Date of Award


Document Type


Degree Name

Master of Science in Computer Science


School of Computer Science and Engineering

First Reader/Committee Chair

Dr. Yan Zhang


Police departments are frequently utilizing social media platforms to actively interact with the public. Social media offers an opportunity to share information, facilitate communication, and foster stronger connections between police departments and the communities they serve. In this context sentiment analysis of social media data has become a tool, for identifying sentiments and tracking emerging trends.

This project utilizes sentiment analysis to examine the social media interactions with particular data obtained from the Twitter (X). Initially, the project gathers social media data, from twitter mentioned accounts on Twitter utilizing web scraping techniques. Afterwards, we perform a thorough sentiment analysis using techniques, in Natural Language Processing (NLP). We utilize two reliable sentiment analysis tools, TextBlob and Natural Language Toolkit (NTLK) to classify media posts into three distinct sentiment categories positive, negative, and neutral. Additionally, it monitors the opinions of public sentiments on a monthly basis. The project utilizes data visualization techniques like pie charts, line charts, and clustered column charts to represent sentiment analysis data in appealing ways that highlight the distribution and the trends of public opinion.