Resumo

Collective organization in multi-party conversations emerges through the exchange of utterances between participants. While most research has focused on content-centred mechanisms that lead to emergent conversational coordination, less attention has been given to explaining conversational order based on who is addressed and who responds, especially when dealing with large conversational datasets. In this paper, we introduce a Python library, ParShift, that implements a state-of-the-art theoretical quantitative framework known as Participation Shifts. This framework enables researchers to study participant-centred order and differentiation in multi-party conversations. With ParShift, researchers can characterize conversations by quantifying the probabilities of events related to how people address each other during conversations. This library is particularly useful for studying conversation threads in social networks, parliamentary debates, team meetings, or student debates on a large scale. Keywords: Small groups Social interaction Participation shifts Interpersonal coordination Turn-taking Emergent social behaviour
Idioma originalInglês
Número do artigo101554
RevistaSoftwareX
Volume24
DOIs
Estado da publicaçãoPublicadas - 1 dez. 2023

Nota bibliográfica

SoftwareX

Financiamento

Financiadoras/-esNúmero do financiador
Fundação para a Ciência e a TecnologiaDSAIPA/DS/0102/2019

    Keywords

    • GRUPOS
    • INTERAÇÃO SOCIAL
    • COMPORTAMENTO SOCIAL
    • INFORMÁTICA

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