Since the emergence of the social media, many studies are conducted on social media to gain information on social media users. Among these studies are sentiment analysis which is an analysis of user sentiments and emotions towards an object, term, or event based on what they post. Sentiment analysis are often conducted on sites like Facebook and Twitter because of their huge number of users and popularity. This paper aims to create a GUI-based sentiment analysis application to find out popularity of universities based on Twitter user’s sentiment. For this purpose, we firstly collected 600 tweets datasets, which is a mixture of 200 tweets each from Princeton University, Stanford University and University of Oxford for a period of 4 days (12/1/2018 to 15/1/2018). Second, the tweets were classified based on their sentiment into “positive”, "neutral" and “negative” tweets. Finally, the results were being analyzed in terms of Precision, Recall and F1 score. These information will help universities to gather information of public sentiment towards their institution and allow them to recognize their strength and weakness. Universities can use that information to improve their public image if needed in the future.
Explainable Sentiment Analysis Application for Social Media Crisis Management in Retail
