Happy Travelers Take Big Pictures: A Psychological Study with Machine Learning and Big Data
This provides a big-data validation of a psychological theory for researchers, though it is incremental in applying existing methods to new data.
The study tested the 'broaden-and-build' theory by analyzing 418K travel photos, finding a strong correlation between high-rated tourist sites and a preference for wide-angle photos, using deep learning for classification.
In psychology, theory-driven researches are usually conducted with extensive laboratory experiments, yet rarely tested or disproved with big data. In this paper, we make use of 418K travel photos with traveler ratings to test the influential "broaden-and-build" theory, that suggests positive emotions broaden one's visual attention. The core hypothesis examined in this study is that positive emotion is associated with a wider attention, hence highly-rated sites would trigger wide-angle photographs. By analyzing travel photos, we find a strong correlation between a preference for wide-angle photos and the high rating of tourist sites on TripAdvisor. We are able to carry out this analysis through the use of deep learning algorithms to classify the photos into wide and narrow angles, and present this study as an exemplar of how big data and deep learning can be used to test laboratory findings in the wild.