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Research Paper | Health and Medical Sciences | India | Volume 12 Issue 6, June 2023 | Popularity: 5.4 / 10

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Twitter Rumour Detection in the Health Domain

Anjana Krishna Sajith, Manika Tyagi, Riddhi Maniktalia, Muskan Bansal

Abstract: Due to the widespread usage of the internet now a-days, a huge quantity of data is produced every day as a result of our daily activity on many platforms including social media, news articles, forums, emails, and websites. Twitter is a microblogging website among social networking sites where users may express their ideas, opinions, and knowledge in a condensed amount of words. Yet, the platform is also susceptible to misinformation that could negatively impact people?s lives, particularly in situations involving health. This study focuses on finding health-related rumours on Twitter and figuring out how they spread in order to address this problem. Data gathering, identification, verification, and the study of networks that spread rumours are the four mod-ules that make up the project. These modules make use of data mining, manual data processing, supervised machine learning, and social network theories. The implementation is carried out using the Python programming language and pertinent libraries like Pandas and Numpy. Several researchers are investigating various approaches to identify whether a subject is a rumour or not in order to tackle the issue of fake news. This study suggests a brand-new rumour detection technique that includes recently developed features like impact potential and measurements of network parameters.

Keywords: Rumor Detection and Classification; Machine Learning; Twitter; Online Social media

Edition: Volume 12 Issue 6, June 2023

Pages: 570 - 576

DOI: https://www.doi.org/10.21275/SR23531125834

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