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Social media has become an embedded part of the political system of the modern world, as regular citizens and political leaders have access to a digital platform to voice their personal opinions on policies and news. The recent 2016 General Election in the United States featured heavy use of social media platforms, but also featured accusations of election interference using biased and targeted social media posts and ads. The purpose of this research project is a proof-of-concept digital tool used to analyze posts and use artificial intelligence to dissect and analyze said posts for political keywords and opinions. Using context dependent artificial intelligence, with assistance from the Natural Language Toolkit1, the tool should be able to recognize current political keywords, recognize the sentiment of the post and categorize the post to measure the political leanings of the user. This tool could be theoretical election targeting tool used by domestic or foreign adversaries, and remains a prominent issue in the upcoming 2020 elections, and this research project can hopefully be an example that nearly anyone with technical skills can index and identify moving partisan trends in times of political upheaval.



This is a metadata-only record.



  • Subject
    • Computer Science & Information Systems

  • Institution
    • Dahlonega

  • Event location
    • MPR 3

  • Event date
    • 22 March 2019

  • Date submitted

    19 July 2022

  • Additional information
    • Acknowledgements: