@inproceedings{pascucci-etal-2020-hotel,
title = "Is this hotel review truthful or deceptive? A platform for disinformation detection through computational stylometry",
author = "Pascucci, Antonio and
Manna, Raffaele and
Caterino, Ciro and
Masucci, Vincenzo and
Monti, Johanna",
editor = "Bhatia, Archna and
Shaikh, Samira",
booktitle = "Proceedings for the First International Workshop on Social Threats in Online Conversations: Understanding and Management",
month = may,
year = "2020",
address = "Marseille, France",
publisher = "European Language Resources Association",
url = "https://aclanthology.org/2020.stoc-1.6",
pages = "35--40",
abstract = "In this paper, we present a web service platform for disinformation detection in hotel reviews written in English. The platform relies on a hybrid approach of computational stylometry techniques, machine learning and linguistic rules written using COGITO, Expert System Corp.{'}s semantic intelligence software thanks to which it is possible to analyze texts and extract all their characteristics. We carried out a research experiment on the Deceptive Opinion Spam corpus, a balanced corpus composed of 1,600 hotel reviews of 20 Chicago hotels split into four datasets: positive truthful, negative truthful, positive deceptive and negative deceptive reviews. We investigated four different classifiers and we detected that Simple Logistic is the most performing algorithm for this type of classification.",
language = "English",
ISBN = "979-10-95546-39-9",
}
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<abstract>In this paper, we present a web service platform for disinformation detection in hotel reviews written in English. The platform relies on a hybrid approach of computational stylometry techniques, machine learning and linguistic rules written using COGITO, Expert System Corp.’s semantic intelligence software thanks to which it is possible to analyze texts and extract all their characteristics. We carried out a research experiment on the Deceptive Opinion Spam corpus, a balanced corpus composed of 1,600 hotel reviews of 20 Chicago hotels split into four datasets: positive truthful, negative truthful, positive deceptive and negative deceptive reviews. We investigated four different classifiers and we detected that Simple Logistic is the most performing algorithm for this type of classification.</abstract>
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%0 Conference Proceedings
%T Is this hotel review truthful or deceptive? A platform for disinformation detection through computational stylometry
%A Pascucci, Antonio
%A Manna, Raffaele
%A Caterino, Ciro
%A Masucci, Vincenzo
%A Monti, Johanna
%Y Bhatia, Archna
%Y Shaikh, Samira
%S Proceedings for the First International Workshop on Social Threats in Online Conversations: Understanding and Management
%D 2020
%8 May
%I European Language Resources Association
%C Marseille, France
%@ 979-10-95546-39-9
%G English
%F pascucci-etal-2020-hotel
%X In this paper, we present a web service platform for disinformation detection in hotel reviews written in English. The platform relies on a hybrid approach of computational stylometry techniques, machine learning and linguistic rules written using COGITO, Expert System Corp.’s semantic intelligence software thanks to which it is possible to analyze texts and extract all their characteristics. We carried out a research experiment on the Deceptive Opinion Spam corpus, a balanced corpus composed of 1,600 hotel reviews of 20 Chicago hotels split into four datasets: positive truthful, negative truthful, positive deceptive and negative deceptive reviews. We investigated four different classifiers and we detected that Simple Logistic is the most performing algorithm for this type of classification.
%U https://aclanthology.org/2020.stoc-1.6
%P 35-40
Markdown (Informal)
[Is this hotel review truthful or deceptive? A platform for disinformation detection through computational stylometry](https://aclanthology.org/2020.stoc-1.6) (Pascucci et al., STOC 2020)
ACL