MACHINE LEARNING OF TWITTER FEEDS AND WOMEN SAFETY IN INDIAN CITIES

Authors

  • S. Gokulakrishnan Department of CSE, Sri Chandrasekharendra Saraswathi Viswa Mahavidyalaya, Kanchipuram, India
  • Chitte Ashok Reddy Department of CSE, Sri Chandrasekharendra Saraswathi Viswa Mahavidyalaya, Kanchipuram, India
  • Palutla Venkata Sai Anudeep Department of CSE, Sri Chandrasekharendra Saraswathi Viswa Mahavidyalaya, Kanchipuram, India

DOI:

https://doi.org/10.58973/CTRJ.221112

Keywords:

Twitter, accuracy, , Harassment,, Indian cities,, Safety

Abstract

Background: Women and girls in Indian cities increasingly post about harassment and unsafe situations on Twitter, generating large volumes of tweets whose analysis calls for automated methods.

Objective: This paper examines the role of Twitter feeds in assessing the safety of women and girls in Indian cities using machine learning algorithms.

Methods: A dataset of tweets on women's safety was cleaned with NLTK and analyzed with the TextBlob package and a sentiment dictionary, which count positive, negative, and neutral polarity.

Results: Of 15,054 tweets analyzed, 74.6% expressed negative sentiment, 22.3% neutral, and 3.1% positive, so that about 74% of the location can be confirmed unsafe for women.

Conclusion: Machine learning algorithms help organize and analyze Twitter data, including millions of daily tweets and messages, and the same approach can be extended to other social media platforms. 

Keywords: Accuracy, Harassment, Sarcasm, Emoticons

 HIGHLIGHTS:

1.      A simple machine learning algorithm helps analyze tweet feeds concerning girls’ safety.

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Published

2022-10-05

Issue

Vol. 1 No. 1 (2022): October: Computing Technology Research Journal

Section

Short Communication

License

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How to Cite

MACHINE LEARNING OF TWITTER FEEDS AND WOMEN SAFETY IN INDIAN CITIES. (2022). Computing Technology Research Journal, 1(1), 12-13. https://doi.org/10.58973/CTRJ.221112