Journal ArticleOpen Access
Deep Learning Approach for Classifying the Aggressive Comments on Social Media: Machine Translated Data Vs Real Life Data
Author Affiliations
Kennesaw State University, North South University, University of Calabria
Published In2022 IEEE International Conference on Big Data (Big Data)
Year2022
Citations20
Abstract
Aggressive comments on social media negatively impact human life. Such offensive contents are responsible for depression and suicidal-related activities. Since online social networking is increasing day by day, the hate content is also increasing. Several investigations have been done on the domain of cyberbullying, cyberaggression, hate speech, etc. The majority of the inquiry has been done in the English language. Some languages (Hindi and Bangla) still lack proper investigations due to the lack of a dataset. This paper particularly worked on the Hindi, Bangla, and English datasets to detect aggressive comments and have shown a novel way of generating machine-translated data to resolve data unavailability issues. A fully machine-translated English dataset has been analyzed with the models such as the…
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Fields & Keywords
Physical SciencesComputer ScienceArtificial IntelligenceHate Speech and Cyberbullying DetectionSentiment Analysis and Opinion MiningNetwork Security and Intrusion DetectionArtificial intelligenceMachine learningNatural language processingSpeech recognitionOperating systemReliability engineeringQuantum mechanicsProgramming languageWorld Wide Web