.

M. Deshpande and G. Karypis, recommendation algorithms, ACM Transactions on Information Systems, vol.22, issue.1, 2004.
DOI : 10.1145/963770.963776

C. Droge, M. Stanko, and W. Pollitte, Lead Users and Early Adopters on the Web: The Role of New Technology Product Blogs*, Journal of Product Innovation Management, vol.31, issue.(4, 2010.
DOI : 10.1111/j.1540-5885.2009.00700.x

N. Eagle and A. Pentland, Eigenbehaviors: Identifying Structure in Routine, Behavioral Ecology and Sociobiology, vol.63, 2009.

A. Gelman and J. Hill, Data Analysis Using Regression and Multilevel/Hierarchical Models, 2006.
DOI : 10.1017/CBO9780511790942

URL : https://repozitorij.uni-lj.si/Dokument.php?id=69512

N. Glance, M. Hurst, and T. Tomokiyo, Blogpulse: Automated Trend Discovery for Weblogs, WWW 2004 workshop on the weblogging ecosystem: Aggregation, analysis and dynamics, 2004.

J. Golbeck, C. Robles, and K. Turner, Predicting personality with social media, Proceedings of the 2011 annual conference extended abstracts on Human factors in computing systems, CHI EA '11, 2011.
DOI : 10.1145/1979742.1979614

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.186.5890

D. Goldberg, D. Nichols, B. M. Oki, and D. Terry, Using collaborative filtering to weave an information tapestry, Communications of the ACM, vol.35, issue.12, 1992.
DOI : 10.1145/138859.138867

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.104.3739

K. Goldberg, T. Roeder, D. Gupta, and C. Perkins, Eigentaste: A Constant Time Collaborative Filtering Algorithm, Information Retrieval, vol.4, issue.2, 2001.

S. González-bailón, J. Borge-holthoefer, A. Rivero, and Y. Moreno, The Dynamics of Protest Recruitment through an Online Network Scientific reports, 2011.

A. Goyal, F. Bonchi, and L. V. Lakshmanan, Learning influence probabilities in social networks, Proceedings of the third ACM international conference on Web search and data mining, WSDM '10, 2010.
DOI : 10.1145/1718487.1718518

F. A. Haight, Handbook of the Poisson Distribution, 1967.

S. Havre, B. Hetzler, and L. Nowell, ThemeRiver: visualizing theme changes over time, IEEE Symposium on Information Visualization 2000. INFOVIS 2000. Proceedings, 2000.
DOI : 10.1109/INFVIS.2000.885098

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.135.4974

J. L. Herlocker, J. A. Konstan, A. Borchers, and J. , An algorithmic framework for performing collaborative filtering, Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval , SIGIR '99, 1999.
DOI : 10.1145/312624.312682

J. L. Herlocker, J. A. Konstan, L. G. Terveen, and J. T. , Evaluating collaborative filtering recommender systems, ACM Transactions on Information Systems, vol.22, issue.1, 2004.
DOI : 10.1145/963770.963772

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.78.8384

R. Hu and P. Pu, Acceptance issues of personality-based recommender systems, Proceedings of the third ACM conference on Recommender systems, RecSys '09, 2009.
DOI : 10.1145/1639714.1639753

Y. Hu, Y. Koren, and C. Volinsky, Collaborative Filtering for Implicit Feedback Datasets, 2008 Eighth IEEE International Conference on Data Mining, 2008.
DOI : 10.1109/ICDM.2008.22

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.167.5120

M. Jamali and M. Ester, A matrix factorization technique with trust propagation for recommendation in social networks, Proceedings of the fourth ACM conference on Recommender systems, RecSys '10, 2010.
DOI : 10.1145/1864708.1864736

T. Jambor, J. Wang, and N. Lathia, Using control theory for stable and efficient recommender systems, Proceedings of the 21st international conference on World Wide Web, WWW '12, 2012.
DOI : 10.1145/2187836.2187839

B. Jansen, M. Zhang, K. Sobel, and A. Chowdury, Micro-blogging as online word of mouth branding, Proceedings of the 27th international conference extended abstracts on Human factors in computing systems, CHI EA '09, 2009.
DOI : 10.1145/1520340.1520584

G. Jawaheer, M. Szomszor, and P. Kostkova, Characterisation of explicit feedback in an online music recommendation service, Proceedings of the fourth ACM conference on Recommender systems, RecSys '10, 2010.
DOI : 10.1145/1864708.1864776

N. Jones, P. Pu, D. Kempe, J. Kleinberg, and E. Tardos, User Technology Adoption Issues in Recommender Systems Influential Nodes in a Diffusion Model for Social Networks, Proceedings of Networking and Electronic Commerce Research Conference (NAEC) Proceedings of the 32 nd International Conference on Automata, Languages and Programming (ICALP), pp.379-418, 2005.

J. Kleinberg, Bursty and hierarchical structure in streams, Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining , KDD '02, 2002.
DOI : 10.1145/775047.775061

N. Koenigstein, G. Dror, and Y. Koren, Yahoo! music recommendations, Proceedings of the fifth ACM conference on Recommender systems, RecSys '11, 2011.
DOI : 10.1145/2043932.2043964

J. A. Konstan, S. M. Mcnee, C. Ziegler, R. Torres, N. Kapoor et al., Lessons on Applying Automated Recommender Systems to Information-Seeking Tasks, Proceedings of the National Conference on Artificial Intelligent, 2006.

I. Konstas, V. Stathopoulos, and J. Jose, On social networks and collaborative recommendation, Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval, SIGIR '09, 2009.
DOI : 10.1145/1571941.1571977

W. Kornblum and C. Smith, Sociology in a Changing World, 2007.

H. Kwak, C. Lee, H. Park, and S. Moon, What is Twitter, a social network or a news media?, Proceedings of the 19th international conference on World wide web, WWW '10, 2010.
DOI : 10.1145/1772690.1772751

P. Lazarsfeld and E. Katz, Personal Influence: the Part Played by People in the Flow of Mass Communications, 1955.

D. Lemire and A. Maclachlan, Slope One Predictors for Online Rating-Based Collaborative Filtering, Proceedings of the 2005 SIAM International Conference on Data Mining (SDM), 2005.
DOI : 10.1137/1.9781611972757.43

J. Leskovec, L. Backstrom, and J. Kleinberg, Meme-tracking and the dynamics of the news cycle, Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining, KDD '09, 2009.
DOI : 10.1145/1557019.1557077

H. Li, Y. Wang, D. Zhang, M. Zhang, and E. Chang, Pfp, Proceedings of the 2008 ACM conference on Recommender systems, RecSys '08, 2008.
DOI : 10.1145/1454008.1454027

D. Liben-nowell, J. Novak, R. Kumar, P. Raghavan, and A. Tomkins, Geographic routing in social networks, Proceedings of the National Academy of Sciences, vol.102, issue.33, 2005.
DOI : 10.1073/pnas.0503018102

G. Linden, B. Smith, and J. York, Amazon.com recommendations: item-to-item collaborative filtering, IEEE Internet Computing, vol.7, issue.1, 2003.
DOI : 10.1109/MIC.2003.1167344

J. Lindqvist, J. Cranshaw, J. Wiese, J. Hong, and J. Zimmerman, I'm the mayor of my house, Proceedings of the 2011 annual conference on Human factors in computing systems, CHI '11, 2011.
DOI : 10.1145/1978942.1979295

D. J. Mackay, Information Theory, Inference and Learning Algorithms, 2003.

S. M. Mcnee, J. Riedl, and J. A. Konstan, Being accurate is not enough, CHI '06 extended abstracts on Human factors in computing systems, CHI EA '06, 2006.
DOI : 10.1145/1125451.1125659

R. Merton, Patterns of Influence: Local and Cosmopolitan Influentials, Social Theory and Social Structure, 1957.

B. N. Miller, I. Albert, S. K. Lam, J. A. Konstan, and J. , MovieLens unplugged, Proceedings of the 8th international conference on Intelligent user interfaces, IUI '03, 2003.
DOI : 10.1145/604045.604094

M. Muller, N. S. Shami, D. R. Millen, and J. Feinberg, We are all lurkers, Proceedings of the 16th ACM international conference on Supporting group work, GROUP '10, 2010.
DOI : 10.1145/1880071.1880106

T. Murakami, K. Mori, and R. Orihara, Metrics for Evaluating the Serendipity of Recommendation Lists, New Frontiers in Artificial Intelligence, 2008.
DOI : 10.1007/978-3-540-78197-4_5

M. Naaman, H. Becker, and L. Gravano, Hip and trendy: Characterizing emerging trends on Twitter, Journal of the American Society for Information Science and Technology, vol.8, issue.6, 2011.
DOI : 10.1002/asi.21489

M. Nagarajan, K. Gomadam, A. Sheth, A. Ranabahu, R. Mutharaju et al., Spatio-Temporal-Thematic Analysis of Citizen Sensor Data: Challenges and Experiences, 2009.
DOI : 10.1007/978-3-642-04409-0_52

C. Neustaedter, A. Tang, and J. K. Tejinder, The role of community and groupware in geocache creation and maintenance, Proceedings of the 28th international conference on Human factors in computing systems, CHI '10, 2010.
DOI : 10.1145/1753326.1753590

S. Nikolov, Trend or No Trend: A Novel Nonparametric Method for Classifying Time Series, 2012.

D. W. Oard and J. Kim, Implicit Feedback for Recommender Systems, Proceedings of the AAAI Workshop on Recommender Systems, 1998.

M. P. O-'mahony, N. J. Hurley, and G. Silvestre, Detecting Noise in Recommender System Databases, Proceedings of the 11 th International Conference on Intelligent User Interfaces (IUI), 2006.

J. Onnela, S. Arbesman, M. C. González, A. Barabási, and N. A. Christakis, Geographic Constraints on Social Network Groups, PLoS ONE, vol.20, issue.4, 2011.
DOI : 10.1371/journal.pone.0016939.g005

M. Panik, Advanced Statistics From an Elementary Point of View [86] E. Pariser. The Filter Bubble: What the Internet is Hiding from You, 2005.

D. Parra and X. Amatriain, Walk the Talk, pp.255-268, 2011.
DOI : 10.1007/978-3-642-13470-8_32

D. M. Pennock, E. Horvitz, S. Lawrence, and C. L. Giles, Collaborative Filtering by Personality Diagnosis: A Hybrid Memory-And Model-Based Approach, Proceedings of the 16 th ACM Conference on Uncertainty in Artificial Intelligence (UAI), 2000.

S. Petrovi´cpetrovi´c, M. Osborne, and V. Lavrenko, Streaming First Story Detection with Application to Twitter, Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL). Association for Computational Linguistics, 2010.

O. Phelan, K. Mccarthy, and B. Smyth, Using twitter to recommend real-time topical news, Proceedings of the third ACM conference on Recommender systems, RecSys '09, 2009.
DOI : 10.1145/1639714.1639794

URL : http://hdl.handle.net/10197/1893

D. Quercia and L. Capra, FriendSensing, Proceedings of the third ACM conference on Recommender systems, RecSys '09
DOI : 10.1145/1639714.1639766

D. Quercia, M. Kosinski, D. Stillwell, and J. Crowcroft, Our Twitter Profiles, Our Selves: Predicting Personality with Twitter, 2011 IEEE Third Int'l Conference on Privacy, Security, Risk and Trust and 2011 IEEE Third Int'l Conference on Social Computing, 2011.
DOI : 10.1109/PASSAT/SocialCom.2011.26

D. Quercia, N. Lathia, F. Calabrese, G. D. Lorenzo, and J. Crowcroft, Recommending Social Events from Mobile Phone Location Data, 2010 IEEE International Conference on Data Mining, 2010.
DOI : 10.1109/ICDM.2010.152

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.469.1876

A. M. Rashid, I. Albert, D. Cosley, S. K. Lam, S. M. Mcnee et al., Getting to know you, Proceedings of the 7th international conference on Intelligent user interfaces , IUI '02, 2002.
DOI : 10.1145/502716.502737

S. Rendle, C. Freudenthaler, and L. Schmidt-thieme, Factorizing personalized Markov chains for next-basket recommendation, Proceedings of the 19th international conference on World wide web, WWW '10, 2010.
DOI : 10.1145/1772690.1772773

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.187.682

P. Resnick, N. Iacovou, M. Suchak, P. Bergstrom, and J. , GroupLens, Proceedings of the 1994 ACM conference on Computer supported cooperative work , CSCW '94, 1994.
DOI : 10.1145/192844.192905

P. Resnick and H. R. Varian, Recommender systems, Communications of the ACM, vol.40, issue.3, 1997.
DOI : 10.1145/245108.245121

F. Ricci, L. Rokach, and B. Shapira, Introduction to Recommender Systems Handbook . Recommender Systems Handbook, pp.1-35, 2011.
DOI : 10.1007/978-0-387-85820-3_1

D. Saez-trumper, G. Comarela, V. Almeida, R. Baeza-yates, and F. Benevenuto, Finding trendsetters in information networks, Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining, KDD '12, 2012.
DOI : 10.1145/2339530.2339691

D. Saez-trumper, D. Quercia, and J. Crowcroft, Ads and the city, Proceedings of the sixth ACM conference on Recommender systems, RecSys '12, 2012.
DOI : 10.1145/2365952.2365988

T. Sakaki, M. Okazaki, and Y. Matsuo, Earthquake shakes Twitter users, Proceedings of the 19th international conference on World wide web, WWW '10, pp.851-860, 2010.
DOI : 10.1145/1772690.1772777

B. Sarwar, G. Karypis, J. Konstan, and J. , Item-based collaborative filtering recommendation algorithms, Proceedings of the tenth international conference on World Wide Web , WWW '01, 2001.
DOI : 10.1145/371920.372071

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.167.7612

B. Sarwar, G. Karypis, J. Konstan, and J. , Analysis of recommendation algorithms for e-commerce, Proceedings of the 2nd ACM conference on Electronic commerce , EC '00, 2000.
DOI : 10.1145/352871.352887

S. Scellato, A. Noulas, R. Lambiotte, and C. Mascolo, Socio-spatial Properties of Online Location-based Social Networks, Proceedings of the 5 th International AAAI Conference on Weblogs and Social Media (ICWSM), 2011.

G. Shani and A. Gunawardana, Evaluating Recommender Systems. Recommender Systems Handbook, pp.257-298, 2009.

D. Sornette and A. Helmstetter, Endogenous versus Exogenous Shocks in Systems with Memory. Physica A: Statistical Mechanics and its Applications, p.318, 2003.

C. Steinfield, N. B. Ellison, and C. Lampe, Social capital, self-esteem, and use of online social network sites: A longitudinal analysis, Journal of Applied Developmental Psychology, vol.29, issue.6, p.29, 2008.
DOI : 10.1016/j.appdev.2008.07.002

X. Su and T. M. Khoshgoftaar, A Survey of Collaborative Filtering Techniques, Advances in Artificial Intelligence, vol.46, issue.2, 2009.
DOI : 10.1002/asi.10372

J. Surowiecki, The Wisdom of Crowds: Why the Many Are Smarter Than the Few and How Collective Wisdom Shapes Business. Economies, Societies and Nations, 2004.

J. Tang, J. Sun, C. Wang, Z. Yang, S. T. Dumais et al., Social Influence Analysis in Large-scale Networks Potential for Personalization, Proceedings of the 15 th International Conference on Knowledge Discovery and Data Mining, 2009.

L. Terveen and W. Hill, Beyond Recommender Systems: Helping People Help Each Other. HCI in the New Millennium, pp.487-509, 2001.

J. Travers and S. Milgram, An Experimental Study of the Small World Problem, Sociometry, 1969.

S. Vargas and P. Castells, Rank and relevance in novelty and diversity metrics for recommender systems, Proceedings of the fifth ACM conference on Recommender systems, RecSys '11, 2011.
DOI : 10.1145/2043932.2043955

A. Vázquez, J. G. Oliveira, Z. Dezsö, K. Goh, I. Kondor et al., Modeling bursts and heavy tails in human dynamics, Physical Review E, vol.73, issue.3, 2006.
DOI : 10.1103/PhysRevE.73.036127

X. Wang and A. Mccallum, Topics over time, Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining , KDD '06, 2006.
DOI : 10.1145/1150402.1150450

X. Wang, C. Zhai, X. Hu, and R. Sproat, Mining correlated bursty topic patterns from coordinated text streams, Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining , KDD '07, 2007.
DOI : 10.1145/1281192.1281276

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.572.508

D. Watts, Challenging the Influentials Hypothesis, Measuring Word of Mouth, vol.3, 2007.

D. Watts and P. Dodds, Influentials, Networks, and Public Opinion Formation, Journal of Consumer Research, vol.34, issue.4, 2007.
DOI : 10.1086/518527

URL : http://cdg.columbia.edu/uploads/papers/watts2007_influentials.pdf

D. Watts and S. Strogatz, Collective Dynamics of 'Small-world' Networks, Nature, vol.393, issue.6684, 1998.

D. J. Watts, Everything Is Obvious: *Once You Know the Answer, Crown Business, 2011.

J. Weng, E. Lim, J. Jiang, and Q. He, TwitterRank, Proceedings of the third ACM international conference on Web search and data mining, WSDM '10, 2010.
DOI : 10.1145/1718487.1718520

I. H. Witten and E. Frank, Data mining, ACM SIGMOD Record, vol.31, issue.1, 2005.
DOI : 10.1145/507338.507355

F. Wu and B. A. Huberman, How Public Opinion Forms, Proceedings of the 4 th International Workshop on Internet and Network Economics (WINE), 2008.
DOI : 10.1007/978-3-540-92185-1_39

M. Wu, Collaborative Filtering via Ensembles of Matrix Factorizations, Proceedings of KDD Cup and Workshop, 2007.

S. Yardi and D. Boyd, Tweeting from the Town Square: Measuring Geographic Local Networks, Proceedings of the 4 th AAAI International Conference on Weblogs and Social Media (ICWSM), 2010.

L. Yu, S. Asur, and B. A. Huberman, What Trends in Chinese Social Media. The 5 th Workshop on Social Network Mining and Analysis, 2011.

M. Zhang and N. Hurley, Avoiding monotony, Proceedings of the 2008 ACM conference on Recommender systems, RecSys '08, 2008.
DOI : 10.1145/1454008.1454030

Y. Zhang, J. Callan, and T. Minka, Novelty and redundancy detection in adaptive filtering, Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval , SIGIR '02, pp.81-88, 2002.
DOI : 10.1145/564376.564393

Y. Zhang, D. Séaghdha, D. Quercia, and T. Jambor, Auralist, Proceedings of the fifth ACM international conference on Web search and data mining, WSDM '12, 2012.
DOI : 10.1145/2124295.2124300

V. Zheng, Y. Zheng, X. Xie, and Q. Yang, Collaborative location and activity recommendations with GPS history data, Proceedings of the 19th international conference on World wide web, WWW '10, 2010.
DOI : 10.1145/1772690.1772795

Y. Zhou, D. Wilkinson, R. Schreiber, and R. Pan, Large-Scale Parallel Collaborative Filtering for the Netflix Prize, Algorithmic Aspects in Information and Management, 2008.
DOI : 10.1007/978-3-540-68880-8_32

T. Zhuo, Z. Kuscik, J. Liu, M. Medo, J. R. Wakeling et al., Solving the apparent diversity-accuracy dilemma of recommender systems, Proceedings of the National Academy of Sciences, vol.107, issue.10, 2010.
DOI : 10.1073/pnas.1000488107

C. Ziegler, S. M. Mcnee, J. A. Konstan, and G. Lausen, Improving recommendation lists through topic diversification, Proceedings of the 14th international conference on World Wide Web , WWW '05, 2005.
DOI : 10.1145/1060745.1060754

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.144.835