A field study on real-time self-reported emotions in crowds

Abstract

Crowd experience is inevitable in daily life. Crowd managers need tools to accurately estimate the psychological aspects of crowds, an important one being crowd emotion. In this study, we explore the feasibility of obtaining a real-time, dynamic map of crowd emotions through self-reporting by crowd members. To this end, a smart phone application “EmoApp” was developed. EmoApp allows users to report their emotions without interfering with their on-going activities. We conducted a field study to test EmoApp in a music festival. The collected data revealed that the users’ movements and emotional changes were consistent with the activities at the festival. This suggests that a majority of the users reported their real emotions. The paper also discussed several aspects of emotion detection, namely, privacy protection, reliability of self-report method, accuracy of positioning users and user-friendliness of the application design. This study is part of the on-going research in understanding the psychological aspects of crowds.