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Towards Toxic Positivity DetectionAuthors: Ishan Sanjeev Upadhyay,KV Aditya Srivatsa,Radhika Mamidi Conference: Proceedings of the Tenth International Workshop on Natural Language Processing for Social Media (SocialNLP) 2022 Pages: 1-8 Date: 2022-07-14 Report no: IIIT/TR/2022/21 AbstractOver the past few years, there has been a growing concern around toxic positivity on social media which is a phenomenon where positivity is used to minimize one’s emotional experience. In this paper, we create a dataset for toxic positivity classification from Twitter and an inspirational quote website. We then perform benchmarking experiments using various text classification models and show the suitability of these models for the task. We achieved a macro F1 score of 0.71 and a weighted F1 score of 0.85 by using an ensemble model. To the best of our knowledge, our dataset is the first such dataset created. Full paper: pdf Centre for Language Technologies Research Centre |
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