# Effect of Toxic Review Content on Overall Product Sentiment

arXiv: https://arxiv.org/abs/2201.02857 · HTML: https://mlsanity.com/paper/2201.02857/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 6 of its 27 references that are in the map.
- First posted on arXiv 8 Jan 2022.

## Builds on (most cited first, 6 of 6)

- [Anyone Can Become a Troll: Causes of Trolling Behavior in Online Discussions](https://mlsanity.com/paper/1702.01119/) (2017)
- [Mean Birds: Detecting Aggression and Bullying on Twitter](https://mlsanity.com/paper/1702.06877/) (2017)
- [Deep Learning for User Comment Moderation](https://mlsanity.com/paper/1705.09993/) (2017)
- [Machine Learning Suites for Online Toxicity Detection](https://mlsanity.com/paper/1810.01869/) (2018)
- [Towards Understanding Cyberbullying Behavior in a Semi-Anonymous Social Network](https://mlsanity.com/paper/1404.3839/) (2014)
- [On bibliographic networks](https://mlsanity.com/paper/1301.4655/) (2013)

## Abstract (arXiv)

Toxic contents in online product review are a common phenomenon. A content is perceived to be toxic when it is rude, disrespectful, or unreasonable and make individuals leave the discussion. Machine learning algorithms helps the sell side community to identify such toxic patterns and eventually moderate such inputs. Yet, the extant literature provides fewer information about the sentiment of a prospective consumer on the perception of a product after being exposed to such toxic review content. In this study, we collect a balanced data set of review comments from 18 different players segregated into three different sectors from google play-store. Then we calculate the sentence-level sentiment and toxicity score of individual review content. Finally, we use structural equation modelling to quantitatively study the influence of toxic content on overall product sentiment. We observe that comment toxicity negatively influences overall product sentiment but do not exhibit a mediating effect over reviewer score to influence sector-wise relative rating.