Paper Info
Title
Intent Classification Using Feature Sets for Domestic Violence Discourse on Social Media
Abstract
Domestic Violence against women is now recognized to be a serious and widespread problem worldwide. Domestic Violence and Abuse is at the root of so many issues in society and considered as the societal tabooed topic. Fortunately, with the popularity of social media, social welfare communities and victim support groups facilitate the victims to share their abusive stories and allow others to give advice and help victims. Hence, in order to offer the immediate resources for those needs, the specific messages from the victims need to be alarmed from other messages. In this paper, we regard intention mining as a binary classification problem (abuse or advice) with the usecase of abuse discourse. To address this problem, we extract rich feature sets from the raw corpus, using psycholinguistic clues and textual features by term-class interaction method. Machine learning algorithms are used to predict the accuracy of the classifiers between two different feature sets. Our experimental results with high classification accuracy give a promising solution to understand a big social problem through big social media and its use in serving information needs of various community welfare organizations.
Year
DOI
Venue
2018
10.1109/APWConCSE.2017.00030
2017 4th Asia-Pacific World Congress on Computer Science and Engineering (APWC on CSE)
Keywords
Field
DocType
Domestic-Violence,-Social-Media,-classification,-abuse,-machine-learning
Internet privacy,Social media,Information needs,Social issues,Binary classification,Computer science,Popularity,Knowledge management,Welfare,Domestic violence,Social Welfare
Journal
Volume
ISBN
Citations 
abs/1804.03497
978-1-5386-4531-4
0
PageRank 
References 
Authors
0.34
24
3
Name
Order
Citations
PageRank
Sudha Subramani100.34
Huy Quan Vu2437.99
Hua Wang3109077.62