Sharing Emotions at Scale: The Vent Dataset


  • Nikolaos Lykousas University of Piraeus
  • Constantinos Patsakis University of Piraeus
  • Andreas Kaltenbrunner Universitat Pompeu Fabra. Barcelona
  • Vicenç Gómez Universitat Pompeu Fabra. Barcelona


The continuous and increasing use of social media has enabled the expression of human thoughts, opinions, and everyday actions publicly at an unprecedented scale. We present the Vent dataset, the largest annotated dataset of text, emotions, and social connections to date. It comprises more than 33 millions of posts by nearly a million users together with their social connections. Each post has an associated emotion. There are 705 different emotions, organized in 63 “emotion categories”, forming a two-level taxonomy of affects. Our initial statistical analysis describes the global patterns of activity in the Vent platform, revealing large heterogeneities and certainly remarkable regularities regarding the use of the different emotions. We focus on the aggregated use of emotions, the temporal activity, and the social network of users, and outline possible methods to infer emotion networks based on the user activity. We also analyze the text and describe the affective landscape of Vent, finding agreements with existing (small scale) annotated corpus in terms of emotion categories and positive/negative valences. Finally, we discuss possible research questions that can be addressed from this unique dataset.




How to Cite

Lykousas, N., Patsakis, C., Kaltenbrunner, A., & Gómez, V. (2019). Sharing Emotions at Scale: The Vent Dataset. Proceedings of the International AAAI Conference on Web and Social Media, 13(01), 611-619. Retrieved from