DETECTING ANTI-SOCIAL BEHAVIOUR THROUGH SENTIMENT ANALYSIS OF ROMAN TEXT ON SOCIAL MEDIA
Download
Author:
FOMIA IRUM
Citable URI :
https://vspace.vu.edu.pk/detail.aspx?id=170
Publisher :
Virtual University
Date Issued:
12/21/2018 12:00:00 AM
Abstract
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, I developed 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.
URI :
https://vspace.vu.edu.pk/details.aspx?id=170
Citation:
Irum, F.(2018), DETECTING ANTI-SOCIAL BEHAVIOUR THROUGH SENTIMENT ANALYSIS OF ROMAN TEXT ON SOCIAL MEDIA. Virtual University of Pakistan.(Lahore, Pakistan).
Version :
Final Version
Terms of Use :
Detailed Terms :
Journal :
Files in this item |
Name |
Size |
Format |
Spring 2018_CS720_MS150200589.pdf |
1020kb |
pdf |