Gender-Based Tweet Analysis (GTA)

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Author(s): Dipti P. Rana (Sardar Vallabhbhai National Institute of Technology, Surat, India)and Navodita Saini (Sardar Vallabhbhai National Institute of Technology, Surat, India)
Copyright: 2021
Pages: 13
Source title: Data Preprocessing, Active Learning, and Cost Perceptive Approaches for Resolving Data Imbalance
Source Author(s)/Editor(s): Dipti P. Rana (Sardar Vallabhbhai National Institute of Technology, Surat, India)and Rupa G. Mehta (Sardar Vallabhbhai National Institute of Technology, Surat, India)
DOI: 10.4018/978-1-7998-7371-6.ch015

Keywords: Data Management / Data Mining and Databases / Engineering Science Reference / Knowledge Management and Library Science

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Abstract

Each gender is having special personality and behavior characteristics that can be naturally reflected in the language used on social media to review, spread information, make relationships, etc. This information is used by different agencies for their profits. The magnified study of this information can reflect the implicit biases of their creators' gender. The ratio of gender is imbalanced across the global world, social media, discussion, etc. Twitter is used to discuss the issues caused by COVID-19 disease like its symptoms, mental health, advice, etc. This fascinating information motivated this research to propose the methodology gender-based tweet analysis (GTA) to study and magnify gender's impact on emotions of tweet data. The analysis of the experiment discovered the biases of gender on emotions of tweet data and highlighted the future real-world applications which may become more productive if gender biases are considered for the safety and benefit of society.

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