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Book description

The growth of social media over the last decade has revolutionized the way individuals interact and industries conduct business. Individuals produce data at an unprecedented rate by interacting, sharing, and consuming content through social media. Understanding and processing this new type of data to glean actionable patterns presents challenges and opportunities for interdisciplinary research, novel algorithms and tool development. Social Media Mining integrates social media, social network analysis, and data mining to provide a coherent platform to understand the basics and potentials of social media mining. It introduces the unique problems arising from social media data and presents fundamental concepts, emerging issues, and effective algorithms for network analysis and data mining. Suitable for use in advanced undergraduate and beginning graduate courses as well as professional short courses, the text contains exercises of different degrees of difficulty that improve understanding and help apply concepts, principles and methods for social media mining.

Reviews

'This is an exceptionally well-constructed book on social media that will be useful to academia and industry alike. The book covers the entire area of social network analysis in a comprehensive and understandable way.'

Charu Aggarwal - IBM T. J. Watson Research Center

'This is a delightful exploration of a multidisciplinary field in its simple and straightforward style. Social Media Mining introduces and connects underlying concepts with clarity and enables you to explore this amazing field further with confidence.'

Philip Yu - University of Illinois, Chicago

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References
Abbasi, Mohammad-Ali, Chai, Sun-Ki, Liu, Huan, and Sagoo, Kiran. 2012. Real-World behavior analysis through a social media lens. In: Social computing, behavioral-cultural modeling and prediction. Springer, pp. 18–26.
Abello, J., Resende, M., and Sudarsky, S. 2002. Massive quasi-clique detection. LATIN 2002: Theoretical Informatics.
Adamic, L.A., and Adar, E. 2003. Friends and neighbors on the web. Social networks, 25(3).
Abrahamson, E. and Rosenkopf, L. 1993. Institutional and competitive bandwagons: Using mathematical modeling as a tool to explore innovation diffusion. Academy of Management Review, JSTOR, 487–517.
Adomavicius, Gediminas, and Tuzhilin, Alexander. 2005. 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, 17(6), 734–749.
Agarwal, N., Liu, H., Tang, L., and Yu, P.S. 2008. Identifying the influential bloggers in a community. In: Proceedings of the International Conference on Web Search and Web Data Mining. ACM.
Ahuja, R.K., Magnanti, T.L., Orlin, J.B., and Weihe, K. 1993. Network flows: theory, algorithms and applications. Prentice-Hall, 41(3).
Albert, R., and Barabasi, A.L., 2000. Topology of evolving networks: local events and universality. Physical review letters, 85(24).
Al Hasan, Mohammad, Chaoji, Vineet, Salem, Saeed, and Zaki, Mohammed. 2006. Link prediction using supervised learning. In: SDM'06: Workshop on Link Analysis, Counter-terrorism and Security.
Anagnostopoulos, A., Kumar, R., and Mahdian, M. 2008. Influence and correlation in social networks. In: Proceedings of the 14th ACMSIGKDD international conference on Knowledge Discovery and Data ining. ACM.
Anderson, L.R., and Holt, C.A., 1996. Classroom games: information cascades. Journal of Economic Perspectives, 10(4).
Anderson, L.R., and Holt, C.A. 1997. Information cascades in the laboratory. American Economic Review.
Anderson, R.M., and May, R.M.Infectious diseases ofhumans: dynamics and control. Oxford University Press.
Ankerst, M., Breunig, M.M., Kriegel, H.P., and Sander, J. 1999. OPTICS: ordering points to identify the clustering structure. Proceedings of the 1999 ACM SIGMOD international conference on anagement of Data.
Aral, S., Muchnik, L., and Sundararajan, A. 2009. Distinguishing influence-based contagion from homophily-driven diffusion in dynamic networks. Proceedings of the National Academy of Sciences, 106(51).
Arguello, Jaime, Elsas, Jonathan, Callan, Jamie, and Carbonell, Jaime. 2008. Document representation and query expansion models for blog recommendation. In: Proceedings of the second international conference on Weblogs and Social edia (ICWSM).
Asch, S.E. 1956. Studies of independence and conformity: I. A minority of one against a unanimous majority. Psychological Monographs: General and Applied, 70(9).
Asur, Sitaram, and Huberman, Bernardo A. 2010. Predicting the future with social media. IEEE international conference on Web Intelligence and Intelligent Agent Technology, 1: 492–499. IEEE.
Backstrom, L., Huttenlocher, D., Kleinberg, J.M., and Lan, X. 2006. Group formation in large social networks: membership, growth, and evolution. In: Proceedings of the 12th ACM SIGKDD international conference on Knowledge Discovery and Data Mining. ACM.
Backstrom, L., Sun, E., and Marlow, C. 2010. Find me if you can: improving geographical prediction with social and spatial proximity. In: Proceedings of the 19th international conference on the World Wide Web. ACM, pp. 61–70.
Bailey, N.T.J., 1975. The mathematical theory of infectious diseases and its applications. Charles Griffin & Company.
Bakshy, E., Hofman, J.M., Mason, W.A., and Watts, D.J. 2001. Everyone's an influencer: quantifying influence on Twitter. In: Proceedings of the fourth ACM international conference on Web Search and Data Mining. ACM.
Banerjee, A.V 1992. A simple model of herd behavior. The Quarterly Journal of Economics, 107(3).
Barabasi, A.L., and Albert, R. 1999. Emergence of scaling in random networks. Science, 286(5439).
Barbier, Geoffrey, Zafarani, Reza, Gao, Huiji, Fung, Gabriel, and Liu, Huan. 2012. Maximizing benefits from crowdsourced data. Computational and Mathematical Organization Theory, 18(3), 257–279.
Barbier, Geoffrey, Feng, Zhuo, Gundecha, Pritam, and Liu, Huan. 2013. Provenance data in social media. Morgan & Claypool Publishers.
Barnes, S.J., and Scornavacca, E. 2004. Mobile marketing: the role of permission and acceptance. International Journal of Mobile Communications, 2(2), 128–139.
Barrat, Alain, Barthelemy, Marc, and Vespignani, Alessandro. 2008. Dynamical processes on complex networks. Vol. 1. Cambridge University Press.
Barwise, P., and Strong, C. 2002. Permission-based mobile advertising. Journal of interactive Marketing, 16(1), 14–24.
Bass, F. 1969. A new product growth model for product diffusion. Management Science, 15, 215–227.
Bell, W.G. 1995. The Great Plague in London in 1665. Bracken Books.
Bellma, R. 1956. On a routing problem. Notes, 16(1).
Ben-Akiva, M., Bierlaire, M., Koutsopoulos, H., and Mishalani, R. 1998. DynaMIT: a simulation-based system for traffic prediction. In: DACCORS Short Term Forecasting Workshop, The Netherlands.
Berger, E. 2001. Dynamic monopolies of constant size. Journal of Combinatorial Theory, Series B, 83(2).
Berkhin, P. 2006. A survey of clustering data mining techniques. Grouping Multidimensional Data.
Bernard, H. Russell. 2012. Social research methods: qualitative and quantitative approaches. Sage.
Bikhchandani, S., and Sharma, S. 2001. Herd behavior in financial markets. IMF Staff Papers.
Bikhchandani, S., Hirshleifer, D., and Welch, I. 1992. A theory of fads, fashion, custom, and cultural change as informational cascades. Journal of Political Economy, 5.
Bikhchandani, S., Hirshleifer, D., and Welch, I. 1998. Learning from the behavior of others: conformity, fads, and informational cascades. Journal of Economic Perspectives, 12(3).
Bishop, C.M. 1995. Neural networks for pattern recognition. Oxford University Press.
Bishop, C.M. 2006. Pattern recognition and machine learning. Vol. 4. Springer.
Bollobas, B. 2001. Random graphs. Vol. 73. Cambridge University Press.
Bonabeau, E., Dorigo, M., and Theraulaz, G. 1999. Swarm intelligence: from natural to artificial systems. Oxford University Press.
Bondy, J.A., and Murty, U.S.R., 1976. Graph theory with applications. Vol. 290. MacMillan, 5.
Boyd, Stephen Poythress, and Vandenberghe, Lieven. 2004. Convex optimization. Cambridge University Press.
Brandes, Ulrik. 2001. A faster algorithm for betweenness centrality. Journal of Mathematical Sociology, 25(2), 163–177.
Broder, Andrei, Kumar, Ravi, Maghoul, Farzin, Raghavan, Prabhakar, Rajagopalan, Sridhar, Stata, Raymie, Tomkins, Andrew, and Wiener, Janet. 2000. Graph structure in the web. Computer Networks, 33(1), 309–320.
Bryman, Alan. 2012. Social research methods. Oxford University Press.
Burke, Robin. 2002. Hybrid recommender systems: Survey and experiments. User Modeling and User-Adapted Interaction, 12(4), 331–370.
Candan K., Selcuk, and Sapino, Maria Luisa. 2010. Data management for multimedia retrieval. Cambridge University Press.
Cha, M., Haddadi, H., Benevenuto, F., and Gummadi, K.P. 2010. Measuring user influence in twitter: the million follower fallacy. In: AAAI Conference on Weblogs and Social Media, 14, 8.
Chakrabarti, Soumen. 2003. Mining the Web: discovering knowledge from hypertext data. Morgan Kaufmann.
Chen, Jilin, Geyer, Werner, Dugan, Casey, Muller, Michael, and Guy, Ido. 2009. Make new friends, but keep the old: recommending people on social networking sites. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. ACM, pp. 201–210.
Chinese, S., et al. 2004. Molecular evolution of the SARS coronavirus during the course of the SARS epidemic in China. Science, 303(5664), 1666.
Christakis, Nicholas A., and James H., Fowler. 2009. Connected: The surprising power of our social networks and how they shape our lives. Hachette Digital, Inc.
Christakis, N.A., and Fowler, J.H. 2007. The spread of obesity in a large social network over 32 years. New England Journal of Medicine, 357(4), 370–379.
Chung, F.R.K., 1996. Spectral graph theory. Journal of the American Mathematical Society.
Cialdini, R. B., and M. R., Trost. 1998. Social influence: Social norms, conformity and compliance. In: The handbook ofsocial psychology. 4th ed. Vol. 2, McGraw-Hill, pp. 151–192.
Clauset, Aaron, Shalizi, Cosma Rohilla, and Newman, Mark EJ. 2009. Power-law distributions in empirical data. SIAM review, 51(4): 661–703.
Coleman, J.S., Katz, E., Menzel, H. 1966. Medical innovation: a diffusion study. Bobbs-Merrill.
Cont, R., and Bouchaud, J.P. 2000. Herd behavior and aggregate fluctuations in financial markets. Macroeconomic Dynamics, 4(02).
Cormen, Thomas H., Leiserson, Charles E., Rivest, Ronald L., and Stein, Clifford. 2009. Introduction to algorithms. MIT Press.
Currarini, S., Jackson, M.O., and Pin, P. 2009. An Economic Model of Friendship: Homophily, Minorities, and Segregation. Econometrica, 77(4), 1003–1045.
Das, Abhinandan S., Datar, Mayur, Garg, Ashutosh, and Rajaram, Shyam. 2007. Google news personalization: scalable online collaborative filtering. In: Proceedings of the 16th international conference on the World Wide Web. ACM, pp. 271–280.
Dash, Manoranjan, and Liu, Huan. 1997. Feature selection for classification. Intelligent Data Analysis, 1(3), 131–156.
Dash, Manoranjan, and Liu, Huan. 2000. Feature selectionforclustering. In: Knowledge Discovery and Data Mining. Current Issues and New Applications. Springer, pp. 110–121.
Davidson, James, Liebald, Benjamin, Liu, Junning, Nandy, Palash, Van Vleet, Taylor, Gargi, Ullas, Gupta, Sujoy, He, Yu, Lambert, Mike, Livingston, Blake, et al. 2010. The YouTube video recommendation system. In: Proceedings of the fourth ACM conference on Recommender Systems. ACM, pp. 293–296.
Davies, D.L., and Bouldin, D.W. 1979. A cluster separation measure. IEEE Transactions on Pattern Analysis and Machine Intelligence.
De, I., Pool, S., and Kochen, M. 1978. Contacts and influence. Social Networks, 1, 148.
de Solla Price, D.J. 1965. Networks of scientific papers. Science, 149(3683).
Des Jarlais, D.C., Friedman, S.R., Sotheran, J.L., Wenston, J., Marmor, M.Yancovitz, S.R., Frank, B., Beatrice, S., and Mildvan, D. 1994. Continuity and change within an HIV epidemic. JAMA, 271(2).
Devenow, A., and Welch, I. 1996. Rational herding in financial economics. European Economic Review, 40(3).
Dia, H. 2001. An object-oriented neural network approach to short-term traffic forecasting. European Journal of Operational Research, 131(2), 253–261.
Diestel, R. 2005. Graph theory. 2005. Graduate Texts in Math.
Dietz, K. 1967. Epidemics and rumours: a survey. Journal of the Royal Statistical Society. Series A (General).
Dijkstra, E.W. 1959. A note on two problems in connexion with graphs. Numerische Mathematik, 1(1).
Dodds, P.S., and Watts, D.J. 2004. Universal behavior in a generalized model of contagion. Physical Review Letters, 92(21).
Drehmann, M., Oechssler, J., and Roider, A. 2005. Herding and contrarian behavior in financial markets – an internet experiment. American Economic Review, 95.
Duda, Richard O., Hart, Peter E., and Stork, David G. 2012. Pattern classification. Wiley-interscience.
Dunn, J.C. 1974. Well-separated clusters and optimal fuzzy partitions. Journal of Cybernetics, 4(1).
Dye, C., and Gay, N. 2003. Modeling the SARS epidemic. Science, 300(5627).
Easley, D., and Kleinberg, J.M. 2010. Networks, crowds, and markets. Cambridge Univesity Press.
Eberhart, R.C., Shi, Y., and Kennedy, J. 2001. Swarm intelligence. Morgan Kaufmann.
Edmonds, J., and Karp, R.M. 1972. Theoretical improvements in algorithmic efficiency for network flow problems. Journal of the ACM (JACM), 19(2).
Ellison, Nicole B., et al. 2007. Social network sites: definition, history, and scholarship. Journal of Computer-Mediated Communication, 13(1), 210–230.
Engelbrecht, A.P. 2005. Fundamentals of computational swarm intelligence. Recherche, 67(2).
Erdos, P., and Rényi, A. 1960. On the evolution of random graphs. Akademie Kiado.
Erdos, P., and Rényi, A. 1961. On the strength of connectedness of a random graph. Acta Mathematica Hungarica, 12(1).
Erdos, P., and Rényi, A. 1959. On random graphs. Publicationes Mathematicae Debrecen, 6, 290–297.
Ester, M., Kriegel, H.P., Sander, J., and Xu, X. 1996. A density-based algorithm for discovering clusters in large spatial databases with noise. Proceedings of the second international conference on Knowledge Discovery and Data Mining, AAAI Press, 226–231.
Faloutsos, M., Faloutsos, P., and Faloutsos, C. 1999. On power-law relationships of the internet topology. In: ACMSIGCOMM Computer Communication Review, 29.
Fisher, D. 1987. Improving inference through conceptual clustering. Proceedings of the 1987 AAAI conference, 461–465.
Floyd, R.W. 1962. Algorithm 97: shortest path. Communications of the ACM, 5(6).
Ford, L.R., and Fulkerson, D.R. 1956. Maximal flow through a network. Canadian Journal of Mathematics, 8(3), 399–404.
Fortunato, S. 2009. Community detection in graphs. Physics Reports, 486(3-5).
Friedman, J., Hastie, T., and Tibshirani, R. 2009. The elements of statistical learning. Vol. 1. Springer Series in Statistics.
Gale, D. 1996. What have we learned from social learning?European Economic Review, 40(3).
Gao, Huiji, Wang, Xufei, Barbier, Geoffrey, and Liu, Huan. 2011a. Promoting coordination for disaster relief – from crowdsourcing to coordination. In: Social computing, behavioral-cultural modeling and prediction. Springer, pp. 197–204.
Gao, H., Barbier, G., and Goolsby, R. 2011b. Harnessing the Crowdsourcing Power of Social Media for Disaster Relief. Intelligent Systems, IEEE, 26(3), 10–14.
Gao, H., Tang, J., and Liu, H. 2012a. Exploring Social-Historical Ties on Location-Based Social Networks. In: Proceedings of the sixth international conference on Weblogs and Social Media.
Gao, H., Tang, J., and Liu, H. 2012b. Mobile Location Prediction in Spatio-Temporal Context. Nokia Mobile Data Challenge Workshop.
Gao, Huiji, Tang, Jiliang, and Liu, Huan. 2012c. gSCorr: modeling geo-social correlations for new check-ins on location-based social networks. In: Proceedings of the 21st ACM international conference on Information and Knowledge Management. ACM, pp. 1582–1586.
Gibson, D., Kumar, R., and Tomkins, A. 2005. Discovering large dense subgraphs in massive graphs. In: Proceedings of the 31st international conference on Very Large Data Bases. VLDB Endowment.
Gilbert, E.N. 1959. Random graphs. Annals of Mathematical Statistics, 30(4).
Girvan, M., and Newman, M.E.J., 2002. Community structure in social and biological networks. Proceedings of the National Academy of Sciences, 99(12).
Golbeck, Jennifer, and Hendler, James. 2006. Filmtrust: movie recommendations using trust in web-based social networks. In: Proceedings of the IEEE Consumer Communications and Networking Conference, 96.
Goldberg, A.V., and Tarjan, R.E. 1988. A new approach to the maximum-flow problem. Journal of the ACM (JACM), 35(4).
Golub, B., and Jackson, M.O. 2010. Naive learning in social networks and the wisdom of crowds. American Economic Journal: Microeconomics, 2(1).
Goodchild, M.F., and Glennon, J.A. 2010. Crowdsourcing geographic information for disaster response: a research frontier. International Journal of Digital Earth, 3(3), 231–241.
Goodman, L., and Kruskal, W. 1954. Measures of associations for cross-validations. Journal of the Amerian Statistical Association, 49, 732–764.
Goyal, A., Bonchi, F., and Lakshmanan, L.V.S., 2010. Learning influence probabilities in social networks. In: Proceedings of the Third ACM international conference on Web Search and Data Mining. ACM.
Granovetter, M. 1976. Threshold models of collective behavior. American Journal of Sociology.
Granovetter, M.S. 1983. The strength of weak ties. American Journal of Sociology, 1.
Gray, V. 2007. Innovation in the states: a diffusion study. American Political Science Review, 67(4).
Griliches, Z. 2007. Hybrid corn: an exploration in the economics of technological change. Econometrica, Journal of the Econometric Society, 132.
Gruhl, D., Guha, R., Liben-Nowell, D., and Tomkins, A. 2004. Information diffusion through blogspace. In: Proceedings of the 13th international conference on the World Wide Web. ACM.
Guan, Y., Chen, H., Li, K.S., Riley, S., Leung, G.M., Webster, R., Peiris, J.S.M., and Yuen, K.Y. 2007. A model to control the epidemic of H5N1 influenza at the source. BMC Infectious Diseases, 7(1).
Gundecha, Pritam, and Liu, Huan. 2012. Mining Social Media: a Brief Introduction. Tutorials in Operations Research, 1(4).
Gundecha, Pritam, Barbier, Geoffrey, and Liu, Huan. 2011. Exploiting Vulnerability to Secure User Privacy on a Social Networking Site. In: Proceedings of the 17th ACM SIGKDD international conference on Knowledge Discovery and Data Mining. KDD, pp. 511–519.
Guy, Ido, Zwerdling, Naama, Ronen, Inbal, Carmel, David, and Uziel, Erel. 2010. Social media recommendation based on people and tags. In: Proceedings of the 33rd international ACM SIGIR conference on Research and Development in Information Retrieval. ACM, pp. 194–201.
Guyon, Isabelle. 2006. Feature extraction: foundations and applications. Vol. 207. Springer.
Hagerstrand, T., et al. 1967. Innovation diffusion as a spatial process. University of Chicago Press.
Hamblin, R.L., Jacobsen, R.B., and Miller, J.L.L., 1973. A mathematical theory of social change. Wiley.
Han, Jiawei, Kamber, Micheline, and Pei, Jian. 2006. Data mining: concepts and techniques. Morgan Kaufmann.
Handcock, M.S., Raftery, A.E., and Tantrum, J.M. 2007. Model-based clustering for social networks. Journal of the Royal Statistical Society: Series A (Statistics in Society), 170(2).
Hart, P.E., Nilsson, N.J., and Raphael, B. 2003. A formal basis for the heuristic determination of minimum cost paths. IEEE Transactions on Systems Science and Cybernetics, 4(2).
Haykin, Simon. 1994. Neural networks: a comprehensive foundation. Prentice Hall.
Hethcote, H.W. 1994. A thousand and one epidemic models. Lecture Notes in Biomath-ematics, Springer.
Hethcote, H.W. 2000. The mathematics of infectious diseases. SIAM Review, 42.
Hethcote, H.W., Stech, H.W., and van den Driessche, P. 1981. Periodicity and stability in epidemic models: a survey. In: Differential equations and applications in ecology, epidemics and population problems (S.N. Busenberg and K.L. Cooke, eds.), 65–82.
Hirschman, E.C. 1980. Innovativeness, novelty seeking, and consumer creativity. Journal of Consumer Research, 7.
Hirshleifer, D. 1997. Informational cascades and social conventions. University of Michigan Business School Working Paper No. 9705-10.
Hoff, P.D., Raftery, A.E., and Handcock, M.S. 2002. Latent space approaches to social network analysis. Journal of the American Statistical Association, 97(460).
Hopcroft, J., and Tarjan, R. 1971. Algorithm 447: efficient algorithms for graph manipulation. Communications of the ACM, 16(6).
Hu, Xia, Tang, Jiliang, Gao, Huiji, and Liu, Huan. 2013a. Unsupervised Sentiment Analysis with Emotional Signals. In: Proceedings of the 22nd international conference on the World Wide Web. WWW'13. ACM.
Hu, Xia, Tang, Lei, Tang, Jiliang, and Liu, Huan. 2013b. Exploiting Social Relations for Sentiment Analysis in Microblogging. In: Proceedings of the sixth ACM international conference on Web Search and Data Mining.
Jaccard, P. 1901. Distribution de la Flore Alpine: dans le Bassin des dranses et dans quelques régions voisines. Rouge.
Jackson, M.O. 2010. Social and economic networks. Princeton University Press.
Jain, A.K., and Dubes, R.C. 1999. Algorithms for clustering data. Prentice-Hall.
Jain, A.K., Murty, M.N., and Flynn, P.J. 1999. Data clustering: areview. ACM Computing Surveys (CSUR), 31(3).
Jameson, Anthony, and Smyth, Barry. 2007. Recommendation to groups. In: The adaptive web. Springer, pp. 596–627.
Jannach, Dietmar, Zanker, Markus, Felfernig, Alexander, and Friedrich, Gerhard. 2010. Recommender systems: an introduction. Cambridge University Press.
Jensen, T.R., and Toft, B. 1994. Graph coloring problems. Vol. 39. Wiley-Interscience.
Kadushin, Charles. 2012. Understanding Social Networks: theories, concepts, and findings: theories, concepts, and findings. Oxford University Press.
Kaplan, Andreas M., and Haenlein, Michael. 2010. Users of the world, unite! The challenges and opportunities of Social Media. Business Horizons, 53(1), 59–68.
Karinthy, F. 1929. Chains: Everythingis Different, Vintage Press.
Karypis, G., Han, E.H., and Kumar, V 1999. Chameleon: hierarchical clustering using dynamic modeling. Computer, 32(8), 68–75.
Katz, E., and Lazarsfeld, P.F. 2005. Personal influence: the part played by people in the flow of mass communications. Transaction Publication.
Keeling, M.J., and Eames, K.T.D., 2005. Networks and epidemic models. Journal of the Royal Society Interface, 2(4).
Keller, E., and Berry, J. 2003. The influentials: One American in ten tells the other nine how to vote, where to eat, and what to buy. Free Press.
Kempe, D., Kleinberg, J.M., and Tardos, É. 2003. Maximizing the spread of influence through a social network. In: Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining. ACM.
Kennedy, J. 2006. Swarm intelligence. In: Handbook of Nature-Inspired and Innovative Computing.
Kermack, W.O., and McKendrick, A.G. 1932. Contributions to the mathematical theory of epidemics. II. The problem of endemicity. Proceedings of the Royal Society of London. Series A, 138(834).
Kietzmann, Jan H., Hermkens, Kristopher, McCarthy, Ian P., and Silvestre, Bruno S. 2011. Social media? Get serious! Understanding the functional building blocks of social media. Business Horizons, 54(3), 241–251.
Kleinberg, J.M. 1998. Authoritative sources in a hyperlinked environment. Journal of the ACM (JACM), 46(5).
Kleinberg, J.M. 2007. Challenges in mining social network data: processes, privacy, and paradoxes. In: Proceedings of the 13th ACM SIGKDD international conference on Knowledge Discovery and Data Mining. ACM, pp. 4–5.
Kleinberg, Jon, and Tardos, Éva. 2005. Algorithm Design. Addison Wesley.
Konstas, Ioannis, Stathopoulos, Vassilios, and Jose, Joemon M. 2009. On social networks and collaborative recommendation. In: Proceedings of the 32nd international ACM SIGIR conference on Research and Development in Information Retrieval. ACM, pp. 195–202.
Kosala, R., and Blockeel, H. 2000. Web mining research: a survey. ACM Sig kdd Explorations Newsletter, 2(1).
Kossinets, G., and Watts, D.J. 2006. Empirical analysis of an evolving social network. Science, 311(5757).
Krapivsky, P.L., Redner, S., and Leyvraz, F. 2000. Connectivity of growing random networks. Physical Review Letters, 85(21).
Kruskal, J.B. 1956. On the shortest spanning subtree of a graph and the traveling salesman problem. Proceedings of the American athematical Society, 7(1), 48–50.
Kumar, R., Novak, J., and Tomkins, A. 2010. Structure and evolution of online social networks. In: Link ining: odels, Algorithms, and Applications, Springer.
Kumar, R., Raghavan, P., Rajagopalan, S., and Tomkins, A. 1999. Trawling the Web for emerging cyber-communities. Computer Networks, 31(11-16).
Kumar, S., Zafarani, R., and Liu, H. 2011. Understanding User Migration Patterns in Social Media. In: 25th AAAI Conference on Artificial Intelligence.
Kumar, Shamanth, Zafarani, Reza, and Liu, Huan. 2013. Whom Should I Follow? Identifying Relevant Users During Crises. In: Proceedings of the 24th ACM Conference on Hypertext and Social edia.
La Fond, T., and Neville, J. 2010. Randomization tests for distinguishing social influence and homophily effects. In: Proceedings of the 19th international conference on the World Wide Web. ACM.
Lancichinetti, A., and Fortunato, S. 2009. Community detection algorithms: a comparative analysis. Physical Review E, 80(5).
Langley, P. 1995. Elements of machine learning. Morgan Kaufmann.
Lawson, Charles L., and Hanson, Richard J. 1995. Solving least squares problems, 15. SIAM.
Leibenstein, H. 1950. Bandwagon, snob, and Veblen effects in the theory of consumers' demand. Quarterly Journal of Economics, 64(2).
Leicht, E.A., Holme, P., and Newman, M.E.J., 2005. Vertex similarity in networks. Physical Review E, 73(2).
Leskovec, J., Kleinberg, J.M., and Faloutsos, C. 2005. Graphs overtime: densification laws, shrinking diameters and possible explanations. In: Proceedings of the 11th AC SIGKDD international conference on Knowledge Discovery in Data ining. ACM.
Leskovec, J., Lang, K.J., and Mahoney, M. 2010. Empirical comparison of algorithms for network community detection. In: Proceedings of the 19th international conference on the World Wide Web. ACM.
Leskovec, J., McGlohon, M., Faloutsos, C., Glance, N., and Hurst, M. 2007. Cascading behavior in large blog graphs. Arxivpreprint arXiv:0704.2803.
Leskovec, Jure, Backstrom, Lars, and Kleinberg, Jon. 2009. Meme-tracking and the dynamics of the news cycle. In: Proceedings of the 15th AC SIGKDD international conference on Knowledge Discovery and Data ining. ACM, pp. 497–506.
Lewis, T.G. 2009. Network Science: theory and Applications. Wiley.
Liben-Nowell, D., and Kleinberg, J.M. 2003. The link-prediction problem for social networks. Journal of the American Society for Information Science and Technology, 58(7).
Lietsala, Katri, and Sirkkunen, Esa. 2008. Social media. Introduction to the tools and processes of participatory economy, Tampere University.
Liu, B. 2007. Web data mining: exploring hyperlinks, contents, and usage data. Springer Verlag.
Liu, Huan, and Motoda, Hiroshi. 1998. Feature extraction, construction and selection: a data mining perspective. Springer.
Liu, Huan, and Yu, Lei. 2005. Toward integrating feature selection algorithms for classification and clustering. IEEE Transactions on Knowledge and Data Engineering, 17(4), 491–502.
Liu, Jiahui, Dolan, Peter, and Pedersen, Elinl Ranby. 2010. Personalized news recommendation based on click behavior. In: Proceedings of the 15th international conference on Intelligent User Interfaces. ACM, pp. 31–40.
Lorrain, F., and White, H.C. 1971. Structural equivalence of individuals in social networks. Journal of Mathematical Sociology, 1(1).
Lu, Linyuan, and Zhou, Tao. 2011. Link prediction in complex networks: a survey. Physica A: Statistical Mechanics and its Applications, 390(6), 1150–1170.
Ma, Hao, Yang, Haixuan, Lyu, Michael R., and King, Irwin. 2008. Sorec: social recommendation using probabilistic matrix factorization. In: Proceedings of the 17th ACM conference on Information and Knowledge Management. ACM, pp. 931–940.
Ma, Hao, Lyu, Michael R., and King, Irwin. 2009. Learning to recommend with trust and distrust relationships. In: Proceedings of the third ACMconference on Recommender Systems. ACM, pp. 189–196.
Ma, Hao, Zhou, Dengyong, Liu, Chao, Lyu, Michael R., and King, Irwin. 2011. Rec-ommender systems with social regularization. In: Proceedings of the fourth ACM international conference on Web Search and Data Mining. ACM, pp. 287–296.
Macy, M.W. 1991. Chains of cooperation: threshold effects in collective action. American Sociological Review, 56.
Macy, M.W., and Willer, R. 2002. From factors to actors: computational sociology and agent-based modeling. Annual Review of Sociology, 28.
Mahajan, V. 1985. Models for innovation diffusion. Sage Publications.
Mahajan, V., and Muller, E. 1982. Innovative behavior and repeat purchase diffusion models. In: Proceedings of the American Marketing Educators Conference, 456, 460.
Mahajan, V., and Peterson, R.A. 1978. Innovation diffusion in a dynamic potential adopter population. Management Science, 24.
Mansfield, E. 1961. Technical change and the rate of imitation. Econometrica: Journal of the Econometric Society, 29.
Martino, J.P. 1983. Technological forecasting for decision making. McGraw-Hill.
Massa, Paolo, and Avesani, Paolo. 2004. Trust-aware collaborative filtering for recom-mender systems. In: On the move to meaningful internet systems 2004: CoopIS, DOA, and ODBASE. Springer, pp. 492–508.
McKay, B.D. 1980. Practical Graph Isomorphism. In: Proceedings of the 10th Manitoba Conference on Numerical Mathematics and Computing, October 1-4, 1980, vol.1. Utilitas Mathematica.
McPherson, M., Smith-Lovin, L., and Cook, J.M. 2001. Birds of a feather: homophily in social networks. Annual Review of Sociology, 27.
Midgley, D.F., and Dowling, G.R. 1978. Innovativeness: the concept and its measurement. Journal of Consumer Research, 4.
Milgram, S. 2009. Obedience to authority: an experimental view. Harper Perennial Modern Classics.
Milgram, S., Bickman, L., and Berkowitz, L. 1969. Note on the drawing power of crowds of different size. Journal of Personality and Social Psychology, 13(2).
Milligan, G.W., and Cooper, M.C. 1985. An examination of procedures for determining the number of clusters in a data set. Psychometrika, 50(2).
Mirkin, B.G. 2005. Clustering for data mining: a data recovery approach. Chapman & Hall/CRC.
Mislove, Alan, Marcon, Massimiliano, Gummadi, Krishna P., Druschel, Peter, and Bhattacharjee, Bobby. 2007. Measurement and analysis of online social networks. In: Proceedings of the seventh ACM SIGCOMM conference on Internet Measurement. ACM, pp. 29–42.
Mitchell, T.M. 1997. Machine learning. WCB.
MacGrawHill.Monreale, A., Pinelli, F., Trasarti, R., and Giannotti, F. 2009. WhereNext: a location predictor on trajectory pattern mining. In: Proceedings of the 15th ACM SIGKDD international conference on Knowledge Discovery and Data Mining. ACM, pp. 637–646.
Moore, C., and Newman, M.E.J., 1999. Epidemics and percolation in small-world networks. Physical Review E, 61(5).
Morris, S. 2000. Contagion. Review of Economic Studies, 67(1).
Morstatter, Fred, Pfeffer, Jurgen, Liu, Huan, and Carley, Kathleen M. 2013. Is the sample good enough? Comparing data from Twitter's streaming API with Twitter's firehose. Proceedings of ICWSM.
Motwani, R., and Raghavan, P. 1995. Randomized algorithms. Chapman & Hall/CRC.
Myung, I.J. 2003. Tutorial on maximum likelihood estimation. Journal of Mathematical Psychology, 47(1), 90–100.
Nelson, M.I., and Holmes, E.C. 2007. The evolution of epidemic influenza. Nature Reviews Genetics, 8(3).
Nemhauser, George L., and Wolsey, Laurence A. 1988. Integer and combinatorial optimization. Vol. 18. Wiley.
Neter, John, Wasserman, William, Kutner, Michael H., et al. 1996. Applied linear statistical models. Vol.4. Irwin.
Newman, M.E.J., 2002a. Mixing patterns in networks. Physical Review E, 67(2).
Newman, M.E.J., 2002b. Random graphs as models of networks. In: Handbook of graphs and networks, Wiley.
Newman, M.E.J., 2006. Modularity and community structure in networks. Proceedings of the National Academy of Sciences, 103(23).
Newman, M.E.J., 2010. Networks: an introduction. Oxford University Press.
Newman, M.E.J., and Girvan, M. 2003. Mixing patterns and community structure in networks. Statistical Mechanics of Complex Networks, 625.
Newman, M.E.J., Forrest, S., and Balthrop, J. 2002. Email networks and the spread of computer viruses. Physical Review E, 66(3).
Newman, M.E.J., Watts, D.J., and Strogatz, S.H. 2002. Random graph models of social networks. Proceedings of the National Academy ofSciences, 99(Suppl. 1).
Newman, M.E.J., Strogatz, S.H., and Watts, D.J. 2000. Random graphs with arbitrary degree distributions and their applications. Physical Review E, 64.
Newman, M.E.J., Barabasi, A.L., and Watts, D.J. 2006. The structure and dynamics of networks. Princeton University Press.
Ng, R.T., and Han, J. 1994. Efficient and Effective Clustering Methods for Spatial Data Mining. Proceedings of the 20th international conference on Very Large Data Bases, 144–155.
Nocedal, Jorge, and Wright, S. 2006. Numerical optimization, series in operations research and financial engineering. Springer.
Nohl, J., Clarke, C.H., et al. 2006. The Black Death. A Chronicle of the Plague. Westholme.
O'Connor, , Brendan, Balasubramanyan, Ramnath, Routledge, Bryan R., and Smith, Noah A. 2010. From tweets to polls: linking text sentiment to public opinion time series. In: Proceedings of the international AAAI conference on Weblogs and Social Media, pp. 122–129.
O'Donovan, John, and Smyth, Barry. 2005. Trust in recommender systems. In: Proceedings of the 10th international conference on Intelligent User Interfaces. ACM, pp. 167–174.
Onnela, J.P., and Reed-Tsochas, F. 2010. Spontaneous emergence of social influence in online systems. Proceedings of the National Academy of Sciences, 107(43).
Page, L., Brin, S., Motwani, R., and Winograd, T. 1999. The Page Rankcitation ranking: bringing order to the web, Stanford.
Palla, G., Derenyi, I., Farkas, I., and Vicsek, T. 2005. Uncovering the overlapping community structure of complex networks in nature and society. Nature, 435 (7043).
Palla, Gergely, Barabási, Albert-Laszlo, and Vicsek, Tamas. 2007. Quantifying social group evolution. Nature, 446(7136), 664–667.
Pang, Bo, and Lee, Lillian. 2008. Opinion mining and sentiment analysis. Foundations and Trends in Information Retrieval, 2(1-2), 1–135.
Papadimitriou, Christos H., and Steiglitz, Kenneth. 1998. Combinatorial optimization: algorithms and complexity. Courier Dover Publications.
Pastor-Satorras, R., and Vespignani, A. 2001. Epidemic spreading in scale-free networks. Physical Review Letters, 86(14).
Patterson, K.B., and Runge, T. 2002. Smallpox and the Native American. American Journal of the Medical Sciences, 323(4), 216.
Pattillo, J., Youssef, N., and Butenko, S. 2012. Clique Relaxation Models in Social Network Analysis. In: Handbook of Optimization in Complex Networks, Springer.
Pazzani, Michael J, and Billsus, Daniel. 2007. Content-based recommendation systems. In: The adaptive web. Springer, pp. 325–341.
Peleg, D. 1997. Local majority voting, small coalitions and controlling monopolies in graphs: A review. In: Proceedings of the third Colloquium on Structural Information and Communication Complexity, pp. 152–169.
Poli, R., Kennedy, J., and Blackwell, T. 2007. Particle swarm optimization. Swarm Intelligence, 1(1).
Price, D.S. 1976. A general theory of bibliometric and other cumulative advantage processes. Journal of the American Society for Information Science, 27(5).
Prim, R.C. 1957. Shortest connection networks and some generalizations. Bell System Technical Journal, 36(6), 1389–1401.
Quinlan, J.R. 1986. Induction of decision trees. Machine learning, 1(1).
Quinlan, J.R. 1993. C4. 5: programs for machine learning. Morgan Kaufmann.
Rand, W.M. 1971. Objective criteria for the evaluation of clustering methods. Journal of the American Statistical Association, 66.
Resnick, Paul, and Varian Hal, R. 1997. Recommender systems. Communications of the ACM, 40(3), 56–58.
Robertson, T.S. 1967. The process of innovation and the diffusion of innovation. Journal ofMarketing, 31.
Rogers, E.M. 2003. Diffusion of innovations. Free Press.
Rohlfs, J.H., and Varian, H.R. 2003. Bandwagon effects in high-technology industries. The MIT Press.
Rousseeuw, P.J. 1987. Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of Computational and Applied Mathematics, 20.
Ryan, B., and Gross, N.C. 1943. The diffusion of hybrid seed corn in two Iowa communities. Rural Sociology, 8(1), 15–24.
Salton, G., Wong, A., and Yang, C.S. 1975. A vector space model for automatic indexing. Communications of the ACM, 18(11).
Salton, Gerard, and McGill Michael, J. 1986. Introduction to modern information retrieval, McGraw-Hill.
Sander, J., Ester, M., Kriegel, H.P., and Xu, X. 1998. Density-based clustering in spatial databases: the algorithm GDBSCAN and its applications. Data Mining and Knowledge Discovery, 2(2).
Sarwar, Badrul, Karypis, George, Konstan, Joseph, and Riedl, John. 2001. Item-based collaborative filtering recommendation algorithms. In: Proceedings of the 10th international conference on the World Wide Web. ACM, pp. 285–295.
Scellato, S., Musolesi, M., Mascolo, C., Latora, V., and Campbell, A. 2011. Nextplace: a spatio-temporal prediction framework for pervasive systems. Pervasive Computing, 152–169.
Schafer Ben, J., Konstan, Joseph, and Riedi, John. 1999. Recommender systems in e-commerce. In: Proceedings of the First ACM conference on Electronic Commerce. ACM, pp. 158–166.
Schafer, J Ben, Frankowski, Dan, Herlocker, Jon, and Sen, Shilad. 2007. Collaborative filtering recommender systems. In: The adaptive web. Springer, pp. 291–324.
Scharfstein, D.S., and Stein, J.C. 1990. Herd behavior and investment. American Economic Review.
Schelling, T.C. 1971. Dynamic models of segregation. Journal of Mathematical Sociology, 1(2).
Schelling, T.C. 1978. Micromotives and macrobehavior. Norton & Company.
Scott, John. 1988. Social network analysis. Sociology, 22(1), 109–127.
Sen, Shilad, Vig, Jesse, and Riedl, John. 2009. Tagommenders: connecting users to items through tags. In: Proceedings of the 18th international conference on the World Wide Web. ACM, pp. 671–680.
Shalizi, C.R., and Thomas, A.C. 2010. Homophily and contagion are generically confounded in observational social network studies. Sociological Methods & Research, 40(2).
Shiller, R.J. 1995. Conversation, information, and herd behavior. American Economic Review, 85(2).
Sigurbjörnsson, Borkur, and Van Zwol, Roelof. 2008. Flickr tag recommendation based on collective knowledge. In: Proceedings of the 17th international conference on the WorldWide Web. ACM, pp. 327–336.
Simmel, G., and Hughes, E.C. 1949. The sociology of sociability. American Journal of Sociology, 55.
Simon, H.A. 1954. Bandwagon and underdog effects and the possibility of election predictions. Public Opinion Quarterly, 18(3).
Simon, H.A. 1955. On a class of skew distribution functions. Biometrika, 42(3/4).
Snijders, T.A.B., Steglich, C.E.G., and Schweinberger, M. 2006. Modeling the co-evolution of networks and behavior. In Longitudinal models in the behavioral and related sciences, Routledge.
Solomonoff, R., and Rapoport, A. 1951. Connectivity of random nets. Bulletin ofMath-ematical Biology, 13(2).
Spaccapietra, S., Parent, C., Damiani, M.L., De Macedo, J.A., Porto, F., and Vangenot, C. 2008. A conceptual view on trajectories. Data and Knowledge Engineering, 65(1), 126–146.
Stevens, S.S.On the Theory of Scales of Measurement, Science, 103.
Stephen P., Borgatti and Martin G., Everett. 1993. Two algorithms for computing regular equivalence. Social Networks, 15(4).
Strang, D., and Soule, S.A. 1998. Diffusion in organizations and social movements: from hybrid corn to poison pills. Annual Review ofSociology, 24.
Strehl, A., Ghosh, J., and Cardie, C. 2002. Cluster ensembles-a knowledge reuse framework for combining multiple partitions. Journal of Machine Learning Research, 3(3).
Su, Xiaoyuan, and Khoshgoftaar Taghi, M. 2009. A survey of collaborative filtering techniques. Advances in Artificial Intelligence, 4.
Sun, J., Faloutsos, C., Papadimitriou, S., and Yu, P.S. 2007. GraphScope: parameter-free mining of large time-evolving graphs. In: Proceedings of the 13th ACM SIGKDD international conference on Knowledge Discovery and Data Mining. ACM.
Tan, P.N., Steinbach, M., Kumar, V., et al. 2005. Introduction to data mining. Pearson Addison Wesley.
Tang, Jiliang, and Liu, Huan. 2012a. Feature Selection with Linked Data in Social Media. In: SDM.
Tang, Jiliang, and Liu, Huan. 2012b. Unsupervised Feature Selection for Linked Social Media Data. In: KDD.
Tang, Jiliang, and Liu, Huan. 2013. CoSelect: Feature Selection with Instance Selection for Social Media Data. In: SDM.
Tang, Jiliang, Gao, Huiji, Liu, Huan, and Sarma, Atish Das. 2012a. eTrust: understanding trust evolution in an online world. In: KDD.
Tang, Jiliang, Gao, Huiji, and Liu, Huan. 2012b. mTrust: discerning Multi-Faceted Trust in a Connected World. In: WSDM.
Tang, Jiliang, Gao, Huiji, Hu, Xia, and Liu, Huan. 2013a. Exploiting Homophily Effect for Trust Prediction. In: WSDM.
Tang, Jiliang, Hu, Xia, Gao, Huiji, and Liu, Huan. 2013b. Exploiting Local and Global Social Context for Recommendation. In: IJCAI.
Tang, L., and Liu, H. 2010. Community detection and mining in social media. Synthesis Lectures on Data Mining and Knowledge Discovery, 2(1).
Tang, Lei, and Liu, Huan. 2009. Relational learning via latent social dimensions. In: Proceedings of the 15th ACM SIGKDD international conference on Knowledge Discovery and Data Mining. ACM, pp. 817–826.
Tang, Lei, Wang, Xufei, and Liu, Huan. 2012. Community Detection via Heterogeneous Interaction Analysis. Data Mining and Knowledge Discovery (DMKD), 25(1), 1–33.
Tarde, G. 1907. Las leyes de la imitación: Estudio sociologico. Daniel Jorro.
Thanh, N., and Phuong, T.M. 2007. A Gaussian Mixture Model for Mobile Location Prediction. In: 2007 IEEE international conference on Research, Innovation and Vision for the Future, pp. 152–157.
Travers, J., and Milgram, S. 1969. An experimental study of the small world problem. Sociometry, 32.
Trotter, W. 1916. Instincts of the Herd in War and Peace.
Ugander, Johan, Karrer, Brian, Backstrom, Lars, and Marlow, Cameron. 2011. The Anatomy of the Facebook Social Graph, arXiv preprint arXiv:1111.4503.
Valente, T.W. 1995. Network models of the diffusion of innovations, Hampton Press.
Valente, T.W. 1996a. Network models of the diffusion of innovations. Computational & Mathematical Organization Theory, 2(2).
Valente, T.W. 1996b. Social network thresholds in the diffusion of innovations. Social Networks, 18(1).
Veblen, T. 1899. The Theory of the Leisure Class.
Wang, F., and Huang, Q.Y. 2010. The importance of spatial-temporal issues for case-based reasoning in disaster management. In: 2010 18th international conference on Geoinformatics. IEEE, pp. 1–5.
Wang, S.S., Moon, S.I., Kwon, K.H., Evans, C.A., and Stefanone, M.A. 2009. Face off: implications of visual cues on initiating friendship on Facebook. Computers in Human Behavior, 26(2).
Wang, Xufei, Tang, Lei, Gao, Huiji, and Liu, Huan. 2010. Discovering Overlapping Groups in Social Media. In: 10th IEEE international conference on Data Mining.
Wang, Xufei, Kumar, Shamanth, and Liu, Huan. 2011. A study of tagging behavior across social media. SIGIR Workshop on Social Web Search and Mining (SWSM).
Warshall, S. 1962. A theorem on boolean matrices. Journal of the ACM (JACM), 9(1).
Wasserman, S., and Faust, K. 1994. Social network analysis: Methods and applications. Cambridge University Press.
Watts, D.J. 1999. Networks, dynamics, and the small-world phenomenon 1. American Journal of Sociology, 105(2).
Watts, D.J. 2002. A simple model of global cascades on random networks. Proceedings of the National Academy of Sciences, 99(9).
Watts, D.J. 2003. Small worlds: the dynamics of networks between order and randomness. Princeton University Press.
Watts, D.J., and Dodds, P.S. 2007. Influentials, networks, and public opinion formation. Journal of Consumer Research, 34(4).
Watts, D.J., and Strogatz, S.H. 1997. Collective dynamics of small-world networks. Nature, 393(6684).
Welch, I. 1992. Sequential sales, learning, and cascades. Journal of Finance, 47.
Weng, J., Lim, E.P., Jiang, J., and He, Q. 2010. Twitterrank: finding topic-sensitive influential twitterers. In: Proceedings of the third ACM international conference on Web Search and Data Mining. ACM.
West, D.B. 2001. Introduction to graph theory. Vol. 2. Prentice-Hall.
White, D.R. 1980. Structural equivalences in social networks: concepts and measurement of role structures. In: Research Methods in Social Network Analysis Conference, pp. 193–234.
White, D.R. 1984. Regge: a regular graph equivalence algorithm for computing role distances priorto blockmodeling. Unpublished manuscript, University of California, Irvine.
Witten, I.H., Frank, E., and Hall, M.A. 2011. Data Mining: practical machine learning tools and techniques. Morgan Kaufmann.
Xu, R., and Wunsch, D. 2005. Survey of clustering algorithms. IEEE Transactions on Neural Networks, 16(3), 645–678.
Yang, J., and Leskovec, J. 2010. Modeling information diffusion in implicit networks. In: IEEE 10th International Conference on Data Mining.
Young, H.P. 1988. Individual strategy and social structure: an evolutionary theory of institutions. Princeton University Press.
Yule, G.U. 1925. A mathematical theory of evolution, based on the conclusions of Dr. J.C. Willis, FRS. Philosophical Transactions of the Royal Society of London. Series B, Containing Papers of a Biological Character, 213.
Zachary, W.W. 1977. An information flow model for conflict and fission in small groups. Journal of Anthropological Research, 452–473.
Zafarani, Reza, and Liu, Huan. 2009a. Connecting Corresponding Identities across Communities. In: ICWSM.
Zafarani, Reza, and Liu, Huan. 2009b. Social computing data repository at ASU. School ofComputing, Informatics and Decision Systems Engineering, Arizona State University.
Zafarani, Reza, and Liu, Huan. 2013. Connecting users across social media sites: a behavioral-modeling approach. In: Proceedings of the 19th ACM SIGKDD international conference on Knowledge Discovery and Data Mining. KDD.
Zafarani, Reza, Cole, William D., and Liu, Huan. 2010. Sentiment propagation in social networks: a case study in Live Journal. In: Advances in Social Computing. Springer, pp. 413–420.
Zhao, Zheng Alan, and Liu, Huan. 2011. Spectral feature selection for data mining. Chapman & Hall/CRC.

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