TWITTER SENTIMENT ANALYSIS USING MACHINE LEARNING
Abstract - People use Twitter extensively to share their thoughts and feelings on a variety of situations.Sentiment analysis is a method for examining data and extracting the sentiment it contains. Twittersentiment analysis is the process of applying sentiment analysis to Twitter data (tweets) in order toidentify user sentiments. The amount of study in this area has steadily increased over the last fewdecades. This is because tweets have a complex format that makes processing them challenging.Because tweets are so brief, they create a whole new set of issues, such as slang and abbreviations.The purpose of this study is to analyse a few studies on sentiment analysis on Twitter, including theapproaches used and models used, as well as outlining a broader Python-based strategy. Key Words: Python, natural language processing, machine learning, and sentiment analysis.
Institutions
- Kwara State Polytechnic (NG)
- Matrix Engineering (United States) (US)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2025-04-08
- DOI
- https://doi.org/10.5281/zenodo.15171919
- Primary Topic
- Artificial Intelligence in Games
- Type
- article
- Field-Weighted Citation Impact
- 0.00