Sentiment Analysis and eWOM Advancements with Deep Learning and Artificial Intelligence
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Computer Science & Engineering".
Deadline for manuscript submissions: closed (31 December 2024) | Viewed by 813
Special Issue Editors
Interests: multi-criteria decision-making models; sentiment analysis; recommender systems; data science applied to business, machine learning
Special Issues, Collections and Topics in MDPI journals
Interests: group decision making; consensus reaching processes; smart cities and citizen participation
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The purpose of this Special Issue is to delve deeply into sentiment analysis through the use of deep learning and artificial intelligence techniques in the context of consumer interactions on social media.
In the digital age, the exchange of opinions and reviews on online platforms has grown exponentially, leading to the emergence of electronic word of mouth (e-WOM), which significantly impacts users' purchasing decisions and their perceptions of products and services.
This Special Issue aims to explore how sentiment analysis can help companies to better understand consumer needs and preferences, identify areas for improvement in their products or services, and effectively segment their online audience. Artificial intelligence techniques such as deep learning and transformer models, which are essential for analyzing large volumes of data generated by users in natural language, will be explored. In summary, this Special Issue aspires to offer a comprehensive and updated insight into the impact and applications of sentiment analysis in the realm of e-WOM and business decision-making.
Dr. Ramón Carrasco
Dr. Francisco Mata
Guest Editors
Manuscript Submission Information
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Keywords
- sentiment analysis
- electronic word of mouth
- artificial intelligence
- deep learning
- natural language processing
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