XelaAl
commented
3 years ago Interesting data. I wanted to try speed dating, but then the pandemic began, so I didn't have the possibility. Though I started looking for a partner online and was lucky to check a nerdy dating site out. It turned out that there is a place where people like me (who like animation, science fiction, books, etc.) meet each other. Good source. But still, it is great that scientists work on such studies as they can help lonely people to find a partner easier and faster.
This project looks at the data collected from a Columbia University speed dating study and performs a data analysis task. More concrete, they want to assess what factors lead to a match between two partners, specifically focusing on how attractiveness figures into potential matches. The data contains additional information about each individual's interests/along with that of who they speed dated with.
Because the dataset contains information about the interests/views of people along with ratings of their attractiveness, I find it interesting to separate similarity of interests from attractiveness. I like how you guys listed out your overall motivation for why you undertook this project, contextualizing it in the growing world of speed dating. I also like how there are multiple paths you guys can take in terms of proceeding with this project: even if you find that attractiveness cannot effectively predict pairing success, you guys can fall back on constructing a general model to predict pairing success using a host of features.
In terms of areas for improvement, I don't know if one dataset is enough in terms of being able to fit a model that you think will generalize to other speed dating datasets. I also do not know valuable someone's 'interests' are for predicting pairing success, so this goes into my suggestion for joining this dataset with other datasets to add more features. Also I would encourage you guys to be more concrete about how you guys are going to quantify the success of a 'match'