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International Workshop on New Frontiers in Mining Complex Patterns

NFMCP 2012: New Frontiers in Mining Complex Patterns pp 200–214Cite as

Supporting Information Spread in a Social Internetworking Scenario

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7765))

Abstract

The problem of quickly, capillary and effectively spreading information over social networks has become extremely important in many areas of our society. This problem has been widely studied in the recent literature and is still open, but it becomes even more challenging, due to the new issues to deal with, in a multi-social-network context, where the possibility that information can cross different social networks has a fundamental role. As a matter of fact, this is the scenario towards which social networks are evolving with a rapid increase of the mutual interaction among them. In this new scenario, called Social Internetworking Scenario (SIS, for short), we propose an approach devoted to favor information spreading, by identifying two stereotypes, specific for SISs, which are expected to be good spreaders: the starter and the bridge.

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References

  1. Anjerani, M., Moeini, A.: Selecting influential nodes for detected communities in real-world social networks. In: Proc. of the Iranian Conference on Electrical Engineering, ICEE 2011, Tehran, Iran, pp. 1–6 (2011)

    Google Scholar 

  2. Ardissono, L., Goy, A., Petrone, G., Segnan, M., Console, L., Lesmo, L., Simone, C., Torasso, P.: Agent technologies for the development of adaptive web stores. In: Sierra, C., Dignum, F.P.M. (eds.) AgentLink 2000. LNCS (LNAI), vol. 1991, pp. 194–213. Springer, Heidelberg (2001)

    Chapter  Google Scholar 

  3. Barthelemy, M., Barrat, A., Pastor-Satorras, R., Vespignani, A.: Velocity and hierarchical spread of epidemic outbreaks in scale-free networks. Physical Review Letters 92, 178701–178704 (2004)

    Article  Google Scholar 

  4. Boguna, M., Pastor-Satorras, R.: Epidemic spreading in correlated complex networks. Physical Review E 66, 047104–047107 (2002)

    Google Scholar 

  5. Boyd, S., Ghosh, A., Prabhakar, B., Shah, D.: Gossip algorithms: Design, analysis and applications. In: Proc. of the International Joint Conference of the IEEE Computer and Communications Societies, INFOCOMM 2005, Miami, FL, USA, vol. 3, pp. 1653–1664 (2005)

    Google Scholar 

  6. Brin, S., Page, L.: The Anatomy of a Large-Scale Hypertextual Web Search Engine. Computer Networks 30(1-7), 107–117 (1998)

    Google Scholar 

  7. Buccafurri, F., Lax, G.: Improving Similarity-Based Methods for Information Propagationon Social Networks. Networked Digital Technologies 87(3), 391–401 (2010)

    Article  Google Scholar 

  8. Burnett, C., Norman, T.J., Sycara, K.: Bootstrapping trust evaluations through stereotypes. In: Proc. of the International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2010, Toronto, Ontario, Canada, pp. 241–248. International Foundation for Autonomous Agents and Multiagent Systems (2010)

    Google Scholar 

  9. Caiv, Y., Chen, Y.: Mining influential bloggers: From general to domain specific. In: Velásquez, J.D., Ríos, S.A., Howlett, R.J., Jain, L.C. (eds.) KES 2009, Part II. LNCS, vol. 5712, pp. 447–454. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  10. Carrington, P., Scott, J., Wasserman, S.: Models and Methods in Social Network Analysis. Cambridge University Press (2005)

    Google Scholar 

  11. Catanzaro, M., Caldarelli, G., Pietronero, L.: Assortative model for social networks. Physical Review E - Statistical, Nonlinear, and Soft Matter Physics 70(3), 037101–037104 (2004)

    Google Scholar 

  12. Cattuto, C., Schmitz, C., Baldassarri, A., Servedio, V.D.P., Loreto, V., Hotho, A., Grahl, M., Stumme, G.: Network properties of folksonomies. Artificial Intelligence Communications 20(4), 245–262 (2007)

    MathSciNet  Google Scholar 

  13. Cha, M., Mislove, A., Gummadi, K.P.: A measurement-driven analysis of information propagation in the flickr social network. In: Proc. of the International Conference on World Wide Web, WWW 2009, Madrid, Spain, pp. 721–730. ACM (2009)

    Google Scholar 

  14. Chou, B.-H., Suzuki, E.: Discovering Community-Oriented Roles of Nodes in a Social Network. In: Bach Pedersen, T., Mohania, M.K., Tjoa, A.M. (eds.) DAWAK 2010. LNCS, vol. 6263, pp. 52–64. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  15. Datta, A., Quarteroni, S., Aberer, K.: Autonomous Gossiping: A Self-Organizing Epidemic Algorithm for Selective Information Dissemination in Wireless Mobile Ad-Hoc Networks. In: Bouzeghoub, M., Goble, C.A., Kashyap, V., Spaccapietra, S. (eds.) ICSNW 2004. LNCS, vol. 3226, pp. 126–143. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

  16. De Meo, P., Nocera, A., Terracina, G., Ursino, D.: Recommendation of similar users, resources and social networks in a Social Internetworking Scenario. Information Sciences 181(7), 1285–1305 (2011)

    Article  Google Scholar 

  17. De Meo, P., Quattrone, G., Ursino, D.: Exploitation of semantic relationships and hierarchical data structures to support a user in his annotation and browsing activities in folksonomies. Information Systems 34(6), 511–535 (2009)

    Article  Google Scholar 

  18. Denzinger, J., Hamdan, J.: Improving Modeling of Other Agents using Tentative Stereotypes and Compactification of Observations. In: Proc. of the International Conference on Intelligent Agent Technology, IAT 2004, Beijing, China, pp. 106–112. IEEE Computer Society (2004)

    Google Scholar 

  19. Freeman, L.C.: A set of measuring centrality based on betweenness. Sociometry 40(1), 35–41 (1977)

    Article  Google Scholar 

  20. Goldenberg, J., Han, S., Lehmann, D.R., Hong, J.W.: The Role of Hubs in the Adoption Process. Journal of Marketing 73, 1–13 (2009)

    Article  Google Scholar 

  21. Goldenberg, J., Libai, E., Muller, E.: Talk of the network: A complex systems look at the underlying process of word-of-mouth. Marketing Letters 12(3), 211–223 (2001)

    Article  Google Scholar 

  22. Gruhl, D., Guha, R., Liben-Nowell, D., Tomkins, A.: Information diffusion through blogspace. In: Proc. of the International Conference on World Wide Web, WWW 2004, pp. 491–501. ACM, New York (2004)

    Google Scholar 

  23. Hamed, A., Arman, M., Ehsan, A.: Towards an Efficient Method for Spreading Information in Social Network. In: Proc. of the Asia International Conference on Modelling & Simulation, Bandung, Bali, Indonesia, pp. 152–157. IEEE Computer Society (2009)

    Google Scholar 

  24. Hamilton, D.L., Trolier, T.K.: Stereotypes and stereotyping: An overview of the cognitive approach. In: Dovidio, J.F., Gaertner, S.L. (eds.) Prejudice, Discrimination, and Racism, pp. 127–163. Academic Press, US (1986)

    Google Scholar 

  25. Khelil, A., Becker, C., Tian, J., Rothermel, K.: An epidemic model for information diffusion in MANETs. In: Proc. of the International Workshop on Modeling Analysis and Simulation of Wireless and Mobile Systems, MSWiM 2002, Atlanta, GA, USA, pp. 54–60. ACM (2002)

    Google Scholar 

  26. Kuflik, T., Shapira, B., Shoval, P.: Stereotype-based versus personal-based filtering rules in information filtering systems. Journal of the American Society for Information Science and Technology 54(3), 243–250 (2003)

    Article  Google Scholar 

  27. Kumar, R., Novak, J., Raghavan, P., Tomkins, A.: On the bursty evolution of blogspace. World Wide Web 8(2), 159–178 (2005)

    Article  Google Scholar 

  28. LaFasto, F.M.J., Larson, C.: When Teams Work Best. Sage Publications, Inc. (2001)

    Google Scholar 

  29. Li, Y.M., Lai, C.Y., Chen, C.W.: Discovering influencers for marketing in the blogosphere. Information Sciences 181(23), 5143–5157 (2011)

    Article  Google Scholar 

  30. Lin, F., Chen, C., Tsai, K.: Discovering Group Interaction Patterns in a Teachers Professional Community. In: Proc. of the Annual Hawaii International Conference on System Sciences, HICSS 2003, Big Island, Hawaii, USA, p. 116. IEEE Computer Society (2003)

    Google Scholar 

  31. Lippmann, W.: Public Opinion. Macmillan (1922)

    Google Scholar 

  32. Monclar, R., Tecla, A., Oliveira, J., de Souza, J.M.: MEK: Using spatial–temporal information to improve social networks and knowledge dissemination. Information Sciences 179(15), 2524–2537 (2009)

    Article  Google Scholar 

  33. Nocera, A., Ursino, D.: PHIS: a system for scouting potential hubs and for favoring their “growth” in a Social Internetworking Scenario. Knowledge-Based Systems (forthcoming)

    Google Scholar 

  34. Rich, E.: User modeling via stereotypes. In: Maybury, M.T., Wahlster, W. (eds.) Readings in Intelligent User Interfaces, pp. 329–342. Morgan Kaufmann Publishers Inc., San Francisco (1998)

    Google Scholar 

  35. Scripps, J., Tan, P.N., Esfahanian, A.H.: Node Roles and Community Structure in Networks. In: Proc. of the International Workshop on Knowledge Discovery on the Web and on Social Network Analysis, WebKDD/SNA-KDD 2007, San Jose, CA, USA, pp. 26–35. ACM (2007)

    Google Scholar 

  36. Shah, D.: Gossip Algorithms. Foundations and Trends® in Networking 3(1), 1–125 (2008)

    Article  MATH  Google Scholar 

  37. Sollenborn, M., Funk, P.: Category-Based Filtering and User Stereotype Cases to Reduce the Latency Problem in Recommender Systems. In: Craw, S., Preece, A.D. (eds.) ECCBR 2002. LNCS (LNAI), vol. 2416, pp. 395–420. Springer, Heidelberg (2002)

    Chapter  Google Scholar 

  38. Wagner, A.R.: Using stereotypes to understand one’s interactive partner. In: Proc. of the International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2010, Toronto, Ontario, Canada, pp. 1445–1446. International Foundation for Autonomous Agents and Multiagent Systems (2010)

    Google Scholar 

  39. Wang, Y., Cong, G., Song, G., Xie, K.: Community-based greedy algorithm for mining top-k influential nodes in mobile social networks. In: Proc. of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, pp. 1039–1048. ACM (2010)

    Google Scholar 

  40. Watts, D.J., Strogatz, S.H.: Collective dynamics of ‘small-world’ networks. Nature 393(6684), 440–442 (1998)

    Article  Google Scholar 

  41. Wong, Y.H., Chan, R.Y.K., Leung, T.K.P.: Managing information diffusion in Internet marketing. European Journal of Marketing 39(7/8), 926–946 (2005)

    Article  Google Scholar 

  42. Wu, H., Zubair, M., Maly, K.: Harvesting social knowledge from folksonomies. In: Proc. of the International Conference on Hypertext and Hypermedia, Hypertext 2006, Odense, Denmark, pp. 111–114. ACM (2006)

    Google Scholar 

  43. Xu, X., Yuruk, N., Feng, Z., Schweiger, T.A.J.: SCAN: a structural clustering algorithm for networks. In: Proc. of the International Conference on Knowledge Discovery and Data Mining, KDD 2007, San Jose, CA, USA, pp. 824–833. ACM (2007)

    Google Scholar 

  44. Yoneki, E., Hui, P., Crowcroft, J.: Distinct Types of Hubs in Human Dynamic Networks. In: Proc. of the International Workshop on Social Network Systems, SNS 2008, Glasgow, Scotland, UK, pp. 7–12. ACM (2008)

    Google Scholar 

  45. Zhang, X., Han, H.: An empirical testing of user stereotypes of information retrieval systems. Journal of Information Processing and Management 41(3), 651–664 (2005)

    Article  Google Scholar 

  46. Zhu, T., Wu, B., Wang, B.: Social Influence and Role Analysis Based on Community Structure in Social Network. In: Huang, R., Yang, Q., Pei, J., Gama, J., Meng, X., Li, X. (eds.) ADMA 2009. LNCS, vol. 5678, pp. 788–795. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

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Author information

Authors and Affiliations

  1. DIMET, University “Mediterranea” of Reggio Calabria, Via Graziella, Località Feo di Vito, 89122, Reggio Calabria, Italy

    Francesco Buccafurri, Gianluca Lax, Antonino Nocera & Domenico Ursino

Authors
  1. Francesco Buccafurri
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  2. Gianluca Lax
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  3. Antonino Nocera
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  4. Domenico Ursino
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Editor information

Editors and Affiliations

  1. Dipartimento di Informatica, Università degli Studi di Bari Aldo Moro, Via Orabona 4, 70125, Bari, Italy

    Annalisa Appice , Michelangelo Ceci  & Corrado Loglisci ,  & 

  2. Institute for High Performance Computing and Networks (ICAR), National Research Council (CNR), Via Pietro Bucci 41C, 87036, Rende, CS, Italy

    Giuseppe Manco  & Elio Masciari  & 

  3. Department of Computer Science, University of North Caroline, 9201 Unviersity City Boulevard, 28223, Charlotte, NC, USA

    Zbigniew W. Ras

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Buccafurri, F., Lax, G., Nocera, A., Ursino, D. (2013). Supporting Information Spread in a Social Internetworking Scenario. In: Appice, A., Ceci, M., Loglisci, C., Manco, G., Masciari, E., Ras, Z.W. (eds) New Frontiers in Mining Complex Patterns. NFMCP 2012. Lecture Notes in Computer Science(), vol 7765. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37382-4_14

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  • DOI: https://doi.org/10.1007/978-3-642-37382-4_14

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-37381-7

  • Online ISBN: 978-3-642-37382-4

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