Multi-modal Public Opinion Analysis Based on Image and Text Fusion
Due to the continuous popularization of the Internet and mobile phones, people have gradually entered a participatory network era. More and more people like to publish their opinions, comments and emotions through text and image on the Internet. Effective analysis of these text and image information...
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| Format: | Article |
| Language: | zho |
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Journal of Computer Engineering and Applications Beijing Co., Ltd., Science Press
2022-06-01
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| Series: | Jisuanji kexue yu tansuo |
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| Online Access: | http://fcst.ceaj.org/fileup/1673-9418/PDF/2110056.pdf |
| _version_ | 1811241759992184832 |
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| author | LIU Ying, WANG Zhe, FANG Jie, ZHU Tingge, LI Linna, LIU Jiming |
| author_facet | LIU Ying, WANG Zhe, FANG Jie, ZHU Tingge, LI Linna, LIU Jiming |
| author_sort | LIU Ying, WANG Zhe, FANG Jie, ZHU Tingge, LI Linna, LIU Jiming |
| collection | DOAJ |
| description | Due to the continuous popularization of the Internet and mobile phones, people have gradually entered a participatory network era. More and more people like to publish their opinions, comments and emotions through text and image on the Internet. Effective analysis of these text and image information can not only help companies better improve the quality of their products, but also provide guidance for government decision-making and social production and life. This paper summarizes the sentiment analysis of online public opinion based on multi-modal image and text fusion. Firstly, it summarizes the basic concepts of public opinion analysis. Secondly, it explains the process of single-modal text and visual sentiment analysis on social media. Thirdly, it summarizes the public opinion analysis algorithms based on image and text fusion, and divides the algorithms into feature layer fusion, decision layer fusion and linear regression model according to different fusion strategies. In addition, it summarizes the commonly used multi-modal sentiment analysis for social media dataset. Finally, the difficulties of online opinion analysis and future research directions are discussed. |
| first_indexed | 2024-04-12T13:40:59Z |
| format | Article |
| id | doaj.art-3b77ec3338544ce39ae3f232775240af |
| institution | Directory Open Access Journal |
| issn | 1673-9418 |
| language | zho |
| last_indexed | 2024-04-12T13:40:59Z |
| publishDate | 2022-06-01 |
| publisher | Journal of Computer Engineering and Applications Beijing Co., Ltd., Science Press |
| record_format | Article |
| series | Jisuanji kexue yu tansuo |
| spelling | doaj.art-3b77ec3338544ce39ae3f232775240af2022-12-22T03:30:50ZzhoJournal of Computer Engineering and Applications Beijing Co., Ltd., Science PressJisuanji kexue yu tansuo1673-94182022-06-011661260127810.3778/j.issn.1673-9418.2110056Multi-modal Public Opinion Analysis Based on Image and Text FusionLIU Ying, WANG Zhe, FANG Jie, ZHU Tingge, LI Linna, LIU Jiming01. Center for Image and Information Processing, Xi’an University of Posts and Telecommunications, Xi’an 710121, China;2. Key Laboratory of Electronic Information Application Technology for Crime Scene Investigation, Ministry of Public Security, Xi’an University of Posts and Telecommunications, Xi’an 710121, China;3. Network Public Opinion Monitoring and Analysis Center, Xi’an University of Posts and Telecommunications, Xi’an 710121, China;4. School of Communications and Information Engineering, Xi’an University of Posts and Telecommunications, Xi’an 710121, ChinaDue to the continuous popularization of the Internet and mobile phones, people have gradually entered a participatory network era. More and more people like to publish their opinions, comments and emotions through text and image on the Internet. Effective analysis of these text and image information can not only help companies better improve the quality of their products, but also provide guidance for government decision-making and social production and life. This paper summarizes the sentiment analysis of online public opinion based on multi-modal image and text fusion. Firstly, it summarizes the basic concepts of public opinion analysis. Secondly, it explains the process of single-modal text and visual sentiment analysis on social media. Thirdly, it summarizes the public opinion analysis algorithms based on image and text fusion, and divides the algorithms into feature layer fusion, decision layer fusion and linear regression model according to different fusion strategies. In addition, it summarizes the commonly used multi-modal sentiment analysis for social media dataset. Finally, the difficulties of online opinion analysis and future research directions are discussed.http://fcst.ceaj.org/fileup/1673-9418/PDF/2110056.pdf|network public opinion analysis|image and text fusion|sentiment analysis|multi-modal |
| spellingShingle | LIU Ying, WANG Zhe, FANG Jie, ZHU Tingge, LI Linna, LIU Jiming Multi-modal Public Opinion Analysis Based on Image and Text Fusion Jisuanji kexue yu tansuo |network public opinion analysis|image and text fusion|sentiment analysis|multi-modal |
| title | Multi-modal Public Opinion Analysis Based on Image and Text Fusion |
| title_full | Multi-modal Public Opinion Analysis Based on Image and Text Fusion |
| title_fullStr | Multi-modal Public Opinion Analysis Based on Image and Text Fusion |
| title_full_unstemmed | Multi-modal Public Opinion Analysis Based on Image and Text Fusion |
| title_short | Multi-modal Public Opinion Analysis Based on Image and Text Fusion |
| title_sort | multi modal public opinion analysis based on image and text fusion |
| topic | |network public opinion analysis|image and text fusion|sentiment analysis|multi-modal |
| url | http://fcst.ceaj.org/fileup/1673-9418/PDF/2110056.pdf |
| work_keys_str_mv | AT liuyingwangzhefangjiezhutinggelilinnaliujiming multimodalpublicopinionanalysisbasedonimageandtextfusion |