Topical Alignment in Online Social Systems

Maciel Cardoso, F. (Universidad de Zaragoza) ; Meloni, S. ; Santanche, A. ; Moreno, Y. (Universidad de Zaragoza)

Resumen: 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.

Idioma: Inglés

DOI: 10.3389/fphy.2019.00058

Año: 2019

Publicado en: FRONTIERS IN PHYSICS 7 (2019), 58 [12 pp]
ISSN: 2296-424X

Factor impacto JCR: 2.638 (2019)

Categ. JCR: PHYSICS, MULTIDISCIPLINARY rank: 30 / 84 = 0.357 (2019) - Q2 - T2

Factor impacto SCIMAGO: 0.597 - Mathematical Physics (Q2) - Materials Science (miscellaneous) (Q2) - Physics and Astronomy (miscellaneous) (Q2) - Physical and Theoretical Chemistry (Q2) - Biophysics (Q3)

Financiación: info:eu-repo/grantAgreement/EC/FP7/317532/EU/Foundational Research on MULTIlevel comPLEX networks and systems/MULTIPLEX
Financiación: info:eu-repo/grantAgreement/ES/MINECO/FIS2017-87519-P
Financiación: info:eu-repo/grantAgreement/ES/MINECO/MDM-2017-0711

Tipo y forma: Artículo (Versión definitiva)

Área (Departamento): Área Física Teórica (Dpto. Física Teórica)