Sentiment Analysis and Affective Computing

Dear Colleagues,

The publication of contents, personal experiences and opinions about anything in social media (forums, blogs, social networks, etc.) has aroused great interest in Sentiment Analysis and Affective Computing, since they provide substantial benefits for different sectors. These disciplines are concerned with the study of the opinions, emotional states and human-behaviour expressed in texts.  The automatic detection of this information is of great value for improving business strategies according to the opinions and emotions of customers, detecting signs of depression, identifying cases of cyber-bullying, hate speech or toxic comments, or even for the development of efficient e-learning systems based on student’s emotions.

Although deep learning models are providing breakthrough results in conjunction with large datasets, Sentiment Analysis and Affective Computing are still challenging areas of Natural Language Processing, because these large datasets are not always available.

This special issue is aimed at theoretical or experimental works on Sentiment Analysis or Affective Computing in social media, for languages with limited resources, methods to analyze social behaviors, processing linguistic phenomena (negation, irony, sarcasm, etc.), hate-speech detection, fine-grained sentiment analysis, identification of psychological states such as depression, domain-dependent information, transfer learning issues, multilingual aspects, personalized sentiment analysis,  etc.

Topics of interest include but are not limited to:

• Aspect-based sentiment analysis
• Multilingual sentiment analysis
• Personalized sentiment analysis
• Sentiment analysis or affective computing in languages with few resources
• Resources for sentiment analysis or affective computing
• Negation processing for improving sentiment analysis or affective computing
• Irony or sarcasm detection for improving sentiment analysis or affective computing
• Transfer learning for sentiment analysis or affective computing
• Emotion mining in social media
• Hate-speech detection
• Identification of psychological states such as depression
• Cyber-bullying detection
• Offensive language identification

Dr. Salud María Jiménez-Zafra
Dr. Miguel Ángel García Cumbreras
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Information is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.