• Stars
    star
    2
  • Language
    Jupyter Notebook
  • Created over 4 years ago
  • Updated over 4 years ago

Reviews

There are no reviews yet. Be the first to send feedback to the community and the maintainers!

Repository Details

Twitter undoubtedly contains a diverse range of political insight and commentary. But, to what extent is this representative of an electorate? Can we analyze political sentiment effectively enough to capture the voting intentions of a nation during an election campaign? In this present day, social media platforms are playing a vital role in influencing people’s sentiment in favor or against a government or an organization. Twitter-based data is not inherently a representative sample of society. However, opinion mining using machine learning techniques can categorize a tweet as positive, negative, and neutral in such a way that the election winner can be predicted almost quite accurately based on the ratio of positive tweets to the total tweet mentions. This project aims to identify and analyze public sentiments towards the top presidential candidates within the past 2 Nigerian elections, with the aim of determining their chances of being elected into the highest position of authority in Nigeria based on social media comments.