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Flowing Data: What Makes People the Most Happy

We last featured this dataset in the 09-14-18 Scout Report, and it remains a great resource to return to if you are looking for statistical analysis that will make you smile. From FlowingData (featured in the 1-22-2016 Scout Report) comes "What Makes People the Most Happy," published in June 2018. Here, statistician Nathan Yau analyzes "a corpus of 100,000 happy moments" created when researchers at MIT, the University of Tokyo, and Recruit Institute of Technology asked 10,000 people to each list 10 happy moments. Yau used natural language processing to break the responses down into basic subject-verb-object components, then examines these for patterns. The results showed that while most of the happy moments featured the self as the main subject (e.g. "I got a new car"), many happy moments stemmed from others (e.g. "My husband made dinner for our family") or were felt on behalf of others (e.g. "My best friend got his old job back"). Yau's lighthearted textual analysis includes visual representations of the different categories under consideration, as well as notes on how he analyzed this dataset and links to related FlowingData articles.
Archived Scout Publication URL
Scout Publication
GEM Subject
Date of Scout Publication
March 13th, 2020
Date Of Record Creation
September 10th, 2018 at 3:10pm
Date Of Record Release
September 13th, 2018 at 2:16pm
Resource URL Clicks
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