# Extracting human emotions at different places based on facial expressions and spatial clustering analysis

## TL;DR

This paper presents a novel framework that uses social media photos and facial expression analysis to evaluate human emotions at various locations, revealing how environmental factors influence emotional variation.

## Contribution

The study introduces a new method combining spatial clustering and affective computing to analyze large-scale georeferenced photos for emotion extraction.

## Key findings

- Emotional variation correlates with environmental factors like openness.
- A happiness ranking for 80 tourist sites was generated from 2 million faces.
- Spatial clustering effectively identifies distinct emotional zones.

## Abstract

The emergence of big data enables us to evaluate the various human emotions at places from a statistic perspective by applying affective computing. In this study, a novel framework for extracting human emotions from large-scale georeferenced photos at different places is proposed. After the construction of places based on spatial clustering of user generated footprints collected in social media websites, online cognitive services are utilized to extract human emotions from facial expressions using the state-of-the-art computer vision techniques. And two happiness metrics are defined for measuring the human emotions at different places. To validate the feasibility of the framework, we take 80 tourist attractions around the world as an example and a happiness ranking list of places is generated based on human emotions calculated over 2 million faces detected out from over 6 million photos. Different kinds of geographical contexts are taken into consideration to find out the relationship between human emotions and environmental factors. Results show that much of the emotional variation at different places can be explained by a few factors such as openness. The research may offer insights on integrating human emotions to enrich the understanding of sense of place in geography and in place-based GIS.