Abstract

In this paper, we use signed bipartite graphs to model opinions expressed by one type of entities (e.g., individuals, organizations) about another (e.g., political issues, religious beliefs), and based on the strength of that opinion, partition both types of entities into two clusters. The clustering is done in such a way that support for the second type of entity by the first within a cluster is high and across the cluster is low. We develop an automated partitioning tool that can be used to classify individuals and/or organizations into two disjoint groups based on their beliefs, practices and expressed opinions.

Original languageEnglish (US)
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages196-204
Number of pages9
Volume7227 LNCS
DOIs
StatePublished - 2012
Event5th International Conference on Social Computing, Behavioral-Cultural Modeling and Prediction, SBP 2012 - College Park, MD, United States
Duration: Apr 3 2012Apr 5 2012

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7227 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other5th International Conference on Social Computing, Behavioral-Cultural Modeling and Prediction, SBP 2012
CountryUnited States
CityCollege Park, MD
Period4/3/124/5/12

Fingerprint

Signed Graph
Bipartite Graph
Partitioning
Disjoint
Classify
Partition
Clustering
Beliefs
Model

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Banerjee, S., Sarkar, K., Gokalp, S., Sen, A., & Davulcu, H. (2012). Partitioning signed bipartite graphs for classification of individuals and organizations. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7227 LNCS, pp. 196-204). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7227 LNCS). https://doi.org/10.1007/978-3-642-29047-3_24

Partitioning signed bipartite graphs for classification of individuals and organizations. / Banerjee, Sujogya; Sarkar, Kaushik; Gokalp, Sedat; Sen, Arunabha; Davulcu, Hasan.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 7227 LNCS 2012. p. 196-204 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7227 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Banerjee, S, Sarkar, K, Gokalp, S, Sen, A & Davulcu, H 2012, Partitioning signed bipartite graphs for classification of individuals and organizations. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 7227 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 7227 LNCS, pp. 196-204, 5th International Conference on Social Computing, Behavioral-Cultural Modeling and Prediction, SBP 2012, College Park, MD, United States, 4/3/12. https://doi.org/10.1007/978-3-642-29047-3_24
Banerjee S, Sarkar K, Gokalp S, Sen A, Davulcu H. Partitioning signed bipartite graphs for classification of individuals and organizations. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 7227 LNCS. 2012. p. 196-204. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-642-29047-3_24
Banerjee, Sujogya ; Sarkar, Kaushik ; Gokalp, Sedat ; Sen, Arunabha ; Davulcu, Hasan. / Partitioning signed bipartite graphs for classification of individuals and organizations. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 7227 LNCS 2012. pp. 196-204 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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