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Detecting Anti-Social Behaviour Through Sentiment Analysis of Roman Text on Social Media

Thesis Info

Access Option

External Link

Author

Fomia Irum

Institute

Virtual University of Pakistan

Institute Type

Public

City

Lahore

Province

Punjab

Country

Pakistan

Thesis Completing Year

2018

Thesis Completion Status

Completed

Subject

Software Engineering

Language

English

Link

http://vspace.vu.edu.pk/detail.aspx?id=170

Added

2021-02-17 19:49:13

Modified

2024-03-24 20:25:49

ARI ID

1676720984825

Similar


The automated Sentiment Analysis is widely used in many domains to detect the emotional content in text. This research work aims to detect emotions encapsulated by the writer by means of a combination of statistical analysis and machine learning methods. Many supervised and unsupervised sentiment analysis have been proposed in literature. Majority of these techniques works for English languages sentiment analysis. Whereas Pakistani people?s use roman Urdu for social media sites but there is no technique focusing on roman Urdu text. So, in this research, Ideveloped a model to detect antisocial behavior and define emotional state. The model is taking Roman Urdu feeds as input to help identify the user behavior/mood. An in-depth analysis is be provided by comparing the developed model with other state-of-the-art techniques to justify it in terms of efficiency and effectiveness. I design and implement new algorithm that will detect Anti Social Behavior on roman Urdu using sentiment analysis techniques.
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