Artículo
Strength in coalitions: Community detection through argument similarity
Budan, Paola Daniela
; Escañuela Gonzalez, Melisa Gisselle
; Budan, Maximiliano Celmo David
; Martinez, Maria Vanina
; Simari, Guillermo Ricardo
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Fecha de publicación:
12/2022
Editorial:
IOS Press
Revista:
Argument and Computation
ISSN:
1946-2166
e-ISSN:
1946-2174
Idioma:
Inglés
Tipo de recurso:
Artículo publicado
Clasificación temática:
Resumen
We present a novel argumentation-based method for finding and analyzing communities in social media on the Web, where a community is regarded as a set of supported opinions that might be in conflict. Based on their stance, we identify argumentative coalitions to define them; then, we apply a similarity-based evaluation method over the set of arguments in the coalition to determine the level of cohesion inherent to each community, classifying them appropriately. Introducing conflict points and attacks between coalitions based on argumentative (dis)similarities to model the interaction between communities leads to considering a meta-argumentation framework where the set of coalitions plays the role of the set of arguments and where the attack relation between the coalitions is assigned a particular strength which is inherited from the arguments belonging to the coalition. Various semantics are introduced to consider attacks' strength to particularize the effect of the new perspective. Finally, we analyze a case study where all the elements of the formal construction of the formalism are exercised.
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Articulos(CCT - NOA SUR)
Articulos de CTRO.CIENTIFICO TECNOL.CONICET - NOA SUR
Articulos de CTRO.CIENTIFICO TECNOL.CONICET - NOA SUR
Citación
Budan, Paola Daniela; Escañuela Gonzalez, Melisa Gisselle; Budan, Maximiliano Celmo David; Martinez, Maria Vanina; Simari, Guillermo Ricardo; Strength in coalitions: Community detection through argument similarity; IOS Press; Argument and Computation; 14; 3; 12-2022; 275-325
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