Name
Abstract | ||
|---|---|---|
Detection of toxicity in online commentary is a growing branch of Natural Language Processing (NLP). Most research in the area rely only on text-based toxic comment detection. We propose a machine learning approach for detecting the toxicity of a comment by analyzing both the text and the emojis within the comment. Our approach utilizes word embeddings derived from GloVe and emoji2vec to train a b... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/MASS52906.2021.00097 | 2021 IEEE 18th International Conference on Mobile Ad Hoc and Smart Systems (MASS) |
Keywords | DocType | ISSN |
Toxicology,Conferences,Machine learning,Natural language processing,Data models,Long short term memory | Conference | 2155-6806 |
ISBN | Citations | PageRank |
978-1-6654-4935-9 | 0 | 0.34 |
References | Authors | |
0 | 7 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Michael Aquino | 1 | 0 | 0.34 |
| Yasiris Ortiz | 2 | 0 | 0.34 |
| Arif Rashid | 3 | 0 | 0.34 |
| Anne M. Tumlin | 4 | 0 | 0.68 |
| N. Sertac Artan | 5 | 0 | 1.01 |
| Ziqian Dong | 6 | 101 | 13.99 |
| Huanying Gu | 7 | 0 | 0.68 |