A Framework for Detecting Event related Sentiments of a Community

TL;DR

This paper introduces a generic framework to detect and analyze community-specific sentiments on social media regarding various events, aiding policymakers and researchers in understanding public opinion dynamics.

Contribution

It proposes a novel framework that identifies community users, extracts event-related tweets, and analyzes sentiments, demonstrating effectiveness through qualitative and quantitative evaluation.

Findings

Framework effectively detects community sentiments on events

Accurately identifies community users on Twitter

Proves useful for policy making and social analysis

Abstract

Social media has revolutionized human communication and styles of interaction. Due to its easiness and effective medium, people share and exchange information, carry out discussion on various events, and express their opinions. For effective policy making and understanding the response of a community on different events, we need to monitor and analyze the social media. In social media, there are some users who are more influential, for example, a famous politician may have more influence than a common person. These influential users belong to specific communities. The main object of this research is to know the sentiments of a specific community on various events. For detecting the event based sentiments of a community we propose a generic framework. Our framework identifies the users of a specific community on twitter. After identifying the users of a community, we fetch their tweets and identify tweets belonging to specific events. The event based tweets are pre-processed. Pre-processed tweets are then analyzed for detecting sentiments of a community for specific events. Qualitative and quantitative evaluation confirms the effectiveness and usefulness of our proposed framework.