Reprint

Application of Artificial Intelligence Methods in Processing of Emotions, Decisions and Opinions

Edited by
August 2024
238 pages
  • ISBN978-3-7258-1715-3 (Hardback)
  • ISBN978-3-7258-1716-0 (PDF)
https://doi.org/10.3390/books978-3-7258-1716-0 (registering)

This book is a reprint of the Special Issue Application of Artificial Intelligence Methods in Processing of Emotions, Decisions and Opinions that was published in

Biology & Life Sciences
Chemistry & Materials Science
Computer Science & Mathematics
Engineering
Environmental & Earth Sciences
Physical Sciences
Summary

During recent years, social infrastructure has become irreversibly linked to the Internet through its everyday manifestations, such as social networking services (Twitter, Facebook, etc.). Every second, this new tangible information-based reality provides large amounts of data filled with 1) emotional expressions; 2) people's opinions on various topics; and 3) their reasoning, revealing their decision-making processes. As these three categories are also closely interrelated with each other, they should be studied together to obtain a more robust view on all of the topics involved. This, as never before, provides an opportunity for the development and application of natural language processing methods, in particular those regarding such topics as emotion processing, decision-making, and opinion mining.

Format
  • Hardback
License and Copyright
© 2024 by the authors; CC BY-NC-ND license
Keywords
consumer decision-making; star rating; review comment; sentiment analysis; personality; automatic personality recognition; psychometrics; psycholinguistic features; machine learning; personality computing; sentiment analysis; emotion detection; pretrained language models; model adaptation; task-adaptation approach; emotion recognition; electroencephalogram; affective computing; genetic algorithms; RF; KNN; ANN; social network; natural language process; opinion tendency recognition; graph embedding; graph neural network; vulgar remark detection; vulgar term extraction; low-resource language; logistic regression; recurrent neural network; fake news; detection; dataset; social networks; MOOC; text mining; multi-attribute decision-making; course improvement; deep learning; short answer question; automatic short answer grading (ASAG); SentenceTransformers; dataset balancing; GPT; fine-tuning; decision-making process; decision strategy; knowledge representation; artificial intelligence; data clustering; n/a