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The method developed based on HLSTM model helps in recognizing the hatred word context by mining the intention of the user for using that word in the sentence. Wide experiments suggests that the HLSTM-based classification model gives the accuracy of 97.49% when evaluated against the standard parameters like BLSTM, CRF, LR, SVM, Random Forest and Decision Tree models especially when there are some hatred and trolling words in the social media data.<\/jats:p>","DOI":"10.1007\/s40747-021-00487-7","type":"journal-article","created":{"date-parts":[[2021,8,17]],"date-time":"2021-08-17T05:03:02Z","timestamp":1629176582000},"page":"2813-2826","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":130,"title":["Hatred and trolling detection transliteration framework using hierarchical LSTM in code-mixed social media text"],"prefix":"10.1007","volume":"9","author":[{"given":"Shashi","family":"Shekhar","sequence":"first","affiliation":[]},{"given":"Hitendra","family":"Garg","sequence":"additional","affiliation":[]},{"given":"Rohit","family":"Agrawal","sequence":"additional","affiliation":[]},{"given":"Shivendra","family":"Shivani","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3400-3504","authenticated-orcid":false,"given":"Bhisham","family":"Sharma","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,8,17]]},"reference":[{"key":"487_CR1","doi-asserted-by":"crossref","unstructured":"Mathew, B, Dutt R, Goyal P, Mukherjee A (2018) Spread of hate speech in online social media. 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