The Affective Dynamics of Everyday Digital Life: Opening Computational Possibility.

ABSTRACT: Up to now, there was no way to observe and track the affective impacts of the massive amount of complex visual stimuli that people encounter "in the wild" during their many hours of digital life. In this paper, we propose and illustrate how recent advances in AI-trained ensembles of deep neural networks-can be deployed on new data streams that are long sequences of screenshots of study participants' smartphones obtained unobtrusively during everyday life. We obtained affective valence and arousal ratings of hundreds of images drawn from existing picture repositories often used in psychological studies, and a new screenshot repository chronicling individuals' everyday digital life from both N = 832 adults and an affect computation model (Parry & Vuong, 2021). Results and analysis sug

SUBMITTER: Rocklin ML 

PROVIDER: S-EPMC10514010 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature