"Researchers asked study participants via MTurk to list three happy moments they had in the past 24 hours. The researchers released the data as HappyDB, which provides 100,000 happy moments along with demographics. For the Pudding, Alvin Chang made an abstract map that places the moments based on less agency to more agency on the x-axis and immediate to long-term on the y-axis."
"A Gemini LLM was used to classify the data into continents, countries, and states, based on type of happiness. You can zoom in to the individuals to read the moments and you can filter by location, age, sex, parental status, and marital status."
Researchers collected 100,000 happy moments from MTurk participants describing positive experiences from the past 24 hours, creating the HappyDB dataset with demographic information. The Pudding created an interactive abstract map organizing these moments along two axes: personal agency (low to high) on the x-axis and time frame (immediate to long-term) on the y-axis. A Gemini LLM classified the data geographically by continent, country, and state based on happiness type. The interactive visualization allows users to zoom into individual moments, read specific entries, and filter results by location, age, sex, parental status, and marital status. The creator reflects on how the distribution might differ if wealthy individuals were surveyed instead.
#happiness-data-visualization #crowdsourced-research #interactive-mapping #demographic-analysis #machine-learning-classification
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