A survey by a UK firm has found that Mumbai has become the least happy place to buy a home in the world and the most expensive city in India to buy a property. According to a survey by Online Mortgage Advisor, a UK-based firm, Mumbai scored -17.1 percent. Surat in Gujarat, with a score of -12.8 per cent, ranked fifth in the list of least happy places to buy a home. monecontrol report good.
The survey said that Atlanta in the US and Sydney in Australia rank second and third respectively in the list of the saddest places to buy a home globally. Paris was at number seven and Dubai at number 19.
Chandigarh ranks fifth among the top 20 happiest cities to buy a home, followed by Jaipur at 10th. While Chennai ranked 13th, Indore and Lucknow ranked 17th and 20th respectively.
The survey said that Barcelona in Spain and Florence in Italy were the happiest places in the world to buy property.
The survey was put together using artificial intelligence to analyze the happiness levels of geo-tagged photos on Instagram.
The Barcelona homebuyer photo scored an average happiness score of 95.4 out of a possible 100, which is 15.6 percent higher than the homebuyers’ global average happiness level, it said.
Chandigarh scored 13 per cent, Jaipur 10.8 per cent, Chennai 8.9 per cent, Indore 7.4 per cent and Lucknow 7.1 per cent, the survey said.
The study was conducted to sift through hundreds of thousands of geo-tagged Instagram posts around the world to find out how the average Instagram user’s happiness level compared to recent home buyers.
“We then used AI facial recognition tools to find the most dominant emotion displayed on the face in each photo,” the study said.
The analysis was done considering two sets of Instagram posts in August 2021 – one with the hashtag #selfie and the other using hashtags related to a recent home purchase, such as #homeowner. Only geotagged Instagram photos were considered in the analysis.
Each photo in the analysis was scanned with a Microsoft Azure facial recognition tool, which analyzes candid photos of faces and automatically assigns a score to the level of different emotions present.
Detectable emotions are anger, contempt, disgust, fear, joy, sadness, surprise, and neutral. The UK firm combined negative emotions (anger, contempt, disgust, fear and sadness) into one category (negative) for analysis.
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