Name
Abstract | ||
|---|---|---|
•A probabilistic clustering model for hate speech classification in twitter was developed.•The use of a naïve Bayes model to improve features representation.•The use of a modified Jaccard similarity measure for clustering real-time tweet into topic clusters.•The use of 4-level scale fuzzy model for hate speech classification.•The Paired Sample t-Test validated the efficiency of the developed model. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1016/j.eswa.2021.114762 | Expert Systems with Applications |
Keywords | DocType | Volume |
Twitter,Hate speech,Fuzzy logic,Combinatorial algorithm,Bayesian function,Sentiment analysis | Journal | 173 |
ISSN | Citations | PageRank |
0957-4174 | 0 | 0.34 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Femi Emmanuel Ayo | 1 | 0 | 0.34 |
| Olusegun Folorunso | 2 | 37 | 10.55 |
| Friday Thomas Ibharalu | 3 | 0 | 0.34 |
| Idowu Ademola Osinuga | 4 | 0 | 0.34 |
| Adebayo Abayomi-Alli | 5 | 1 | 1.36 |