Year: 2023
Type: article
Abstract: We describe the creation of an affective film dataset for researchers interested in studying a broad spectrum of emotional experiences. Two hundred twenty-two 60-seconds long video clips were selected based on multimedia content analysis and screened in the lab with 407 participants. The participants' ratings mapped to 31 emotion categories in the first stage. Based on the selection criteria, 69 audio-visual clips were selected. These selected affective clips were then presented to 271 participants. Participants rated these clips on rating scales and categorized them into emotion categories. The affective clips were able to induce 19 basic and complex emotion categories reliably. Since the presented dataset is comprised of film clips based on both Indian and western content, the dataset can effectively be used for cross-cultural emotion research. From the dataset, researchers can select emotional movie clips based on the ratings and quantitative measures, including the reliability measures presented in this work. We also show a continuity of emotional experiences using an advanced visualisation technique to complement the existing knowledge based on V-A space with the information on how the transitions among emotion categories are taking place.
Language: English
Topic: Emotion and Mood Recognition
Subfield: Experimental and Cognitive Psychology
Field: Psychology
Domain: Social Sciences
Open Access status: green
Funder: Arizona State University
OpenAlex ID: W4387770599