TAILIEUCHUNG - An empirical study of Vietnamese sentiment analysis

Sentiment Analysis is the area of research that studies people’s opinions, sentiments, evaluations, attitudes and emotions from written text. This has become one of the most active research fields in Natural Language Processing. In recent years, sentiment analysis for Vietnamese text has received a considerable attention. | Công nghệ thông tin Cơ sở toán học cho tin học AN EMPIRICAL STUDY OF VIETNAMESE SENTIMENT ANALYSIS Nguyen Hoang Quan Le Dinh Son Nguyen Quang Uy Abstract Sentiment Analysis is the area of research that studies people s opinions sentiments evaluations attitudes and emotions from written text. This has become one of the most active research fields in Natural Language Processing. In recent years sentiment analysis for Vietnamese text has received a considerable attention. In the fourth international workshop on Vietnamese language and speech processing there was a competition between various researchers in solving this problem based on a benchmark dataset provided by the workshop committee. However each researcher address the problem with different methods. In this paper we present a comparison of a large number of machine learning algorithms for tackling this problem. The results of the experiments help to gain insight into the ability of various machine learning algorithms when used for Vietnamese sentiment analysis. Keywords Sentiment analysis Opinion mining Machine learning. 1. INTRODUCTION Sentiment analysis is the task of determining user s opinion about products movies events or policies etc. In this topic sentiment classification is one of the most important task aiming to classify opinion of a sentence or document into several categories such as positive negative and neutral. Predicting user s sentiment is extremely important because the user s opinion becomes more and more value. The public interest is the main factor that affects the profit of products like movies books etc. Subsequently this problem is the interest of both researchers and companies. For a comprehensive survey of sentiment analysis and opinion mining readers are refered to 1 . The major tasks in sentiment analysis include Subjective classification aims to classify subjectivity and objectivity documents. Polarity sentiment classification aims to classify an subjectivity document into one of

• Kỹ thuật lập trình
• Sentiment analysis
• Opinion mining
• Machine learning
• Vietnamese sentiment analysis
• Natural Language Processing
• Sentiment analysis for opinions on social media
• Types of sentiment analysis
• Challenges in sentiment analysis
• Social media platforms
• Valuable data source
• Aspect based sentiment analysis
• Text analysis
• Vietnamese Language and Speech Processing
• Shared task
• VLSP workshop
• Online crisis detection
• Burst detection
• Aspect oriented sentiment ontology
• Online social media
• Information sciences
• Multi dimensional relation model
• Dimensional sentiment analysis
• Valence arousal irony ratings
• A System for Real time Twitter Sentiment Analysis
• 2012 U
• Hao Wang
• báo cáo khoa học
• báo cáo ngôn ngữ
• ngôn ngữ tự nhiên
• A Bilingual Context Mining
• Sentiment Analysis Summarization System
• Wen Tai Hsieh
• Multilingual Subjectivity
• Rada Mihalcea
• A study of Information
• Retrieval weighting schemes
• Semi supervised latent variable models
• sentence level sentiment analysis
• Long Papers
• Subjectivity and Sentiment Analysis
• Modern Standard Arabic
• Mohammed Korayem
• Sentiment Analysis of Citations
• Sentence Structure Based Features
• Awais Athar
• Discovering the Discriminative Views
• Measuring Term Weights
• xử lý ngôn ngữ tự nhiên
• Learning Word Vectors
• Andrew L
• Maas
• Structured Models
• Fine to Coarse Sentiment Analysis
• Ryan McDonald
• mô hình ngôn ngữ
• A Sentimental Education
• Sentiment Analysis Using Subjectivity Summarization
• Minimum Cuts
• Incorporating topic information
• sentiment analysis models
• Tony Mullen
• Comparative sentences
• Support vector machines
• Conditional random fields
• Convolution neural network
• Deep learning
• Long short term memory
• Sentimental approaches
• Word embedding
• Decision tree
• Voting Classifier
• Nearest Neighbor
• Support Vector Machine
• Investor sentiment
• Principal component analysis
• Stock returns
• Market states
• Stock returns in Taiwan’s stock market
• Word to vector (Word2vec)
• Parts of speech (POS)
• Representation learning
• Comment analysis for product and service satisfaction
• Thai customers’ review in social network
• Clarify the problem
• Mining Thai customers’ opinions
• The Thai language
• Sentiment analysis techniques
• Public service
• Social listening
• Public health services
• Dissatisfaction towards public services