Visual analytics of social networks: mining and visualizing co-authorship networks

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 6780 LNAI, Issue , 2011, Pages 335-345

  Leung, Carson Kai Sang ^a   Carmichael, Christopher L ^a   Teh, Eu Wern ^a  

^a UNIVERSITY OF MANITOBA   (Canada)

Author keywords

augmented cognition; data mining; data visualization; frequent patterns; Human computer interaction; information and knowledge visualization; social computing; social information; social network analysis and mining; visualizing social interaction

Indexed keywords

AUGMENTED COGNITION; FREQUENT PATTERNS; HUMAN-COMPUTER; KNOWLEDGE VISUALIZATION; SOCIAL COMPUTING; SOCIAL INFORMATION; SOCIAL INTERACTIONS; SOCIAL NETWORK ANALYSIS; SOCIAL NETWORK ANALYSIS AND MININGS;

ADAPTIVE SYSTEMS; COGNITIVE SYSTEMS; DATA VISUALIZATION; ELECTRIC NETWORK ANALYSIS; HUMAN COMPUTER INTERACTION; KNOWLEDGE MANAGEMENT; SOCIAL NETWORKING (ONLINE); VISUALIZATION; SOCIAL ASPECTS; SOCIAL SCIENCES COMPUTING;

DATA MINING;

EID: 79960301265     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-21852-1_40     Document Type: Conference Paper

References (25)

1. Adams, R., Gill, S.P.: Augmented cognition, universal access and social intelligence in the information society. In: Schmorrow, D.D., Reeves, L.M. (eds.) FAC 2007, HCII 2007. LNCS (LNAI), vol. 4565, pp. 231-240. Springer, Heidelberg (2007)
2. Agrawal, R., Imielinski, T., Swami, A.N.: Mining association rules between sets of items in large databases. In: ACM SIGMOD 1993, pp. 207-216 (1993)
3. Benchettara, N., Kanawati, R., Rouveirol, C.: Supervised machine learning applied to link prediction in bipartite social networks. In: ASONAM 2010, pp. 326-330 (2010)
4. Biryukov, M.: Co-author network analysis in DBLP: classifying personal names. In: MCO 2008. CCIS, vol. 14, pp. 399-408. Springer, Heidelberg (2008)
5. Blanchard, J., Guillet, F., Briand, H.: Interactive visual exploration of association rules with rule-focusing methodology. KAIS 13(1), 43-75 (2007)
6. Carmichael, C.L., Leung, C.K.-S.: CloseViz: visualizing useful patterns. In: ACM UP 2010, pp. 17-26 (2010)
7. Carrington, P.J., Scott, J., Wasserman, S. (eds.): Models and Methods in Social Network Analysis. Cambridge University Press, Cambridge (2005)
8. Chi, E.H.: Augmented social cognition: using social web technology to enhance the ability of groups to remember, think, and reason. In: ACM SIGMOD 2009, pp. 973-984 (2009)
9. Goyal, A., Bonchi, F., Lakshmanan, L.V.S.: Learning influence probabilities in social networks. In: ACM WSDM 2010, pp. 241-250 (2010)
10. Han, J., Pei, J., Yin, Y., Mao, R.: Mining frequent patterns without candidate generation: a frequent-pattern tree approach. Data Mining and Knowledge Discovery 8(1), 53-87 (2004)
11. Han, Y., Zhou, B., Pei, J., Jia, Y.: Understanding importance of collaborations in coauthorship networks: a supportiveness analysis approach. In: SDM 2009, pp. 1111-1122 (2009)
12. Hansen, D.L., Shneiderman, B., Smith, M.A.: Analyzing Social Media Networks with NodeXL. Morgan Kaufmann, Burlington, MA (2011)
13. Lakshmanan, L.V.S., Leung, C.K.-S., Ng, R.T.: Efficient dynamic mining of constrained frequent sets. ACM TODS 28(4), 337-389 (2003)
14. Leung, C.K.-S., Carmichael, C.L.: FpVAT: a visual analytic tool for supporting frequent pattern mining. SIGKDD Explorations 11(2), 39-48 (2009)
15. Leung, C.K.-S., Carmichael, C.L.: Exploring social networks: a frequent pattern visualization approach. In: IEEE SocialCom 2010, pp. 419-424 (2010)
16. Leung, C.K.-S., Irani, P.P., Carmichael, C.L.: FIsViz: a frequent itemset visualizer. In: Washio, T., Suzuki, E., Ting, K.M., Inokuchi, A. (eds.) PAKDD 2008. LNCS (LNAI), vol. 5012, pp. 644-652. Springer, Heidelberg (2008)
17. Leung, C.K.-S., Irani, P.P., Carmichael, C.L.: WiFIsViz: effective visualization of frequent itemsets. In: IEEE ICDM 2008, pp. 875-880 (2008)
18. Leung, C.K.-S., Khan, Q.I., Li, Z., Hoque, T.: CanTree: a canonical-order tree for incremental frequent-pattern mining. KAIS 11(3), 287-311 (2007)
19. Lévy, P.: Toward a self-referential collective intelligence some philosophical background of the IEML research program. In: Nguyen, N.T., Kowalczyk, R., Chen, S.-M. (eds.) ICCCI 2009. LNCS (LNAI), vol. 5796, pp. 22-35. Springer, Heidelberg (2009)
20. Makanju, A., Brooks, S., Zincir-Heywood, A.N., Milios, E.E.: LogView: visualizing event log clusters. In: PST 2008, pp. 99-108 (2008)
21. Milani Fard, A., Ester, M.: Collaborative mining in multiple social networks data for criminal group discovery. In: IEEE SocialCom 2009, pp. 582-587 (2009)
22. Misue, K.: Visual analysis tool for bipartite networks. In: Lovrek, I., Howlett, R.J., Jain, L.C. (eds.) KES 2008, Part II. LNCS (LNAI), vol. 5178, pp. 871-878. Springer, Heidelberg (2008)
23. Ugai, T., Aoyama, K.: Organization diagnosis tools based on social network analysis. In: Smith, M.J., Salvendy, G. (eds.) Human Interface 2009, Part I, HCII 2009. LNCS, vol. 5617, pp. 181-189. Springer, Heidelberg (2009)
24. van Ham, F., Schulz, H.-J., DiMicco, J.M.: Honeycomb: visual analysis of large scale social networks. In: Gross, T., Gulliksen, J., Kotzé, P., Oestreicher, L., Palanque, P., Prates, R.O., Winckler, M. (eds.) INTERACT 2009, Part II . LNCS, vol. 5727, pp. 429-442. Springer, Heidelberg (2009)
25. Wasserman, S., Faust, K.: Social Network Analysis: Methods and Applications. Cambridge University Press, Cambridge (1994)