TWITTER MINING FOR NATURAL DISASTER RESPONSE
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,...
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| Main Author: | |
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| Format: | Final Year Project |
| Language: | English |
| Published: |
IRC
2020
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| Subjects: | |
| Online Access: | http://utpedia.utp.edu.my/21715/1/24614_Ushalinie%20Selvi%20A_P%20Prakasan.pdf http://utpedia.utp.edu.my/21715/ |
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| Summary: | 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. |
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