ParShift: a Python package to study order and differentiation in group conversations
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Data
2023-12-01
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Editora
Elsevier
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
Descrição
SoftwareX
Palavras-chave
GRUPOS, GROUPS, INTERAÇÃO SOCIAL, SOCIAL INTERACTION, COMPORTAMENTO SOCIAL, SOCIAL BEHAVIOUR, INFORMÁTICA, COMPUTER SCIENCE
Citação
Ferreira-Saraiva, B.D., Matos-Carvalho, J.P., Fachada, N. & Pita, M. (2023). ParShift: a Python package to study order and differentiation in group conversations. SoftwareX, 24. 101554. https://doi.org/10.1016/j.softx.2023.101554