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All that is English may be Hindi: Enhancing language identification through automatic ranking of likeliness of word borrowing in social media.

, , , , , , and . CoRR, (2017)

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Is this word borrowed? An automatic approach to quantify the likeliness of borrowing in social media., , , , , and . CoRR, (2017)A deep-learning framework to detect sarcasm targets., , and . EMNLP/IJCNLP (1), page 6335-6341. Association for Computational Linguistics, (2019)All that is English may be Hindi: Enhancing language identification through automatic ranking of likeliness of word borrowing in social media., , , , , , and . CoRR, (2017)Code-Switching Patterns Can Be an Effective Route to Improve Performance of Downstream NLP Applications: A Case Study of Humour, Sarcasm and Hate Speech Detection., , , , and . ACL, page 1018-1023. Association for Computational Linguistics, (2020)Characterizing the Spread of Exaggerated Health News Content over Social Media., , , , , and . HT, page 279-280. ACM, (2019)IISERB Brains at SemEval-2022 Task 6: A Deep-learning Framework to Identify Intended Sarcasm in English., , , , and . SemEval@NAACL, page 938-944. Association for Computational Linguistics, (2022)All that is English may be Hindi: Enhancing language identification through automatic ranking of the likeliness of word borrowing in social media., , , , , , and . EMNLP, page 2264-2274. Association for Computational Linguistics, (2017)What Propels Celebrity Follower Counts? Language Use or Social Connectivity., , and . CoRR, (2018)Context-Aware Deep Markov Random Fields for Fake News Detection., , , , and . IEEE Access, (2021)KGPChamps at SemEval-2019 Task 3: A deep learning approach to detect emotions in the dialog utterances., , , and . SemEval@NAACL-HLT, page 241-246. Association for Computational Linguistics, (2019)