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Erschienen in:
Perception of Masculinity and Femininity of Agent’s Appearance and Self-adaptors Kapitel lesen Erstes Kapitel lesen

2017 | OriginalPaper | Buchkapitel

From Reviews to Arguments and from Arguments Back to Reviewers’ Behaviour

verfasst von : Simone Gabbriellini, Francesco Santini

Erschienen in: Agents and Artificial Intelligence

Verlag: Springer International Publishing

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Abstract

Our aim is to understand reviews from the point of view of the arguments they contain, and then do a first step from how arguments are distributed in such reviews towards the behaviour of the reviewers that posted them. We consider 253 reviews of a selected product (a ballet tutu for kids), extracted from the “Clothing, Shoes and Jeweller” section of Amazon.​com. We explode these reviews into arguments, and we study how their characteristics, e.g., the distribution of positive (in favour of purchase) and negative ones (against purchase), change through a period of four years. Among other results, we discover that negative arguments tend to permeate also positive reviews. As a second step, by using such observations and distributions, we successfully replicate the reviewers’ behaviour by simulating the review-posting process from their basic components, i.e., the arguments themselves.

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Vorheriges Kapitel Adaptive Switching Behavioral Strategies for Effective Team Formation in Changing Environments
Nächstes Kapitel Integrating Graded Knowledge and Temporal Change in a Modal Fragment of OWL
Fußnoten
9
Polarisation only on specific issues has already been observed in many off-line contexts, see [3].
 
10
We used the R poweRlaw package for heavy tailed distributions (developed by Colin Gillespie [12]).
 
11
We used the relatively conservative choice that the power law is ruled out if \(pvalue = 0.1\) [6].
 
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Metadaten
Titel
From Reviews to Arguments and from Arguments Back to Reviewers’ Behaviour
verfasst von
Simone Gabbriellini
Francesco Santini
Copyright-Jahr
2017
Buch
Agents and Artificial Intelligence

Print ISBN: 978-3-319-53353-7

Electronic ISBN: 978-3-319-53354-4

Copyright-Jahr: 2017

DOI
https://doi.org/10.1007/978-3-319-53354-4_4

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