Detecting state of aggression in sentences using CNN
Rodmonga Potapova, Denis Gordeev

TL;DR
This paper explores detecting aggression in sentences through neural networks, comparing CNN and Random Forest classifiers on message data from anonymous imageboards and movie reviews.
Contribution
It introduces a neural network approach for aggression detection and compares its performance with traditional classifiers on specific corpora.
Findings
CNN outperforms Random Forest on aggression detection
Neural networks show promise for verbal aggression analysis
Results demonstrate effectiveness on specialized message datasets
Abstract
In this article we study verbal expression of aggression and its detection using machine learning and neural networks methods. We test our results using our corpora of messages from anonymous imageboards. We also compare Random forest classifier with convolutional neural network for "Movie reviews with one sentence per review" corpus.
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Taxonomy
TopicsHate Speech and Cyberbullying Detection · Sentiment Analysis and Opinion Mining · Network Security and Intrusion Detection
