Microblog Sentiment Analysis Model Based on Emoticons

2014 ◽  
pp. 127-135 ◽  
Author(s):  
Shaojie Pei ◽  
Lumin Zhang ◽  
Aiping Li
Keyword(s):  
Sentiment Analysis ◽  
Analysis Model ◽  
Model Based

Sentiment Analysis Model Based on the Word Structural Representation

2021 ◽  
pp. 170-178
Author(s):  
Gulmira Bekmanova ◽  
Banu Yergesh ◽  
Altynbek Sharipbay
Keyword(s):  
Sentiment Analysis ◽  
Analysis Model ◽  
Structural Representation ◽  
Model Based

Towards a Sentiment Analysis Model Based on Semantic Relation Analysis

2018 ◽  
Vol 9 (2) ◽  
pp. 54-75 ◽  
Author(s):  
Thien Khai Tran ◽  
Tuoi Thi Phan
Keyword(s):  
Sentiment Analysis ◽  
Semantic Relation ◽  
Effective Model ◽  
Analysis Model ◽  
Model Based ◽  
Relation Analysis ◽  
Novel Approaches ◽  
Syntactic Dependency

Sentiment analysis is an important new field of research that has attracted the attention not only of researchers, but also businesses and organizations. In this article, the authors propose an effective model for aspect-based sentiment analysis for Vietnamese. First, sentiment dictionaries and syntactic dependency rules were combined to extract reliable word pairs (sentiment - aspect). They then relied on ontology to group these aspects and determine the sentiment polarity of each. They introduce two novel approaches in this work: 1) in order to “smooth” the sentiment scaling (rather than using discrete categories of 1, 0, and -1) for fined-grained classification, then extract multi-word sentiment phrases instead of sentiment words, and 2) the focus is not only on adjectives but also nouns and verbs. Initial evaluations of the system using real reviews show promising results.

scholarly journals Towards a sentiment analysis model based on semantic relation analysis

2018 ◽  
Vol 20 (K7) ◽  
pp. 21-27
Author(s):  
Thien Khai Tran ◽  
Tuoi Thi Phan
Keyword(s):  
Sentiment Analysis ◽  
Semantic Relation ◽  
Effective Model ◽  
Analysis Model ◽  
Model Based ◽  
Sentiment Dictionary ◽  
Relation Analysis ◽  
Syntactic Dependency ◽  
Positive Results

In this paper, we propose an effective model for aspect-based sentiment analysis. First, we combined a sentiment dictionary and syntactic dependency rules to extract reliable word pairs (sentiment — aspect). Then, thanks to ontology, we grouped those aspects and determined the sentiment polarity of each. When we conducted experiments on real reviews, the system showed positive results.

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