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Analysis and mining of an election-based network using large-scale twitter data: a retrospective study.

Amartya Chakraborty1, Nandini Mukherjee2

  • 1Department of Computer Science and Engineering, University of Engineering and Management, Kolkata, West Bengal 700160 India.

Social Network Analysis and Mining
|May 1, 2023
PubMed
Summary

Analyzing Twitter data from India

Keywords:
Cluster dominanceElection networkIndian electionsNetwork analysisSocial networksTwitter network

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Area of Science:

  • Social Network Analysis
  • Computational Social Science
  • Political Communication

Background:

  • User-generated Twitter data offers insights into global social, economic, and political issues.
  • Analyzing online social interactions reveals dynamics and real-world phenomena.

Purpose of the Study:

  • To study the structure and dynamics of Twitter networks during Indian state assembly elections.
  • To identify influential actors and analyze user emotions for election forecasting.

Main Methods:

  • Network analysis of tweet-reply interactions during the West Bengal elections.
  • Hashtag analysis for key political contenders.
  • Lexicon-based emotion detection on collected tweets.

Main Results:

  • Cluster dominance in the Twitter network correlated with actual election outcomes, suggesting forecasting potential.
  • Fear was the dominant emotion expressed, with happiness being scarce.
  • Identification of key political and media actors and their network influence.

Conclusions:

  • Twitter network analysis, including cluster dominance and emotion detection, can serve as an election forecasting tool.
  • The study highlights the significant role of social media in reflecting and potentially influencing political discourse and outcomes.