2012/11/01 by Bogdan Gliwa, Anna Zygmunt, Aleksander Byrski · 7 citations
Computer Science · Physics and Astronomy · Psychology · #Artificial intelligence #Benchmark (surveying) #Complex Network Analysis Techniques #Computer science #Data Visualization and Analytics #Data mining #Data science #Dynamics (music) #Group (periodic table) #Human–computer interaction #Opinion Dynamics and Social Influence #Psychology #Qualitative analysis #Qualitative research #Scale (ratio) #Social dynamics #Social media #Social network analysis #World Wide Web #cs.SI #physics.soc-ph
paper · pdf · doi:10.1109/cason.2012.6412375
Fourth International Conference on Computational Aspects of Social Networks, CASoN 2012, Sao Carlos, Brazil, November 21-23, 2012, pp. 41-46; IEEE Computer Society, 2012
openalex publication_date 2012/11/01 · arxiv created 2013/07/23 · arxiv updated 2013/07/24 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
Identifying communities in social networks becomes an increasingly important research problem. Several methods for identifying such groups have been developed, however, qualitative analysis (taking into account the scale of the problem) still poses serious problems. This paper describes a tool for facilitating such an analysis, allowing to visualize the dynamics and supporting localization of different events (such as creation or merging of groups). In the final part of the paper, the experimental results performed using the benchmark data (Enron emails) provide an insight into usefulness of the proposed tool.