A micro study on the evolution of arguments in amazon.Com’s reviews

Simone Gabbriellini, Francesco Santini*

*Autore corrispondente per questo lavoro

Risultato della ricerca: Contributo in libroContributo a convegno

Abstract

In this work we present an exploratory study on arguments in Amazon.com reviews. We manually extract positive (in favour of purchase) and negative (against it) arguments from each review concerning a selected product. Moreover, we link arguments to the rating score and length of reviews. For instance, we show that negative arguments are quite sparse during the first steps of such social review-process, while positive arguments are more equally distributed. In addition, we connect arguments through attacks and we compute Dung’s extensions to check whether they capture such evolution through time. We also use Preference-based Argumentation to exploit the number of appearances of each argument in reviews.
Lingua originaleEnglish
Titolo della pubblicazione ospitePRIMA 2015: Principles and Practice of Multi-Agent Systems
Pagine284-300
Numero di pagine17
Volume9387
DOI
Stato di pubblicazionePubblicato - 2015
Evento18th International Conference on Principles and Practice of Multi-Agent Systems (PRIMA) - Bertinoro (FC), Italy
Durata: 26 giu 201530 giu 2015

Serie di pubblicazioni

NomeLECTURE NOTES IN COMPUTER SCIENCE

Convegno

Convegno18th International Conference on Principles and Practice of Multi-Agent Systems (PRIMA)
CittàBertinoro (FC), Italy
Periodo26/6/1530/6/15

Keywords

  • consumer behavior
  • computational argumentation
  • agent-based models

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