Start Date
12-13-2015
Description
In 2013 Facebook launched a feature allowing users to add a feeling tag to their posts. We have collected 18 months worth of such public posts. Our aim is to map the semantic space of ‘Facebook feelings’ to understand patterns in how feelings are tagged and how they can be described in terms of valence and arousal. Our findings reveal temporal and social patterns in the most commonly shared feelings. In line with the ‘exhibitional’ nature of Facebook, our analyses indicate that ‘extreme’ feelings, such as excitement and anger, may be expressed in even more extreme levels of both valence and arousal. Facebook also provides novel emotional scripts (e.g., “meh”) that help people express feelings in ways that traditionally socialized feelings do not. This understanding of the semantic space of ‘Facebook feelings’ ultimately serves to inform the development of an automatic ‘Feelings Meter’.
Recommended Citation
Zimmerman, Christopher; Stein, Mari-Klara; Hardt, Daniel; and Vatrapu, Ravi, "Emergence of Things Felt: Harnessing the Semantic Space of Facebook Feeling Tags" (2015). ICIS 2015 Proceedings. 20.
https://aisel.aisnet.org/icis2015/proceedings/HumanBehaviorIS/20
Emergence of Things Felt: Harnessing the Semantic Space of Facebook Feeling Tags
In 2013 Facebook launched a feature allowing users to add a feeling tag to their posts. We have collected 18 months worth of such public posts. Our aim is to map the semantic space of ‘Facebook feelings’ to understand patterns in how feelings are tagged and how they can be described in terms of valence and arousal. Our findings reveal temporal and social patterns in the most commonly shared feelings. In line with the ‘exhibitional’ nature of Facebook, our analyses indicate that ‘extreme’ feelings, such as excitement and anger, may be expressed in even more extreme levels of both valence and arousal. Facebook also provides novel emotional scripts (e.g., “meh”) that help people express feelings in ways that traditionally socialized feelings do not. This understanding of the semantic space of ‘Facebook feelings’ ultimately serves to inform the development of an automatic ‘Feelings Meter’.