Classification of social media Toxic comments using Machine learning models
The abstract outlines the problem of toxic comments on social media platforms, where individuals use disrespectful, abusive, and unreasonable language that can drive users away from discussions. This behavior is referred to as anti-social behavior, which occurs during online debates, comments, and fights. The comments containing explicit language can be classified into various categories, such as toxic, severe toxic, obscene, threat, insult, and identity hate. This behavior leads to online harassment and cyberbullying, which forces individuals to stop expressing their opinions and ideas. To protect users from offensive language, companies have started flagging comments and blocking users. The abstract proposes to create a classifier using an Lstm-cnn model that can differentiate between toxic and non-toxic comments with high accuracy. The classifier can help organizations examine the toxicity of the comment section better.
Code (1)
Tasks
BlockingSimilar Papers 제목 키워드 기반
Constructive and Toxic Speech Detection for Open-domain Social Media Comments in Vietnamese
The rise of social media has led to the increasing of comments on online forums. However, there still exists invalid comments which are not informative for users. Moreover, those comments are also quite toxic and harmful…
Constructive Comment ClassificationGeneral ClassificationText ClassificationToxic Comment Classification+1Toxic Language Detection in Social Media for Brazilian Portuguese: New Dataset and Multilingual Analysis
Hate speech and toxic comments are a common concern of social media platform users. Although these comments are, fortunately, the minority in these platforms, they are still capable of causing harm. Therefore, identifyin…
Hate Speech DetectionMulti-Label ClassificationMUlTI-LABEL-ClASSIFICATIONText ClassificationAssessing the Level of Toxicity Against Distinct Groups in Bangla Social Media Comments: A Comprehensive Investigation
Social media platforms have a vital role in the modern world, serving as conduits for communication, the exchange of ideas, and the establishment of networks. However, the misuse of these platforms through toxic comments…
Aanisha@TamilNLP-ACL2022:Abusive Detection in Tamil
In social media, there are instances where people present their opinions in strong language, resorting to abusive/toxic comments.There are instances of communal hatred, hate-speech, toxicity and bullying. And, in this ag…
Multi-class ClassificationToxicity Detection for Indic Multilingual Social Media Content
Toxic content is one of the most critical issues for social media platforms today. India alone had 518 million social media users in 2020. In order to provide a good experience to content creators and their audience, it …
Abuse DetectionSentence