TY - JOUR
T1 - Demonstrating the effect of exposure to nature on happy facial expressions via Flickr data
T2 - Advantages of non-intrusive social network data analyses and geoinformatics methodologies
AU - Svoray, Tal
AU - Dorman, Michael
AU - Shahar, Golan
AU - Kloog, Itai
N1 - Funding Information:
This is the 1st paper of the NEGEV-GEOPSYCHOLOGY Research Group established in Ben-Gurion University of the Negev by Tal Svoray and Golan Shahar. Golan Shahar was partially supported by a donation by the Barry Leonard Katz Memorial Philanthropic Funds of the Jewish Community Federation and Endowment Fund , and the Silicon Valley Community Foundation , for a program of research targeting the biopsychological underpinnings of suicidal depression.
Publisher Copyright:
© 2018 Elsevier Ltd
PY - 2018/8/1
Y1 - 2018/8/1
N2 - Although the role of exposure to nature (ETN) in improving well-being was previously demonstrated, most of the existing research is derived from self-report measures. Conversely, geoinformatics methodologies are seldom used. To address this gap, we examined the prevalence of happy facial expressions (HFE) in natural settings such as water bodies, green vegetation, and undeveloped areas. We applied a novel, spatio-temporal analysis of photos taken in the Boston area and posted on Flickr – a location-based social network – during 2012–2015 (N = 60,013). Photos were analyzed using Microsoft Emotion API to detect facial expressions. ETN, measured either as a composite score, or based on the three aforementioned aspects, was significantly associated with HFEs, even after controlling for temporal patterns. An exploratory visualization of spatial clusters characterized by high HFE proportion was in agreement with the statistical results. This method can be used to explore human-environment interactions more explicitly in a non-intrusive manner.
AB - Although the role of exposure to nature (ETN) in improving well-being was previously demonstrated, most of the existing research is derived from self-report measures. Conversely, geoinformatics methodologies are seldom used. To address this gap, we examined the prevalence of happy facial expressions (HFE) in natural settings such as water bodies, green vegetation, and undeveloped areas. We applied a novel, spatio-temporal analysis of photos taken in the Boston area and posted on Flickr – a location-based social network – during 2012–2015 (N = 60,013). Photos were analyzed using Microsoft Emotion API to detect facial expressions. ETN, measured either as a composite score, or based on the three aforementioned aspects, was significantly associated with HFEs, even after controlling for temporal patterns. An exploratory visualization of spatial clusters characterized by high HFE proportion was in agreement with the statistical results. This method can be used to explore human-environment interactions more explicitly in a non-intrusive manner.
UR - http://www.scopus.com/inward/record.url?scp=85053054655&partnerID=8YFLogxK
U2 - 10.1016/j.jenvp.2018.07.006
DO - 10.1016/j.jenvp.2018.07.006
M3 - Article
AN - SCOPUS:85053054655
SN - 0272-4944
VL - 58
SP - 93
EP - 100
JO - Journal of Environmental Psychology
JF - Journal of Environmental Psychology
ER -