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  Published Paper Details:

  Paper Title

Analysis Of Women Safety In Indian Cities Using Machine Learning On Tweets

  Authors

  Neha Kumari,  Dr. G. Jose Moses

  Keywords

Sentiment Analysis, Women Safety, Sentiment Classification, Machine Learning

  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 Indian cities with special reference to the role of social media websites and applications like X, Facebook and Instagram. This paper also focuses on how sense of responsibility on part of Indian society can be developed the common Indian people so that we should focus on the safety of women surrounding them. Tweets on X which usually contain images and text and also written messages and quotes which focus on the safety of women in Indian cities can be used to read a message among the Indian Youth Culture and educate people to take strict action and public those who harass the women. X handle which include hash tag messages that are widely spread across the whole globe sir as a platform for women to express their views about how they feel while we go out for work or travel in a public transport and what is the state of their mind when they are surrounded by unknown men and whether these women feel safe or not. Future research can enhance this work by employing advanced deep learning models for better sentiment detection, supporting multilingual analysis to cover regional perspectives, and developing real-time dashboards for law enforcement use. Integrating artificial intelligence with predictive analytics can further assist in forecasting potential safety risks and recommending preventive measures. In conclusion, this study underscores the importance of leveraging machine learning and social media analytics in assessing and improving women's safety in Indian cities. By analyzing public sentiment on social media, authorities can gain valuable insights into prevailing concerns and implement data-driven interventions. The findings contribute to the growing field of AI-driven public safety solutions and emphasize the need for continuous monitoring and policy enhancements to create safer urban environments for women in India.

  IJCRT's Publication Details

  Unique Identification Number - IJCRT25A6171

  Paper ID - 290445

  Page Number(s) - k114-k131

  Pubished in - Volume 13 | Issue 6 | June 2025

  DOI (Digital Object Identifier) -   

  Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Cite this article

  Neha Kumari,  Dr. G. Jose Moses,   "Analysis Of Women Safety In Indian Cities Using Machine Learning On Tweets", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.13, Issue 6, pp.k114-k131, June 2025, Available at :http://www.ijcrt.org/papers/IJCRT25A6171.pdf

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ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
ISSN
ISSN and 7.97 Impact Factor Details


ISSN
ISSN
ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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