The advent of Web 2.0 has enabled a host of platforms for the creation and dissemination of content, which offers unique opportunities to understand users’ opinions, intentions and expression through the content they publish and/or consume.
Affect analysis on content, specifically text, to understand the author/reader is a upcoming research area, with work that spans multiple disciplines. For instance, research in sentiment and emotion analysis has focused on measuring the evoked as well as the expressed dimension in published content. Psychology and Consumer Behavior research defines theories to capture other dimensions of evoked affect, such as behavioral and cognitive responses in users. Affective
Computing research aims to capture human reactions through multiple sensor data. This workshop aims at bringing together researchers in the field of psycho-linguistics, computational linguistics, HCI, and Consumer Behavior analysis
for stimulating discussions on the open research problems in this space with a focus on language and text. Computational models for the consumer behavior theories using linguistics and machine learning approaches present a huge opportunity to build intelligent systems that understand human reactions. The proposed workshop is focused around this aspect of Affective Content Understanding and analysis. The AffCon workshop will incorporate multiple invited talks, papers sessions, a poster session, and a session on bringing together multi-disciplinary resources, both data and algorithms in this