A NLP Approach to "Review Bombing" in Metacritic PC Videogames User Ratings
<|reference_start|>A NLP Approach to "Review Bombing" in Metacritic PC Videogames User Ratings: 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.<|reference_end|>
@article{coronado-blázquez2024a,
    title={A NLP Approach to "Review Bombing" in Metacritic PC Videogames User
  Ratings},
    author={Javier Coronado-Bl'azquez},
    journal={arXiv preprint arXiv:2405.06306},
    year={2024},
    archivePrefix={arXiv},
    eprint={2405.06306},
    primaryClass={cs.CL cs.LG}
}