| Autor: |
Reddy, K. Babu, Ramkumar, G. |
| Předmět: |
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| Zdroj: |
AIP Conference Proceedings; 2024, Vol. 2871 Issue 1, p1-7, 7p |
| Abstrakt: |
A study that pits a novel recurrent neural network-based cyberbullying inference approach against a support vector machine classifier reveals that the new method outperforms the latter. Approach and Substances Employed: This strategy is used by two firms. Twenty instances were assigned to each group so that they could test their cyberbullying deduction skills. While Group 1 made use of recurrent neural networks, Group 2 opted to employ support vector machines. We estimated the sample size using a fixed pretest power of 80% and a G power of 80%. In terms of accuracy, the data shows that RNNs are 94.43% better than support vector machines. There is a statistically significant difference, as shown by the p-value of 0.18 (p>0.05). The results show that recurrent neural network techniques are much superior than support vector machine classifiers. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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