title: A Unified Framework for Creating Domain Dependent Polarity Lexicons from User Generated Reviews.
abstract: The exponential increase in the explosion of Web-based user generated reviews has resulted in the emergence of Opinion Mining (OM) applications for analyzing the users' opinions toward products, services, and policies. The polarity lexicons often play a pivotal role in the OM, indicating the positivity and negativity of a term along with the numeric score. However, the commonly available domain independent lexicons are not an optimal choice for all of the domains within the OM applications. The aforementioned is due to the fact that the polarity of a term changes from one domain to other and such lexicons do not contain the correct polarity of a term for every domain. In this work, we focus on the problem of adapting a domain dependent polarity lexicon from set of labeled user reviews and domain independent lexicon to propose a unified learning framework based on the information theory concepts that can assign the terms with correct polarity (+ive, -ive) scores. The benchmarking on three datasets (car, hotel, and drug reviews) shows that our approach improves the performance of the polarity classification by achieving higher accuracy. Moreover, using the derived domain dependent lexicon changed the polarity of terms, and the experimental results show that our approach is more effective than the base line methods.
authors.affiliation: Institute of Computing and Information Technology (ICIT), Gomal University, Dera Ismail Khan, Pakistan.
authors.forename: Muhammad Zubair
authors.initials: MZ
authors.lastname: Asghar
authors.affiliation: Institute of Engineering and Computer Science, University of Science and Technology, Bannu, Pakistan.
authors.forename: Aurangzeb
authors.initials: A
authors.lastname: Khan
authors.affiliation: Faculty of Computing and Information Technology, King Abdul Aziz University (KAU), Rabigh, Saudi Arabia.
authors.forename: Shakeel
authors.initials: S
authors.lastname: Ahmad
authors.affiliation: COMSATS Institute of Information Technology, Abbottabad, Pakistan.
authors.forename: Imran Ali
authors.initials: IA
authors.lastname: Khan
authors.affiliation: Institute of Computing and Information Technology (ICIT), Gomal University, Dera Ismail Khan, Pakistan.
authors.forename: Fazal Masud
authors.initials: FM
authors.lastname: Kundi
mesh_terms: D000465:Algorithms; D008962:Models, Theoretical