Topical Alignment in Online Social Systems

Author(s)

Maciel Cardoso, Felipe ^{[1, 2]} ; Meloni, Sandro ^{[2, 3]} ; Santanche, Andre ^[1] ; Moreno, Yamir ^{[2, 4, 5]}

Affiliation

^[1] Univ Estadual Campinas, Inst Comp, Campinas, SP - Brazil

^[2] Univ Zaragoza, Inst Biocomputat & Phys Complex Syst, Zaragoza - Spain

^[3] UIB, CSIC, Inst Cross Disciplinary Phys & Complex Syst, IFISC, Palma de Mallorca - Spain

^[4] Univ Zaragoza, Dept Theoret Phys, Zaragoza - Spain

^[5] ISI Fdn, Turin - Italy

• Document type: Journal article
• Source: FRONTIERS IN PHYSICS; v. 7, APR 17 2019.
• Web of Science Citations: 0

Abstract

Understanding the dynamics of social interactions is crucial to comprehend human behavior. The emergence of online social media has enabled access to data regarding people relationships at a large scale. Twitter, specifically, is an information oriented network, with users sharing and consuming information. In this work, we study whether users tend to be in contact with people interested in similar topics, i.e., if they are topically aligned. To do so, we propose an approach based on the use of hashtags to extract information topics from Twitter messages and model users' interests. Our results show that, on average, users are connected with other users similar to them. Furthermore, we show that topical alignment provides interesting information that can eventually allow inferring users' connectivity. Our work, besides providing a way to assess the topical similarity of users, quantifies topical alignment among individuals, contributing to a better understanding of how complex social systems are structured. (AU)

• FAPESP's process: 15/01587-0 - Storage, modeling and analysis of dynamical systems for e-Science applications
• Grantee: João Eduardo Ferreira
• Support Opportunities: Research Grants - eScience and Data Science Program - Thematic Grants