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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: 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/
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spelling my-utp-utpedia.217152021-09-23T23:43:48Z http://utpedia.utp.edu.my/21715/ TWITTER MINING FOR NATURAL DISASTER RESPONSE PRAKASAN, USHALINIE SELVI Q Science (General) 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. IRC 2020-09 Final Year Project NonPeerReviewed application/pdf en http://utpedia.utp.edu.my/21715/1/24614_Ushalinie%20Selvi%20A_P%20Prakasan.pdf PRAKASAN, USHALINIE SELVI (2020) TWITTER MINING FOR NATURAL DISASTER RESPONSE. IRC, Universiti Teknologi PETRONAS. (Submitted)
institution Universiti Teknologi Petronas
building UTP Resource Centre
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Petronas
content_source UTP Electronic and Digitized Intellectual Asset
url_provider http://utpedia.utp.edu.my/
language English
topic Q Science (General)
spellingShingle Q Science (General)
PRAKASAN, USHALINIE SELVI
TWITTER MINING FOR NATURAL DISASTER RESPONSE
description 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.
format Final Year Project
author PRAKASAN, USHALINIE SELVI
author_facet PRAKASAN, USHALINIE SELVI
author_sort PRAKASAN, USHALINIE SELVI
title TWITTER MINING FOR NATURAL DISASTER RESPONSE
title_short TWITTER MINING FOR NATURAL DISASTER RESPONSE
title_full TWITTER MINING FOR NATURAL DISASTER RESPONSE
title_fullStr TWITTER MINING FOR NATURAL DISASTER RESPONSE
title_full_unstemmed TWITTER MINING FOR NATURAL DISASTER RESPONSE
title_sort twitter mining for natural disaster response
publisher IRC
publishDate 2020
url http://utpedia.utp.edu.my/21715/1/24614_Ushalinie%20Selvi%20A_P%20Prakasan.pdf
http://utpedia.utp.edu.my/21715/
_version_ 1739832902373343232
score 13.211869

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