Extração de Conhecimento e Análise Visual de Redes Sociais
Resumo
Uma rede social é um grafo onde pessoas ou organizações (dependendo da aplicação) são representadas por nodos conectados por arestas as quais podem corresponder tanto a fortes relacionamentos sociais como ao compartilhamento de alguma característica. A análise da estrutura desse grafo, assim como a análise estatística dos atributos dos nodos e/ou das arestas pode revelar indivíduos/organizações importantes, relacionamentos especiais e grupos. Enquanto novas informações continuam a ser coletadas e armazenadas, e o tamanho e a complexidade dos grafos semânticos sobrepujam a capacidade cognitiva humana, é necessário melhorar a habilidade de analisar tais volumes de dados. Este artigo focaliza a análise da informação presente nas redes sociais, a extração de conhecimento a partir de grafos e a visualização de fatos decorrentes dessa análise.
Referências
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Araújo, R. M., e Lamb, L. C. (2007) “An Information-Theoretic Analysis of Memory Bounds in a Distributed Resource Allocation Mechanism”. In Proc. of Intl. Joint Conf. on Artificial Intelligence IJCAI-07, pp. 212-217. AAAI Press.
Araújo, R. M., e Lamb, L. C. (2008) “Distributed Problem Solving by Memetic Networks”. In Proc. of GECCO 2008, to appear.
Barabasi, A.-L. (2003) “Linked: How Everything Is Connected to Everything Else and What It Means for Business, Science, and Everyday Life”. Plume Books.
Battista, G., Eades, P., Tamassia, R. e Tollis, I.G. (1999) “Graph Drawing: Algorithms for the Visualization of Graphs”. New Jersey: Prentice Hall.
Bertin, J. (1983) “Semiology of Graphics”, University of Wisconsin Press.
Day, G. S. e Wensley, R. (1988) “Assessing advantage: a framework for diagnosing competitive superiority”. Journal of Marketing, p. 1-20, V.52, n.1.
DBLP: Digital bibliography and library project, [link], 2007.
Degenne, A. e Forse, M. (1999) “Introducing Social Networks”. Sage Publications.
The Economist (2006) "Artificial artificial intelligence", London, 8 June.
Elmqvist, N., Henry, N., Richie, Y., Fekete, J-D (2008). “ Melange: Space folding for multifocus interaction”. In ACM SIGCHI, New York. ACM.
Erdös, P. e Rényi, A. (1960). “On the evolution of random graphs”. In Publ. Math. Inst. Hungar. Acad. Sci., pages 17–61.
Fayyad, U. M., Piatetsky-Shapiro, G., Smyth, P. (1996) “From Data Mining to Knowledge Discovery: An Overview”. In: Fayyad, U. M. et al. Advances in Knowledge Discovery and Data Mining. Menlo Park: AAAI Press. 611p. p.11-34.
Florescu, D. e Kossmann, D. (1999) “Storing and Querying XML Data using an RDBMS”. IEEE Data Engineering Bulletin, 22(3), 27-34.
Fruchterman, T.M.J. e Reingold, E.M. (1991). "Graph Drawing by Force–Directed Placement". Software - Practice & Experience, 21 (Nov), 1129–1164
Freitas, C.M.D.S. (2007) “Visualização de Informações e a Convergência de Técnicas de Computação Gráfica e Interação Humano-Computador”. In: Kowaltowski, T. e Breitman, K. (org.) Atualizações em Informática. Rio de Janeiro, PUC-Rio/SBC.
van Ham, F. (2005) “Interactive Visualization of Large Graphs”. PhD Thesis,Technische Universiteit Eindhoven, ISBN 90-386-0704-0
Han, J. e Kamber, M. (2006) “Data Mining: concepts and Techniques”. Morgan Kaufmann, Second Edition. 600p.
Henry, N., e Fekete, J.-D. (2006) “MatrixExplorer: a dual-representation system to explore social networks". IEEE Trans. on Visualization & Computer Graphics, 12(5): 677-684.
Henry, N. e Fekete, J.-D. (2007) “Nodetrix: Hybrid representation for analyzing social networks”. IEEE Transactions on Visualization & Computer Graphics, 13(6): 1302-1309.
Herman, I, Melançon, G. e Marshall, M.S. (2000) “Graph Visualization and Navigation in Information Visualization: A Survey”. IEEE Transactions on Visualization & Computer Graphics, 6(1):24-42.
Jagadish, H. V. et al. (2002). “TIMBER: A native XML database”. VLDB Journal, 11(4):274-291.
John, G. H. (1997) “Enhancements to the Data Mining Process”. Stanford Univ., Ph.D. Thesis.
Kumar, G. e Garland, M. (2006a). “Visual exploration of complex time-varying graphs”. IEEE Transactions on Visualization & Computer Graphics, 12(5):805–812.
Kumar, K., Novak, J., e Tomkins, A. (2006b) “Structure and evolution of online social networks”. In Proc. of ACM SIGKDD Intl. Conf. on Knowledge Discovery and Data Mining, p. 611-617, New York.
Laender, A. H. F.; Gonçalves, M. A.; Roberto, P. A. (2004) “BDBComp: building a digital library for the Brazilian computer science community”. In: 4th ACM/IEEE-CS Joint Conf. on Digital Libraries, New York, NY, USA. p. 23–24.
Nascimento, H.A.D e Ferreira, C.B.R. (2005) “Visualização de Informações – Uma Abordagem Prática”. In Anais do XXV Congresso da Soc. Bras. de Computação, pp. 1262-1311.
Nooy, W. de, Mrvar, A. e Batagelj, V. (2005) “Exploratory Social Network Analysis with Pajek” (Structural Analysis in the Social Sciences). Cambridge University Press.
Roffilli, M. e Lomi, A. (2006), "Identifying and classifying social groups: A machine learning approach", in Data Science and Classification, V.Batagelj, H.-H.Bock, A.Ferligoj, A.Ziberna (Editors). Springer.
Sindre, G., Gulla, B. e Jokstad, H. G. (1993). “Onion graphs: aesthetics and layout”. In VL, pages 287–291.
Shinoda, K., Matsuo, Y. e Nakashima, H. (2007). “Emergence of Global Network Property Based on Multi-Agent Voting Model”. In Proc. AAMAS2007, ACM Press.
Spritzer, A.S. e Freitas, C.M.D.S. (2008) "A Physics-based Approach for Interactive Manipulation of Graph Visualizations". Proc. Intl. Conf. on Advanced Visual Interfaces, AVI 2008, Napoli.
Ware, C. (2001) “Information Visualization: Perception for Design”, San Francisco, Morgan Kaufmann.
Wasserman, S. e Faust, K. (1994) “Social network analysis: methods and applications”, vol. 8 of Structural analysis in the social sciences. Cambridge Univ. Press, Cambridge.
Wattenberg, M. (2006) “Visual exploration of multivariate graphs”. In Proc. of SIGCHI Conf. Human Factors in Computing Systems, p. 811–819, New York. ACM.
Watts, D. J. (2003) “Six Degrees: The Science of a Connected Age”. W.W. Norton & Company.
Zhou, M. e Feiner, S. K. (1998) "Visual Task Characterization for Automated Visual Discourse Synthesis". Proc. CHI’98 Conference, ACM Press, pp. 392-399.
Araújo, R. M., e Lamb, L. C. (2007) “An Information-Theoretic Analysis of Memory Bounds in a Distributed Resource Allocation Mechanism”. In Proc. of Intl. Joint Conf. on Artificial Intelligence IJCAI-07, pp. 212-217. AAAI Press.
Araújo, R. M., e Lamb, L. C. (2008) “Distributed Problem Solving by Memetic Networks”. In Proc. of GECCO 2008, to appear.
Barabasi, A.-L. (2003) “Linked: How Everything Is Connected to Everything Else and What It Means for Business, Science, and Everyday Life”. Plume Books.
Battista, G., Eades, P., Tamassia, R. e Tollis, I.G. (1999) “Graph Drawing: Algorithms for the Visualization of Graphs”. New Jersey: Prentice Hall.
Bertin, J. (1983) “Semiology of Graphics”, University of Wisconsin Press.
Day, G. S. e Wensley, R. (1988) “Assessing advantage: a framework for diagnosing competitive superiority”. Journal of Marketing, p. 1-20, V.52, n.1.
DBLP: Digital bibliography and library project, [link], 2007.
Degenne, A. e Forse, M. (1999) “Introducing Social Networks”. Sage Publications.
The Economist (2006) "Artificial artificial intelligence", London, 8 June.
Elmqvist, N., Henry, N., Richie, Y., Fekete, J-D (2008). “ Melange: Space folding for multifocus interaction”. In ACM SIGCHI, New York. ACM.
Erdös, P. e Rényi, A. (1960). “On the evolution of random graphs”. In Publ. Math. Inst. Hungar. Acad. Sci., pages 17–61.
Fayyad, U. M., Piatetsky-Shapiro, G., Smyth, P. (1996) “From Data Mining to Knowledge Discovery: An Overview”. In: Fayyad, U. M. et al. Advances in Knowledge Discovery and Data Mining. Menlo Park: AAAI Press. 611p. p.11-34.
Florescu, D. e Kossmann, D. (1999) “Storing and Querying XML Data using an RDBMS”. IEEE Data Engineering Bulletin, 22(3), 27-34.
Fruchterman, T.M.J. e Reingold, E.M. (1991). "Graph Drawing by Force–Directed Placement". Software - Practice & Experience, 21 (Nov), 1129–1164
Freitas, C.M.D.S. (2007) “Visualização de Informações e a Convergência de Técnicas de Computação Gráfica e Interação Humano-Computador”. In: Kowaltowski, T. e Breitman, K. (org.) Atualizações em Informática. Rio de Janeiro, PUC-Rio/SBC.
van Ham, F. (2005) “Interactive Visualization of Large Graphs”. PhD Thesis,Technische Universiteit Eindhoven, ISBN 90-386-0704-0
Han, J. e Kamber, M. (2006) “Data Mining: concepts and Techniques”. Morgan Kaufmann, Second Edition. 600p.
Henry, N., e Fekete, J.-D. (2006) “MatrixExplorer: a dual-representation system to explore social networks". IEEE Trans. on Visualization & Computer Graphics, 12(5): 677-684.
Henry, N. e Fekete, J.-D. (2007) “Nodetrix: Hybrid representation for analyzing social networks”. IEEE Transactions on Visualization & Computer Graphics, 13(6): 1302-1309.
Herman, I, Melançon, G. e Marshall, M.S. (2000) “Graph Visualization and Navigation in Information Visualization: A Survey”. IEEE Transactions on Visualization & Computer Graphics, 6(1):24-42.
Jagadish, H. V. et al. (2002). “TIMBER: A native XML database”. VLDB Journal, 11(4):274-291.
John, G. H. (1997) “Enhancements to the Data Mining Process”. Stanford Univ., Ph.D. Thesis.
Kumar, G. e Garland, M. (2006a). “Visual exploration of complex time-varying graphs”. IEEE Transactions on Visualization & Computer Graphics, 12(5):805–812.
Kumar, K., Novak, J., e Tomkins, A. (2006b) “Structure and evolution of online social networks”. In Proc. of ACM SIGKDD Intl. Conf. on Knowledge Discovery and Data Mining, p. 611-617, New York.
Laender, A. H. F.; Gonçalves, M. A.; Roberto, P. A. (2004) “BDBComp: building a digital library for the Brazilian computer science community”. In: 4th ACM/IEEE-CS Joint Conf. on Digital Libraries, New York, NY, USA. p. 23–24.
Nascimento, H.A.D e Ferreira, C.B.R. (2005) “Visualização de Informações – Uma Abordagem Prática”. In Anais do XXV Congresso da Soc. Bras. de Computação, pp. 1262-1311.
Nooy, W. de, Mrvar, A. e Batagelj, V. (2005) “Exploratory Social Network Analysis with Pajek” (Structural Analysis in the Social Sciences). Cambridge University Press.
Roffilli, M. e Lomi, A. (2006), "Identifying and classifying social groups: A machine learning approach", in Data Science and Classification, V.Batagelj, H.-H.Bock, A.Ferligoj, A.Ziberna (Editors). Springer.
Sindre, G., Gulla, B. e Jokstad, H. G. (1993). “Onion graphs: aesthetics and layout”. In VL, pages 287–291.
Shinoda, K., Matsuo, Y. e Nakashima, H. (2007). “Emergence of Global Network Property Based on Multi-Agent Voting Model”. In Proc. AAMAS2007, ACM Press.
Spritzer, A.S. e Freitas, C.M.D.S. (2008) "A Physics-based Approach for Interactive Manipulation of Graph Visualizations". Proc. Intl. Conf. on Advanced Visual Interfaces, AVI 2008, Napoli.
Ware, C. (2001) “Information Visualization: Perception for Design”, San Francisco, Morgan Kaufmann.
Wasserman, S. e Faust, K. (1994) “Social network analysis: methods and applications”, vol. 8 of Structural analysis in the social sciences. Cambridge Univ. Press, Cambridge.
Wattenberg, M. (2006) “Visual exploration of multivariate graphs”. In Proc. of SIGCHI Conf. Human Factors in Computing Systems, p. 811–819, New York. ACM.
Watts, D. J. (2003) “Six Degrees: The Science of a Connected Age”. W.W. Norton & Company.
Zhou, M. e Feiner, S. K. (1998) "Visual Task Characterization for Automated Visual Discourse Synthesis". Proc. CHI’98 Conference, ACM Press, pp. 392-399.
Publicado
12/07/2008
Como Citar
FREITAS, Carla M. D. S. et al.
Extração de Conhecimento e Análise Visual de Redes Sociais. In: SEMINÁRIO INTEGRADO DE SOFTWARE E HARDWARE (SEMISH), 35. , 2008, Belém/PA.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2008
.
p. 106-120.
ISSN 2595-6205.
