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Research Paper | Data & Knowledge Engineering | India | Volume 13 Issue 1, January 2024
Predictive Analysis of Social Unrest in India: A Machine Learning Perspective on 2016-2023 Data Trends
Abstract: Riots and social unrest pose serious threats to public safety and societal stability. For efficient prevention and management, it is essential to comprehend the patterns and dynamics of such incidents. This study focuses on utilizing machine learning techniques to analyze, visualize, forecast, and classifyevents of social unrest in India from 2016 to 2023. The study makes use of a large dataset that includes a variety of information, such as geographic data, event characteristics, connected actors, and 28 different parameters. Two machine learning models are employed: a decision tree classifier and a random forest classifier for the classification and forecasting of social unrest and events. These models are trained and evaluated using the Armed Conflict Location and Event Data (ACLED)dataset, which is split into training and testing sets.
Keywords: Social unrest, Riot prediction, Machine learning, Armed conflict analysis, Riots analysis India
Edition: Volume 13 Issue 1, January 2024,
Pages: 359 - 363