Articles producció científica> Enginyeria Informàtica i Matemàtiques

Characterizing interactions in online social networks during exceptional events

  • Identification data

    Identifier: imarina:3654403
    Authors:
    Omodei, ElisaDe Domenico, ManlioArenas, Alex
    Abstract:
    Nowadays, millions of people interact on a daily basis on online social media like Facebook and Twitter, where they share and discuss information about a wide variety of topics. In this paper, we focus on a specific online social network, Twitter, and we analyze multiple datasets each one consisting of individuals' online activity before, during and after an exceptional event in terms of volume of the communications registered. We consider important events that occurred in different arenas that range from policy to culture or science. For each dataset, the users' online activities are modeled by a multilayer network in which each layer conveys a different kind of interaction, specifically: retweeting, mentioning and replying. This representation allows us to unveil that these distinct types of interaction produce networks with different statistical properties, in particular concerning the degree distribution and the clustering structure. These results suggests that models of online activity cannot discard the information carried by this multilayer representation of the system, and should account for the different processes generated by the different kinds of interactions. Secondly, our analysis unveils the presence of statistical regularities among the different events, suggesting that the non-trivial topological patterns that we observe may represent universal features of the social dynamics on online social networks during exceptional events.
  • Others:

    Author, as appears in the article.: Omodei, Elisa; De Domenico, Manlio; Arenas, Alex;
    Department: Enginyeria Informàtica i Matemàtiques
    URV's Author/s: Arenas Moreno, Alejandro / DE DOMENICO, MANLIO
    Keywords: Social networks Multilayer Exceptional events Complex networks Big data
    Abstract: Nowadays, millions of people interact on a daily basis on online social media like Facebook and Twitter, where they share and discuss information about a wide variety of topics. In this paper, we focus on a specific online social network, Twitter, and we analyze multiple datasets each one consisting of individuals' online activity before, during and after an exceptional event in terms of volume of the communications registered. We consider important events that occurred in different arenas that range from policy to culture or science. For each dataset, the users' online activities are modeled by a multilayer network in which each layer conveys a different kind of interaction, specifically: retweeting, mentioning and replying. This representation allows us to unveil that these distinct types of interaction produce networks with different statistical properties, in particular concerning the degree distribution and the clustering structure. These results suggests that models of online activity cannot discard the information carried by this multilayer representation of the system, and should account for the different processes generated by the different kinds of interactions. Secondly, our analysis unveils the presence of statistical regularities among the different events, suggesting that the non-trivial topological patterns that we observe may represent universal features of the social dynamics on online social networks during exceptional events.
    Thematic Areas: Physics, multidisciplinary Physics and astronomy (miscellaneous) Physics and astronomy (all) Physical and theoretical chemistry Mathematical physics Materials science (miscellaneous) General physics and astronomy Biophysics
    licence for use: https://creativecommons.org/licenses/by/3.0/es/
    Author's mail: alexandre.arenas@urv.cat
    Author identifier: 0000-0003-0937-0334
    Record's date: 2024-09-28
    Papper version: info:eu-repo/semantics/publishedVersion
    Link to the original source: https://www.frontiersin.org/articles/10.3389/fphy.2015.00059/full
    Licence document URL: https://repositori.urv.cat/ca/proteccio-de-dades/
    Papper original source: Frontiers In Physics. 3 (59):
    APA: Omodei, Elisa; De Domenico, Manlio; Arenas, Alex; (2015). Characterizing interactions in online social networks during exceptional events. Frontiers In Physics, 3(59), -. DOI: 10.3389/fphy.2015.00059
    Article's DOI: 10.3389/fphy.2015.00059
    Entity: Universitat Rovira i Virgili
    Journal publication year: 2015
    Publication Type: Journal Publications
  • Keywords:

    Biophysics,Materials Science (Miscellaneous),Mathematical Physics,Physical and Theoretical Chemistry,Physics and Astronomy (Miscellaneous),Physics, Multidisciplinary
    Social networks
    Multilayer
    Exceptional events
    Complex networks
    Big data
    Physics, multidisciplinary
    Physics and astronomy (miscellaneous)
    Physics and astronomy (all)
    Physical and theoretical chemistry
    Mathematical physics
    Materials science (miscellaneous)
    General physics and astronomy
    Biophysics
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