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Human Rights Violation Detection on Social Media

Pilankar, Yash (2022) Human Rights Violation Detection on Social Media. Masters thesis, Dublin, National College of Ireland.

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Apart from entertainment, Social Media is also used for being vocal for Human Rights, as Activists and other User’s shares Post in form of text or Media but are not able to reach audience and Human Rights organizations. As there is a staggering growth in technology, usage of advance techniques like Machine Learning and Deep Learning Models can help to get sentiments of these users for better insights and classification. Hence, the objective of the given study was to detect the post/tweets which are about Human Rights Violation over Social Media which can help peacekeeping organization to monitor real-time situation where human rights are being violated. The study was achieved by implementing different experiments of Machine Learning, Natural Language Processing (NLP) and Deep Learning Models on a Dataset fetched from Twitter using Twitter API and were adjudged based on metrics namely accuracy, sensitivity and specificity.For Machine Learning Models accuracy of 98% was achieved whereas on Deep Learning Model decent accuracy of 75% was obtained.Based on the results, given study was able to classify tweets about Human Rights violation and can be used extended further for future use by different organizations.

Item Type: Thesis (Masters)
Subjects: Q Science > QA Mathematics > Electronic computers. Computer science
T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science
Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Machine learning
Z Bibliography. Library Science. Information Resources > ZA Information resources > ZA4150 Computer Network Resources > The Internet > World Wide Web > Websites > Online social networks
T Technology > TK Electrical engineering. Electronics. Nuclear engineering > Telecommunications > The Internet > World Wide Web > Websites > Online social networks
Divisions: School of Computing > Master of Science in Data Analytics
Depositing User: Tamara Malone
Date Deposited: 28 Feb 2023 17:30
Last Modified: 01 Mar 2023 17:47

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