Submit your paper : editorIJETjournal@gmail.com Paper Title : Analysis of Women Safety in Indian Cities Using Machine Learning on Tweets ISSN : 2395-1303 Year of Publication : 2022 10.5281/zenodo.7296078 MLA Style: -S. Sunil Kumar, B. Sruthi, B. Pallavi, T. Rohini Analysis of Women Safety in Indian Cities Using Machine Learning on Tweets , Volume 8 - Issue 5 September - October 2022 International Journal of Engineering and Techniques (IJET) ,ISSN:2395-1303 , www.ijetjournal.org APA Style: -S. Sunil Kumar, B. Sruthi, B. Pallavi, T. Rohini Analysis of Women Safety in Indian Cities Using Machine Learning on Tweets , Volume 8 - Issue 5 September - October 2022 International Journal of Engineering and Techniques (IJET) ,ISSN:2395-1303 , www.ijetjournal.org Abstract Women and girls have been experiencing a lot of violence and harassment in public places in various cities starting from stalking and leading to sexual harassment or sexual assault. This research paper basically focuses on the role of social media in promoting the safety of women in the safety of women is a concern of increasing urgency in India and other countries. The primary issue in the handling of these cases by the police lies in constraints preventing them from responding quickly to calls of distress Reference [1] Agarwal, Apoorv, Fadi Biadsy, and Kathleen R. Mckeown. "Contextual phrase-level polarity analysis using lexical affect scoring and syntactic n-grams." Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics. Association for Computational Linguistics, 2009. [2] Barbosa, Luciano, and Junlan Feng. "Robust sentiment detection on twitter from biased and noisy data." Proceedings of the 23rd international conference on computational linguistics: posters. Association for Computational Linguistics, 2010. [3] Bermingham, Adam, and Alan F. Smeaton. "Classifying sentiment in microblogs: is brevity an advantage?." Proceedings of the 19th ACM international conference on Information and knowledge management. ACM, 2010. [4] Gamon, Michael. "Sentiment classification on customer feedback data: noisy data, large feature vectors, and the role of linguistic analysis." Proceedings of the 20th international conference on Computational Linguistics. Association for Computational Linguistics, 2004. [5] Kim, Soo-Min, and Eduard Hovy. "Determining the sentiment of opinions." Proceedings of the 20th international conference on Computational Linguistics. Association for Computational Linguistics, [6] Klein, Dan, and Christopher D. Manning. "Accurate unlexicalized parsing. [7]Klein, Dan, and Christopher D. Manning. "Accurate unlexicalized parsing." Proceedingsof the 41st Annual Meeting on Association for Computational Linguistics-Volume 1. Association for Computational Linguistics, 2003.. Keywords — Women, Safety, sexual harassment, Hash tag, Sentimental Analysis |