Emotion and sentiment in social and expressive media: Introduction to the special issue

Social and expressive media represent a challenge and a push forward for research on emotion and sentiment analysis. The advent of social media has brought about new paradigms of interaction that foster first-person engagement and crowdsourced contents: the subjective dimension moves to the foreground, opening the way to the emergence of an affective component within a dynamic corpus of digitized contents created and enriched by the users. Expressive media, which play a key role in fields related to creativity, such as figurative arts, music or drama, gather multimedia contents into online social environments, by joining the social dimension with the aims of artistic creation and self-expression. Artistic creation and performance seem to be a very interesting testbed for cross-validating and possibly integrating approaches, models and tools for automatically analyzing emotion and sentiment. In fact, in such contexts the social and affective dimensions (emotions and feelings) naturally emerge (Silvia, 2005), think for instance of the visitors’ feedback to a real or virtual art exhibition, or of the audience–performance interaction. Social and expressive media generate – in a continuous loop of interaction between online environments and the community of users – new digitized contents, including spontaneous, multi-faceted and unstructured user responses. This advocates new techniques for automatic processing, indexing and retrieval of the affective and subjective information conveyed. The automatic analysis of the opinions and of the affective component expressed in such data, in fact, poses special challenges, since it involves a deep understanding of natural language texts by the computational systems, from which we are still far (Cambria et al., 2013). Approaches enabling contextand concept-based analysis can lead to a better understanding of opinions expressed in textual data, so as to reduce the gap between unstructured information and structured machine-processable data. Moreover, the focus on multimedia contents calls for the development of new techniques for automatic extraction and classification of affective information, where both textual and extra-linguistic features can be exploited and combined via multimodal approaches (Mihalcea & Strapparava, 2012; Sartori et al., 2015). Another key aspect to consider in order to bring advancements in this field is related to the role of cognitive models of emotions. Affective models that encompass the expressive aims of social and expressive media, need to be defined and integrated into traditional techniques of analysis and information processing. In fact, generation and manipulation of produced contents, for distribution, categorization, browsing or visualization must be equipped with a proper model of their affective qualities – and of their reception by the users – especially when the practical goal of assembling and delivering to the users contents in a personalized way is pursued. In this context, studying emotion representations that enable semantic metadata processing is also an important issue to face in order to foster the interoperability and integration of affect processing tools. In light of these considerations, this special issue focuses on the presentation and discussion of a set of novel computational approaches to the analysis of emotion and sentiment in social and expressive media.