Unsupervised Sentiment Analysis using Affinity Propagation
Unsupervised Sentiment Analysis using Affinity Propagation
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In today's digital age, the vast number of tweets generated every moment presents a significant opportunity to understand public opinion and sentiment. This project, titled 'Unsupervised Sentiment Analysis using Affinity Propagation' aims to develop a comprehensive understanding of sentiment analysis using innovative techniques like Affinity Propagation clustering. By utilizing social media tweets, it delves into the realm of tweet sentiments to uncover valuable insights within the dynamic world of social media.
In today's digital age, the vast number of tweets generated every moment presents a significant opportunity to understand public opinion and sentiment. This project, titled 'Unsupervised Sentiment Analysis using Affinity Propagation' aims to develop a comprehensive understanding of sentiment analysis using innovative techniques like Affinity Propagation clustering. By utilizing social media tweets, it delves into the realm of tweet sentiments to uncover valuable insights within the dynamic world of social media.
Sentiment analysis is like reading the mood of online conversations. It helps us understand what people are feeling and thinking on social media. By decoding these emotions, we can make better decisions and stay ahead of trends.
Github REPO for the Code for this project: https://github.com/Mayimunah/Affinity-progation-sentiment-analysis
Student
Mayimunah Nagayi
Email: 4163113@myuwc.ac.za
Supervisor
Prof Clement N. Nyirenda
Email: cnyirenda@uwc.ac.za
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