(Georgia Institute of Technology, 2022-12)
Durrani, Faris; Ahmed, Nemeth; Zandstra, Justin; Wang, RenChu; Lakshmanan, Lakshmi Sree; Lin, Shuyan
Sentiment Analysis has been used to identify changing moods of populations. In this project, we have analysed how sentiments revolve over topics from significant world events across social media platform (Facebook, Reddit, Twitter) and news sources (CNN, The New York Times, The Guardian). We have created an interactive visualization tool that allows to filter data on specific keywords and dates, and visualize time series sentiments along with the top words used in posts. This dashboard could potentially be used by businesses or political campaigns to analyze the effect of marketing strategies on public sentiment regarding their product, or to analyze the social climate surrounding certain ideas and issues on multiple platforms. Future steps could include a dynamic rendering of sentiments with new media posts using faster, more efficient algorithms.