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M.P.S. Bhatia

Work place: Computer Engineering Division, NSIT, Delhi University, New Delhi- INDIA

E-mail: mpsbhatia@nsit.ac.in

Website: https://orcid.org/0000-0001-7190-9770

Research Interests: Computational Learning Theory, Computer Architecture and Organization, Information Security, Network Security, Data Mining, Data Structures and Algorithms

Biography

Dr. M.P.S. Bhatia received his Ph.D. in Computer Science from the University of Delhi. Dr. Bhatia is a Professor in the Division of COE at the Netaji Subhas Institute of Technology, affiliated to the University of Delhi. He is also serving the Institute as Dean, Student Welfare and Head, Placement Cell. He has guided many M.Tech and Ph.D. students in their research work. His research interests include data mining, cyber security, semantic web, machine learning, social network analysis and sentiment analysis. He is an author or co-author of many research papers in international journals and conferences. Dr. Bhatia is a member of IEEE (Institute of Electrical and Electronics Engineers) and CSI (Computer Society of India).

Author Articles
Challenges with Sentiment Analysis of On-line Micro-texts

By Ritesh Srivastava M.P.S. Bhatia

DOI: https://doi.org/10.5815/ijisa.2017.07.04, Pub. Date: 8 Jul. 2017

With the evolution of World Wide Web (WWW) 2.0 and the emergence of many micro-blogging and social networking sites like Twitter, the internet has become a massive source of short textual messages called on-line micro-texts, which are limited to a few number of characters (e.g. 140 characters on Twitter). These on-line micro-texts are considered as real-time text streams. On-line micro-texts are extremely subjective; they contain opinions about various events, social issues, personalities, and products. However, despite being so voluminous in quantity, the qualitative nature of these micro-texts is very inconsistent. These qualitative inconsistencies of raw on-line micro-texts impose many challenges in sentiment analysis of on-line micro-texts by using the established methods of sentiment analysis of unstructured reviews. This paper presents many challenges and issues observed during sentiment analysis of On-line Micro-texts.

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