Files and links (1)
Published, Version of Record (VoR)Open Access via Drexel Libraries Read and Publish Program 2024CC BY V4.0, Open
Journal article
Structural balance in real-world social networks: incorporating direction and transitivity in measuring partial balance
Social network analysis and mining, v 14(168)
22 Aug 2024
Featured in Collection : Research Supported by Drexel Libraries' OA Programs
Abstract
Structural balance theory predicts that triads in networks gravitate towards stable configurations. This theory has been verified for undirected graphs. Since real-world networks are often directed, we introduce a novel method for considering both transitivity and sign consistency for evaluating partial balance in signed digraphs. We test our approach on graphs constructed by using different methods for identifying edge signs: natural language processing to infer signs from underlying text data, and self-reported survey data. Our results show that for various social contexts and edge sign detection methods, partial balance of these digraphs is moderately high, ranging from 61 to 96%. Our approach not only enhances the theoretical framework of structural balance but also provides practical insights into the stability of social networks, enabling a deeper understanding of interpersonal and group dynamics across different communication platforms.
Metrics
Details
- Title
- Structural balance in real-world social networks: incorporating direction and transitivity in measuring partial balance
- Creators
- Rezvaneh Rezapour (Corresponding Author) - Drexel University, Information ScienceLy Dinh - University of Illinois Urbana-ChampaignLan JiangJana Diesner - University of Illinois Urbana-Champaign
- Publication Details
- Social network analysis and mining, v 14(168)
- Publisher
- Springer Nature
- Number of pages
- 13
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Information Science
- Web of Science ID
- WOS:001296569400001
- Scopus ID
- 2-s2.0-85201819853
- Other Identifier
- 991021897111704721
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Collaboration types
- Domestic collaboration
- International collaboration
- Web of Science research areas
- Computer Science, Information Systems