TWITTER MINING FOR NATURAL DISASTER RESPONSE

• Main Author: PRAKASAN, USHALINIE SELVI
• Format: Final Year Project
• Language: English
• Published: IRC 2020
• Subjects: Q Science (General)
• Online Access: http://utpedia.utp.edu.my/21715/1/24614_Ushalinie%20Selvi%20A_P%20Prakasan.pdf; http://utpedia.utp.edu.my/21715/

Recent years, billions of people are using social media and billions of contents are generated by users daily. The common social media platforms used worldwide are Twitter, Facebook and Instagram and the contents are of vast topics such as fashion, politics, business, education, etc. In a way, social media is a useful source of information for conducting sentiment analysis to understand a user’s attitude or emotions towards the topic by classifying it into positive and negative category. The main purpose of this project is to develop sentiment analysis focusing on a single domain which is to detect natural disaster in Tweets by using the widely known lexicon-based approach. Python programming language will be utilized for the development of the system. This project may assist first responders to improve situational awareness and crisis management. In order to understand sentiment analysis and lexicon-based approach, research and literature review was done, and each topic is explained separately.