Automatically Learning Patterns in Subjectivity Classification for Vietnamese

Dang, Tran-Thai; Huong, Nguyen Thi Xuan; Le, Anh-Cuong; Huynh, Van–Nam

doi:10.1007/978-3-319-11680-8_50

Cited by 2 publications

(5 citation statements)

References 9 publications

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“…One of the main tasks involved in sentiment analysis (SA) is subjectivity classification. The main aim is to classify documents or sentences into one of the two classes; objective or subjective [17]. Usually, when dealing with SA, the sentences in the text are labeled as subjective and objective.…”

Section: ) Subjectivity Classificationmentioning

confidence: 99%

“…In this process of SA, subjective sentences are important to the process since they contain sentiments or opinions. The views perspectives, assessments, values, claim thoughts, observations, personal beliefs, and opinions of individuals are expressed in subjective sentences [17]. These types of sentences are classified into different classes, which may be positive, negative, or neutral.…”

Section: ) Subjectivity Classificationmentioning

confidence: 99%

See 1 more Smart Citation

Sentiment Analysis or Opinion Mining: A Review

Saad¹,

Saberi²

2017

International Journal on Advanced Science, Engineering and Information Technology

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Opinion Mining (OM) or Sentiment Analysis (SA) can be defined as the task of detecting, extracting and classifying opinions on something. It is a type of the processing of the natural language (NLP) to track the public mood to a certain law, policy, or marketing, etc. It involves a way that development for the collection and examination of comments and opinions about legislation, laws, policies, etc., which are posted on the social media. The process of information extraction is very important because it is a very useful technique but also a challenging task. That mean, to extract sentiment from an object in the web-wide, need to automate opinion-mining systems to do it. The existing techniques for sentiment analysis include machine learning (supervised and unsupervised), and lexical-based approaches. Hence, the main aim of this paper presents a survey of sentiment analysis (SA) and opinion mining (OM) approaches, various techniques used that related in this field. As well, it discusses the application areas and challenges for sentiment analysis with insight into the past researcher's works.

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Section: ) Subjectivity Classificationmentioning

confidence: 99%

Section: ) Subjectivity Classificationmentioning

confidence: 99%

Sentiment Analysis or Opinion Mining: A Review

Saad¹,

Saberi²

2017

International Journal on Advanced Science, Engineering and Information Technology

View full text Add to dashboard Cite

show abstract

“…The views perspectives, assessments, values, claim thoughts, observations, personal beliefs, and opinions of individuals are expressed in subjective sentences [17]. These types of sentences are classified into different classes, which may be positive, negative, or neutral.…”

Section: ) Subjectivity Classificationmentioning

confidence: 99%

“…There are numerous research studies on subjectivity classification as an individual issue [17]- [20]. In this way, objective sentences may be discarded, leaving only subjective sentences for analysis in terms of sentiments.…”

Section: ) Subjectivity Classificationmentioning

confidence: 99%

See 1 more Smart Citation

Sentiment Analysis or Opinion Mining: A Review

Saad¹,

Saberi²

2017

International Journal on Advanced Science, Engineering and Information Technology

View full text Add to dashboard Cite

Abstract-Opinion Mining (OM) or Sentiment Analysis (SA) can be defined as the task of detecting, extracting and classifying opinions on something. It is a type of the processing of the natural language (NLP) to track the public mood to a certain law, policy, or marketing, etc. It involves a way that development for the collection and examination of comments and opinions about legislation, laws, policies, etc., which are posted on the social media. The process of information extraction is very important because it is a very useful technique but also a challenging task. That mean, to extract sentiment from an object in the web-wide, need to automate opinion-mining systems to do it. The existing techniques for sentiment analysis include machine learning (supervised and unsupervised), and lexical-based approaches. Hence, the main aim of this paper presents a survey of sentiment analysis (SA) and opinion mining (OM) approaches, various techniques used that related in this field. As well, it discusses the application areas and challenges for sentiment analysis with insight into the past researcher's works.

show abstract

Automatically Learning Patterns in Subjectivity Classification for Vietnamese

Cited by 2 publications

References 9 publications

Sentiment Analysis or Opinion Mining: A Review

Sentiment Analysis or Opinion Mining: A Review

Sentiment Analysis or Opinion Mining: A Review

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