Detecting Propaganda During Article 370 Abrogation Using ML on Social Networks

Home Minister Amit Shah's move to abrogate Articles 370 and 35A had massive ramifications for Jammu and Kashmir (J&K). They express their thoughts on Facebook or Twitter, Twitter: It is also a huge playground for spreading misinformation and propaganda. This work employs machine learning with the objective of detecting propaganda during the J&K abrogation of Articles 370 and 35A. Data from Twitter was extracted using its API, leveraging trending hashtags. Subsequently, we manually annotated the results The work makes use of a hybrid-feature engineering method for feature selection, after which several machine learning algorithms are applied in order to classify the tweets into two categories. The decision tree algorithm yields superior results when comparing all the algorithms used. Deep learning can be applied to classification tasks, and the feature engineering approach can be enhanced for more precise outcomes.

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Publication Details

Published
2024-10-24
DOI
https://doi.org/10.1109/iccsc62048.2024.10830370
Primary Topic
Spam and Phishing Detection
Type
article
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article

Detecting Propaganda During Article 370 Abrogation Using ML on Social Networks

Pankaj Verma, Sunita Mahajan
Spam and Phishing Detection
article

Detecting Propaganda During Article 370 Abrogation Using ML on Social Networks

Pankaj Verma, Sunita Mahajan
article en

Abstract

Home Minister Amit Shah's move to abrogate Articles 370 and 35A had massive ramifications for Jammu and Kashmir (J&K). They express their thoughts on Facebook or Twitter, Twitter: It is also a huge playground for spreading misinformation and propaganda. This work employs machine learning with the objective of detecting propaganda during the J&K abrogation of Articles 370 and 35A. Data from Twitter was extracted using its API, leveraging trending hashtags. Subsequently, we manually annotated the results The work makes use of a hybrid-feature engineering method for feature selection, after which several machine learning algorithms are applied in order to classify the tweets into two categories. The decision tree algorithm yields superior results when comparing all the algorithms used. Deep learning can be applied to classification tasks, and the feature engineering approach can be enhanced for more precise outcomes.

Arni University (IN)
Reduced inequalities
Openalex Percentile: Top 59%
Spam and Phishing Detection
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