Analysis of Women Safety In India Using Machine Learning on Different Social Media Platform
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Date
2022
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Journal ISSN
Volume Title
Publisher
NHCE
Abstract
In the current scenario, women community facing issues like gender discrimination, schooling, child marriage, sexual assault and harassment, and much more, not just from
society but also from social media. Women are protected by organizations like the She Team, Disha Act, and many others in society, but these organizations are much less in social media. Social networking sites like Twitter, Instagram, Facebook, etc. cause problems for women. This paper focuses on the safety analysis and monitoring of women using various social media platforms in Indian cities. The posts on Facebook and Instagram, as well as tweets on Twitter, that abuse women are considered and show the percentage of threats that women face from social media, which aids in understanding by the youth of India who misuse the women's safety and harass them in social medias via tweets, posts, and text should face strict action. People may grasp the threats to women with the help of this, and it demonstrates that women face challenges not only from society but also from social media platforms. The
outcome is easily comprehended in the form of a graph and a pie chart. Algorithms such as Nave Bayes (NB) and XGBoost are used in the analysis of women's safety on various social
media sites. The goal is to use classification techniques to categorize or forecast the Type based on dataset properties. Using categorization algorithms, we can determine whether
social media content is positive, negative, or neutral. It has been substantiated that Naive Bayes algorithm has proved better accuracy compared to random forest and decision tree
algorithms.