|
Authors | Features used | Classifier |
|
Nandhini and Sheeba [20] | Noun, pronoun, and adjective | Fuzzy logic-based genetic algorithm |
Potha et al. [21] | Local, sentimental, contextual, and gender-specific language features | SVM |
Kumar and Sachdeva [28] | Direct and indirect CB features | SVM |
Al-garadi et al. [8] | Network, activity and user information, and tweet content | SVM |
[28] | Network, activity and user information, and tweet content | Naïve Bayes (NB) |
[25] | Network, activity and user information, and tweet content | k-nearest neighbor (KNN) and random forest (RF) |
Balakrishnan et al. [25] | Psychological features | NB, RF, and J48 |
Murnion et al. [18] | IsAbusive, IsPositive, IsNegative, HasBadLanguage, IsRacist, NoobRelated, SpecificTarget, and FilteredText | Sentiment text analytics system is supported with a scoring scheme |
Ho et al. [27] | Abusive words | Logistic regression model |
Balakrishnan et al. [24] | 15 twitter features [23] | RF classifier |
Sánchez-Medina et al. [26] | Psychopathy, narcissism, and machiavellianism | Ensemble classification trees |
Lee et al. [22] | New abusive words | Three-layered neural network model |
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