Topic Discovery and Hotspot Analysis of Sentiment Analysis of Chinese Text Using Information-Theoretic Method Article Swipe
Changlu Zhang
,
Haojie Fan
,
Jian Zhang
,
Qiong Yang
,
Liqian Tang
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.3390/e25060935
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.3390/e25060935
Currently, sentiment analysis is a research hotspot in many fields such as computer science and statistical science. Topic discovery of the literature in the field of text sentiment analysis aims to provide scholars with a quick and effective understanding of its research trends. In this paper, we propose a new model for the topic discovery analysis of literature. Firstly, the FastText model is applied to calculate the word vector of literature keywords, based on which cosine similarity is applied to calculate keyword similarity, to carry out the merging of synonymous keywords. Secondly, the hierarchical clustering method based on the Jaccard coefficient is used to cluster the domain literature and count the literature volume of each topic. Thirdly, the information gain method is applied to extract the high information gain characteristic words of various topics, based on which the connotation of each topic is condensed. Finally, by conducting a time series analysis of the literature, a four-quadrant matrix of topic distribution is constructed to compare the research trends of each topic within different stages. The 1186 articles in the field of text sentiment analysis from 2012 to 2022 can be divided into 12 categories. By comparing and analyzing the topic distribution matrices of the two phases of 2012 to 2016 and 2017 to 2022, it is found that the various categories of topics have obvious research development changes in different phases. The results show that: ① Among the 12 categories, online opinion analysis of social media comments represented by microblogs is one of the current hot topics. ② The integration and application of methods such as sentiment lexicon, traditional machine learning and deep learning should be enhanced. ③ Semantic disambiguation of aspect-level sentiment analysis is one of the current difficult problems this field faces. ④ Research on multimodal sentiment analysis and cross-modal sentiment analysis should be promoted.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/e25060935
- https://www.mdpi.com/1099-4300/25/6/935/pdf?version=1686713768
- OA Status
- gold
- Cited By
- 3
- References
- 12
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4380536659
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4380536659Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3390/e25060935Digital Object Identifier
- Title
-
Topic Discovery and Hotspot Analysis of Sentiment Analysis of Chinese Text Using Information-Theoretic MethodWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-06-13Full publication date if available
- Authors
-
Changlu Zhang, Haojie Fan, Jian Zhang, Qiong Yang, Liqian TangList of authors in order
- Landing page
-
https://doi.org/10.3390/e25060935Publisher landing page
- PDF URL
-
https://www.mdpi.com/1099-4300/25/6/935/pdf?version=1686713768Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://www.mdpi.com/1099-4300/25/6/935/pdf?version=1686713768Direct OA link when available
- Concepts
-
Computer science, Sentiment analysis, Jaccard index, Information retrieval, Microblogging, Topic model, Cluster analysis, Social media, Cosine similarity, Data mining, Data science, Artificial intelligence, World Wide WebTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
3Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 1, 2024: 2Per-year citation counts (last 5 years)
- References (count)
-
12Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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