Work

The Arousal Video Game AnnotatIoN (AGAIN) Dataset

Year: 2022

Type: article

Abstract: How can we model affect in a general fashion, across dissimilar tasks, and to which degree are such general representations of affect even possible? To address such questions and enable research towardsgeneralaffective computing, this paper introduces The Arousal video Game AnnotatIoN (AGAIN) dataset. AGAIN is a large-scale affective corpus that features over 1,100 in-game videos (with corresponding gameplay data) from nine different games, which are annotated for arousal from 124 participants in a first-person continuous fashion. Even though AGAIN is created for the purpose of investigating the generality of affective computing across dissimilar tasks, affect modelling can be studied within each of its 9 specific interactive games. To the best of our knowledge AGAIN is the largest—over 37 hours of annotated video and game logs—and most diverse publicly available affective dataset based on games as interactive affect elicitors.

Source: IEEE Transactions on Affective Computing

DOI: 10.1109/taffc.2022.3188851

Authors: David Melhart, Antonios Liapis, Georgios N. Yannakakis

Institution: University of Malta

Language: English

Topic: Emotion and Mood Recognition

Subfield: Experimental and Cognitive Psychology

Field: Psychology

Domain: Social Sciences

Open Access status: green

Funder: European Commission

Award: A European Excellence Centre for Media, Society and Democracy