2021/02/28 by Eftekhar Hossain, Hossain, Eftekhar, Omar Sharif +3 · 1 citation
Computer Science · #Computation and Language (cs.CL) #FOS: Computer and information sciences #Hate Speech and Cyberbullying Detection #Sentiment Analysis and Opinion Mining
paper · pdf · doi:10.48550/arxiv.2103.00464
openalex publication_date 2021/02/28 · openalex created_date 2022/07/25 · openalex updated_date 2026/07/28
In recent years, several systems have been developed to regulate the spread\nof negativity and eliminate aggressive, offensive or abusive contents from the\nonline platforms. Nevertheless, a limited number of researches carried out to\nidentify positive, encouraging and supportive contents. In this work, our goal\nis to identify whether a social media post/comment contains hope speech or not.\nWe propose three distinct models to identify hope speech in English, Tamil and\nMalayalam language to serve this purpose. To attain this goal, we employed\nvarious machine learning (support vector machine, logistic regression,\nensemble), deep learning (convolutional neural network + long short term\nmemory) and transformer (m-BERT, Indic-BERT, XLNet, XLM-Roberta) based methods.\nResults indicate that XLM-Roberta outdoes all other techniques by gaining a\nweighted f1-score of 0.93, 0.60 and 0.85 respectively for English,\nTamil and Malayalam language. Our team has achieved 1st, 2nd and\n1st rank in these three tasks respectively.\n