Do individuals smile more in diverse social company? Studying smiles and diversity via social media photos

Vivek K. Singh, Akanksha Atrey, Saket Hegde

Research output: Chapter in Book/Report/Conference proceedingConference contribution

10 Scopus citations

Abstract

Photographs are one of the most fundamental ways for human beings to capture their social experiences and smiling is one of the most common actions associated with photo-taking. Photos, thus provide a unique opportunity to study the phenomena of mixing of different people and also the smiles expressedby individuals in these social settings. In this work, we study whether a social media-based computational framework can be employed to obtain smile and diversity scores at very fine, individual relationship resolution, and study their associations. We analyze two data sets from different social networks, Twitter and Instagram, over different time periods. Primarily looking at photographs, using computer vision APIs, we capture the diversity of social interactions in terms of age, gender, and race of those present, and smile levels. Analysis of both data sets suggest similar and significant findings: (a) people, in general, tend to smile more in the presence of others; and (b) people tend to smile more in a more diverse company. The results can help scale, test, and validate multiple theories related to affect and diversity in sociology, psychology, biology, and urban planning, and inform future mechanisms for encouraging people to smile more often in everyday settings.

Original languageEnglish (US)
Title of host publicationMM 2017 - Proceedings of the 2017 ACM Multimedia Conference
PublisherAssociation for Computing Machinery, Inc
Pages1818-1827
Number of pages10
ISBN (Electronic)9781450349062
DOIs
StatePublished - Oct 23 2017
Event25th ACM International Conference on Multimedia, MM 2017 - Mountain View, United States
Duration: Oct 23 2017Oct 27 2017

Publication series

NameMM 2017 - Proceedings of the 2017 ACM Multimedia Conference

Other

Other25th ACM International Conference on Multimedia, MM 2017
Country/TerritoryUnited States
CityMountain View
Period10/23/1710/27/17

All Science Journal Classification (ASJC) codes

  • Computer Graphics and Computer-Aided Design
  • Media Technology
  • Computer Vision and Pattern Recognition
  • Software

Keywords

  • Diversity
  • Faces
  • Happiness
  • Images
  • Instagram
  • Photos
  • Smile
  • Social media
  • Twitter

Fingerprint

Dive into the research topics of 'Do individuals smile more in diverse social company? Studying smiles and diversity via social media photos'. Together they form a unique fingerprint.

Cite this