Dr. Arturo Martínez-Rodrigo, Universidad de Castilla-La Mancha (Spain)

Dr. Antonio Fernández-Caballero, Universidad de Castilla-La Mancha (Spain)


Emotions are essential in human-human communication, cognition, learning and rational decision-making processes. However, human-machine interfaces (HMIs) are still not able to understand human sentiments and react accordingly. With the aim of endowing HMIs with the emotional intelligence they lack of, the Affective Computing science focuses on the development of artificial intelligence by means of the analysis of affects and emotions, such that systems and devices could be able to recognize, interpret, process and simulate human sentiments.

Nowadays, the evaluation of electrophysiological signals plays a key role in the advancement towards that purpose since they are an objective representation of the emotional state of an individual. Hence, the interest in physiological variables like electroencephalogram, electrocardiogram, or electrodermal activity, among many others, has notably grown in the field of affective states detection. Furthermore, emotions have also been widely identified by means of the assessment of speech characteristics and facial gestures of people under different sentimental conditions. It is also worth noting that the development of algorithms for the classification of affective states in social media has experienced a notable increase in the last years. In this sense, language of posts included in social networks, such as Facebook or Twitter, is evaluated with the aim of detecting sentiments of the users of those media tools.

This IWINAC 2019 special session on Affective Computing and Sentiment Analysis is intended to be a meeting point for researchers that are interested in any of those areas of expertise related to sentiment analysis, and want to initiate their studies or are currently working on these topics. Hence, manuscripts introducing new proposals based on the analysis of physiological measures, facial recognition, speech recognition, or natural language processing in social media are welcome in this special session on affective computing and sentiment analysis.

Topics areas include (but are not restricted to):

  • Affective Computing
  • Sentiment Analysis
  • Ubiquitous and Pervasive Computing
  • Ambient Intelligence
  • Ambient Assisted Living
  • Physiological Computing
  • Internet of Things
  • Social Media
  • Natural Language Processing
  • Opinion Mining
  • Emotional Models Design
  • Maps of Controversy
  • Brain-Computer Interfaces
  • Biofeedback and Neurofeedback Systems
  • Wearable Systems
  • Applications and Case Studies