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A transformation method for aspect based sentiment analysis

In this paper, we describe our system for this shared task. We employ a supervised learning method based on the Support Vector Machine classifiers combined with a variety of features. | Journal of Computer Science and Cybernetics V.34 N.4 2018 323-333 DOI 10.15625 1813-9663 34 4 13162 A TRANSFORMATION METHOD FOR ASPECT-BASED SENTIMENT ANALYSIS DANG VAN THIN VU DUC NGUYEN KIET VAN NGUYEN NGAN LUU THUY NGUYEN University of Information Technology Vietnam National University Ho Chi Minh thindv@uit.edu.vn Crossref Similarity Check Powered w ITheriliMte Abstract. Along with the explosion of user reviews on the Internet sentiment analysis has become one of the trending research topics in the field of natural language processing. In the last five years many shared tasks were organized to keep track of the progress of sentiment analysis for various languages. In the Fifth International Workshop on Vietnamese Language and Speech Processing VLSP 2018 the Sentiment Analysis shared task was the first evaluation campaign for the Vietnamese language. In this paper we describe our system for this shared task. We employ a supervised learning method based on the Support Vector Machine classifiers combined with a variety of features. We obtained the Fl-score of 61 for both domains which was ranked highest in the shared task. For the aspect detection subtask our method achieved 77 and 69 in Fl-score for the restaurant domain and the hotel domain respectively. Keywords. Sentiment analysis Aspect-based sentiment analysis Natural language processing Text analysis 1. INTRODUCTION The rapid development of the Internet brings many opportunities and challenges for companies in providing high-quality products or services. Internet has become a common channel for users to immediately share comments or experiences about the products or services they used. Hence the number of user reviews is increasing significantly day by day. For e-commerce companies taking care of user feedback is a necessity and they usually have a team to analyze and evaluate user reviews. With a large amount of data however manual analysis is not feasible. Sentiment Analysis SA is a research topic of .