Special Session on Sentiment Analysis in Social Media (SASM)
The 37th International Conference on Industrial, Engineering & Other Applications of Applied Intelligent Systems (IEA/AIE 2024), Hradec Kralove, Czech Republic, July 10 – July 12, 2024
The World Wide Web ushered in the development of websites and social networks, which have gradually become the main channels of information where people post and share their opinions on social issues. These opinions become a meaningful data source for policy-makers, investors, manufacturers, celebrities, and users. For example, the sentiments expressed in citizens’ views indicate to policy-makers whether their policies are suitable for the people, whether the people agree with and support them, and whether they would have to make adjustments to meet the needs of the people. By analyzing the sentiment expressed in users’ opinions about products, manufacturers develop an impression of whether their products are welcomed, whether consumers are dissatisfied and whether aspects of the products are rated as excellent or inadequate. Based on these impressions, they improve the quality and design of products to be more suitable for consumers’ tastes. For the users themselves, a psychological analysis expressed in the form of opinions by other users about a product enables them to identify products that meet their requirements. From that, they can make more effective decisions regarding product selection. Therefore, “Sentiment analysis is increasingly viewed as a vital task both from an academic and a commercial standpoint.” Accordingly, various methods have been proposed to develop and improve the performance of sentiment analysis, such as lexicon-based, machine learning, deep learning, graph neural networks, and hybrid. However, sentiment analysis still has many challenges.
Such justifications motivated us to propose the SASM session. We welcome the original, advanced, and state-of-the-art theoretical and applied contributions to the Sentiment Analysis field and its relevant issues.
Relevant topics include, but are not limited to, the following:
- Aspect-level sentiment analysis
- Sentence-level sentiment analysis
- Document-level sentiment analysis
- Deep learning-based sentiment analysis
- Graph convolutional networks-based sentiment analysis
- Fuzzy logic for sentiment analysis
- Collective intelligence for sentiment analysis
- Multimodal sentiment analysis
- Multi-domain sentiment analysis
- Multilingual sentiment analysis
- Sentiment analysis for recommender systems
- Sentiment analysis for fake news detection
- Sentiment analysis for decision-making
- New datasets for sentiment analysis
- Real-time sentiment analysis
|Paper submission:||December 15, 2023|
|Final Notification:||January 31, 2024|
|Camera Ready Copy:||April 2024|
|Conference Sessions:||April 2024|
- Prof. Ngoc Thanh Nguyen, Department of Applied Informatics, Wroclaw University of Science and Technology, Poland
- Dr. Huyen Trang Phan, Faculty of Information Technology, Nguyen Tat Thanh University, Ho Chi Minh, Vietnam
The conference proceedings will be published by Springer in the Lecture Notes in Artificial Intelligence (LNCS/LNAI) series. A paper will be accepted either as a long or as a short paper. Long papers will be allocated 12 pages while short papers will be allocated 6 pages in the proceedings.
Papers must be written by using the Springer template (https://www.springer.com/gp/computer-science/lncs). The submissions will go through a double blind review for originality and scientific quality.
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