Sentiment Analysis of Medium and Long Text Based on Feature Fusion Model Article Swipe
Changchun Yang
,
Cong Cai
,
Tongguang Ni
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.26855/acc.2023.04.002
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.26855/acc.2023.04.002
At present, the research on microblog short text has reached saturation, while the middle and long text sentences are complex and have many emotional words, which makes it difficult to classify the whole sentence.In order to solve the problem that the emotional feature extraction is not sufficient in the current micro-blog long text sentiment analysis task, which leads to the inability to extract the text sentiment semantics comprehensively, a multi-feature fusion sentiment analysis method (MBEA) combining capsule network, multi-layer bidirectional long short-term memory network and residual network is proposed.This method uses the Word2vec model to generate word vectors, and then inputs the word vectors into the residual network, capsule network and multi-layer bidirectional long-term and short-term memory network to obtain their vector feature representations respectively.Finally, the fully connected layer is input, and the emotion discrimination is performed by the softmax activation function.Experiments on COVID Dataset and Financial Dataset verify the accuracy and effectiveness of the model compared with other baseline models of sentiment analysis.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.26855/acc.2023.04.002
- https://www.hillpublisher.com/ArticleDetails.aspx?type=PDF&cid=1685
- OA Status
- bronze
- Cited By
- 1
- References
- 5
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4380263621
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4380263621Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.26855/acc.2023.04.002Digital Object Identifier
- Title
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Sentiment Analysis of Medium and Long Text Based on Feature Fusion ModelWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2023Year of publication
- Publication date
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2023-06-08Full publication date if available
- Authors
-
Changchun Yang, Cong Cai, Tongguang NiList of authors in order
- Landing page
-
https://doi.org/10.26855/acc.2023.04.002Publisher landing page
- PDF URL
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https://www.hillpublisher.com/ArticleDetails.aspx?type=PDF&cid=1685Direct link to full text PDF
- Open access
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YesWhether a free full text is available
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bronzeOpen access status per OpenAlex
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https://www.hillpublisher.com/ArticleDetails.aspx?type=PDF&cid=1685Direct OA link when available
- Concepts
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Feature (linguistics), Sentiment analysis, Artificial intelligence, Fusion, Computer science, Natural language processing, Pattern recognition (psychology), Linguistics, PhilosophyTop concepts (fields/topics) attached by OpenAlex
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1Total citation count in OpenAlex
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2024: 1Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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