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Analyzing Connections Between User Attributes, Images, and Text

Research output: Contribution to journalJournal articlepeer-review

Published
  • Laura Burdick
  • Rada Mihalcea
  • Ryan Boyd
  • James W. Pennebaker
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<mark>Journal publication date</mark>23/03/2021
<mark>Journal</mark>Cognitive Computation
Volume13
Number of pages20
Pages (from-to)241-260
Publication StatusPublished
Early online date13/02/20
<mark>Original language</mark>English

Abstract

This work explores the relationship between a person’s demographic/ psychological traits (e.g., gender, personality) and selfidentity images and captions. We use a dataset of images and captions provided by N = 1,350 individuals, and we automatically extract features from both the images and captions. We identify several visual and textual properties that show reliable relationships with individual differences between participants. The automated techniques presented here allow us to draw interesting conclusions from our data that would be difficult to identify manually, and these techniques are extensible to other large datasets. We believe that our work on the relationship between user characteristics and user data has relevance in online settings, where users upload billions of images each day (Meeker M, 2014. Internet trends 2014–Code conference. Retrieved May 28, 2014).

Bibliographic note

The final publication is available at Springer via https://link.springer.com/article/10.1007/s12559-019-09695-3