文章基本信息

标题：Analysing tweets using Machine Learning for Woman Safety
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作者：Kalyani Dilip kakade ; Shivani Sunil kakade ; Aditi Singh 等
期刊名称：International Journal of Advances in Engineering and Management
电子版ISSN：2395-5252
出版年度：2019
卷号：1
期号：1
页码：45-49
语种：English
出版社：IJAEM JOURNAL
摘要：Twitter has been used for many analysis based on the sphere of research. In this project we implemented a system which can rate the polarity of woman safety based on the tweets and sentiments shared on the twitter in different regions of the country. We have seen woman safety is a priority in many places of World and in India, so as a result we have come up with a tweet analysis project which can analyze the tweets and based on the sentiments shared by the tweeter users, our system can divide the results in positive aspect. Tweeter users share various kind of information, tweets, images, videos, and other media related to woman safety along with the hashtags that goes with it. Our implementation has successfully distinguished between positive and negative users with respect to regions of the users.
关键词：Women's safety;Sexual Harassment;Sentiments;Safety;Safety Analysis