A Survey on Multimodal Aspect-Based Sentiment Analysis
Multimodal Aspect-Based Sentiment Analysis (MABSA), as an emerging task in the field of sentiment analysis, has recently received widespread attention. Its aim is to combine relevant multimodal data to determine the sentiment polarity of a given aspect in text. Researchers have surveyed both aspect-...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2024-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10401113/ |
| _version_ | 1827374272079724544 |
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| author | Hua Zhao Manyu Yang Xueyang Bai Han Liu |
| author_facet | Hua Zhao Manyu Yang Xueyang Bai Han Liu |
| author_sort | Hua Zhao |
| collection | DOAJ |
| description | Multimodal Aspect-Based Sentiment Analysis (MABSA), as an emerging task in the field of sentiment analysis, has recently received widespread attention. Its aim is to combine relevant multimodal data to determine the sentiment polarity of a given aspect in text. Researchers have surveyed both aspect-based sentiment analysis and multimodal sentiment analysis, but, to the best of our knowledge, there is no survey on MABSA. Therefore, in order to assist related researchers to know MABSA better, we surveyed the research work on MABSA in recent years. Firstly, the relevant concepts of MABSA were introduced. Secondly, the existing research methods for the two subtasks of MABSA research (that is, multimodal aspect sentiment classification and aspect sentiment pairs extraction) were summarized and analyzed, and the advantages and disadvantages of each type of method were analyzed. Once again, the commonly used evaluation corpus and indicators for MABSA were summarized, and the evaluation results of existing research methods on the corpus were also compared. Finally, the possible research trends for MABSA were envisioned. |
| first_indexed | 2024-03-08T11:31:52Z |
| format | Article |
| id | doaj.art-f559d7305c4141f7a54ba1ff23e64472 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-03-08T11:31:52Z |
| publishDate | 2024-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-f559d7305c4141f7a54ba1ff23e644722024-01-26T00:01:33ZengIEEEIEEE Access2169-35362024-01-0112120391205210.1109/ACCESS.2024.335484410401113A Survey on Multimodal Aspect-Based Sentiment AnalysisHua Zhao0https://orcid.org/0000-0001-6467-6892Manyu Yang1https://orcid.org/0009-0000-7773-8394Xueyang Bai2https://orcid.org/0009-0008-3086-4279Han Liu3College of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao, ChinaCollege of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao, ChinaCollege of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao, ChinaCollege of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao, ChinaMultimodal Aspect-Based Sentiment Analysis (MABSA), as an emerging task in the field of sentiment analysis, has recently received widespread attention. Its aim is to combine relevant multimodal data to determine the sentiment polarity of a given aspect in text. Researchers have surveyed both aspect-based sentiment analysis and multimodal sentiment analysis, but, to the best of our knowledge, there is no survey on MABSA. Therefore, in order to assist related researchers to know MABSA better, we surveyed the research work on MABSA in recent years. Firstly, the relevant concepts of MABSA were introduced. Secondly, the existing research methods for the two subtasks of MABSA research (that is, multimodal aspect sentiment classification and aspect sentiment pairs extraction) were summarized and analyzed, and the advantages and disadvantages of each type of method were analyzed. Once again, the commonly used evaluation corpus and indicators for MABSA were summarized, and the evaluation results of existing research methods on the corpus were also compared. Finally, the possible research trends for MABSA were envisioned.https://ieeexplore.ieee.org/document/10401113/Multimodal aspect-based sentiment analysismultimodal aspect sentiment classificationaspect sentiment pairs extraction |
| spellingShingle | Hua Zhao Manyu Yang Xueyang Bai Han Liu A Survey on Multimodal Aspect-Based Sentiment Analysis IEEE Access Multimodal aspect-based sentiment analysis multimodal aspect sentiment classification aspect sentiment pairs extraction |
| title | A Survey on Multimodal Aspect-Based Sentiment Analysis |
| title_full | A Survey on Multimodal Aspect-Based Sentiment Analysis |
| title_fullStr | A Survey on Multimodal Aspect-Based Sentiment Analysis |
| title_full_unstemmed | A Survey on Multimodal Aspect-Based Sentiment Analysis |
| title_short | A Survey on Multimodal Aspect-Based Sentiment Analysis |
| title_sort | survey on multimodal aspect based sentiment analysis |
| topic | Multimodal aspect-based sentiment analysis multimodal aspect sentiment classification aspect sentiment pairs extraction |
| url | https://ieeexplore.ieee.org/document/10401113/ |
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