Mapping out the geography of happiness
Professor Eric Vaz’s new book Geography of Happiness: A Spatial Analysis of Subjective Well-being includes his research on happiness and Instagram posts from across the Greater Toronto Area.
When you find yourself brimming with happiness, where are you? If you’re uploading a picture to Instagram in the Greater Toronto Area (GTA) to share your #happy place, you’re likely posting photos of natural landscapes, according to a recent study by Toronto Metropolitan University (TMU) professor Eric Vaz.
In his research, professor Vaz, who specializes in geographical analysis and is the graduate program director for the master of spatial analysis in TMU’s Faculty of Arts, used data from thousands of Instagram posts that contained the hashtag “#happy” or related words, plus geolocation information. He analyzed where people identify these positive sentiments throughout GTA and the Greater Golden Horseshoe using machine learning and artificial intelligence tools. Professor Vaz has included his findings in his book, Geography of Happiness: A Spatial Analysis of Subjective Well-being.
“The places where you are more in contact with nature and the natural environment have intrinsically more happiness,” said professor Vaz. “In areas that are less clustered and less dense, that’s where you will have hotspots of more happiness,” he added, and his research has shown these natural spaces often inspire people to share happiness on social media. While the analyses did not drill down to the level of specific spots or parks, he was able to assess the general environmental attributes of the hotspot locations, noting many hotspots in Toronto are close to areas with access to the ravine system or tree coverage.
Professor Vaz’s research has found that Instagram posts from the Greater Toronto Area with the hashtag “happy” are often taken outside in natural landscapes.
Professor Vaz says measuring happiness objectively, a state often considered subjective, can be challenging. Using machine learning tools that find patterns in data where people self-identify as feeling happy alleviates this challenge by characterizing the geographic traits that lead to this self-identification. “What machine learning allows you to do is to create a vision based on data,” he said.
Professor Vaz encourages using artificial intelligence tools in spatial analysis to assist decision-makers. “I think that our public policy and governance can make a substantial difference if we understand where people fall into being happy and where we can say from a governance standpoint that it is, after all, not as subjective as we initially assumed,” said professor Vaz.
For those looking to create happier environments, access to natural outdoor spaces is key – but so is a focus on alleviating social and environmental injustice, says professor Vaz. He notes all those factors are important to the happiness and well-being of a city’s residents.
Learn more about the February 2023 publication of Geography of Happiness: A Spatial Analysis of Subjective Well-being (external link, opens in new window) .
Learn more about the March 2023 publication of professor Vaz’s monograph, Regional and Urban Change and Geographical Information Systems and Science (external link, opens in new window) .
