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.
| Original language | English |
|---|---|
| Title of host publication | Agents and Artificial Intelligence |
| Pages | 56-72 |
| Number of pages | 17 |
| Volume | 10162 |
| DOIs | |
| Publication status | Published - 2017 |
| Event | ICAART 2016 - Roma Duration: 24 Feb 2016 → 26 Feb 2016 |
Publication series
| Name | LECTURE NOTES IN COMPUTER SCIENCE |
|---|
Conference
| Conference | ICAART 2016 |
|---|---|
| City | Roma |
| Period | 24/2/16 → 26/2/16 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 12 Responsible Consumption and Production
Keywords
- consumer behavior
- computational argumentation
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