TY - JOUR
T1 - ParShift: a Python package to study order and differentiation in group conversations
AU - Carvalho, João P. Matos
AU - Fachada, Nuno
AU - Pita, Manuel Arturo Marques
AU - Saraiva, Bruno David Ferreira
AU - Matos-Carvalho, João Pedro
N1 - SoftwareX
PY - 2023/12/1
Y1 - 2023/12/1
N2 - 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
AB - 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
KW - GRUPOS
KW - INTERAÇÃO SOCIAL
KW - COMPORTAMENTO SOCIAL
KW - INFORMÁTICA
KW - GROUPS
KW - SOCIAL INTERACTION
KW - SOCIAL BEHAVIOUR
KW - COMPUTER SCIENCE
UR - http://hdl.handle.net/10437/14288
U2 - 10.1016/j.softx.2023.101554
DO - 10.1016/j.softx.2023.101554
M3 - Article
SN - 2352-7110
VL - 24
JO - SoftwareX
JF - SoftwareX
M1 - 101554
ER -