Saved in:
Bibliographic Details
Main Author: Coronado-Blázquez, Javier
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2405.06306
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866916241704222720
author Coronado-Blázquez, Javier
author_facet Coronado-Blázquez, Javier
contents Many videogames suffer "review bombing" -a large volume of unusually low scores that in many cases do not reflect the real quality of the product- when rated by users. By taking Metacritic's 50,000+ user score aggregations for PC games in English language, we use a Natural Language Processing (NLP) approach to try to understand the main words and concepts appearing in such cases, reaching a 0.88 accuracy on a validation set when distinguishing between just bad ratings and review bombings. By uncovering and analyzing the patterns driving this phenomenon, these results could be used to further mitigate these situations.
format Preprint
id arxiv_https___arxiv_org_abs_2405_06306
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle A NLP Approach to "Review Bombing" in Metacritic PC Videogames User Ratings
Coronado-Blázquez, Javier
Computation and Language
Machine Learning
Many videogames suffer "review bombing" -a large volume of unusually low scores that in many cases do not reflect the real quality of the product- when rated by users. By taking Metacritic's 50,000+ user score aggregations for PC games in English language, we use a Natural Language Processing (NLP) approach to try to understand the main words and concepts appearing in such cases, reaching a 0.88 accuracy on a validation set when distinguishing between just bad ratings and review bombings. By uncovering and analyzing the patterns driving this phenomenon, these results could be used to further mitigate these situations.
title A NLP Approach to "Review Bombing" in Metacritic PC Videogames User Ratings
topic Computation and Language
Machine Learning
url https://arxiv.org/abs/2405.06306