Are you swiping Tinder on hard Mode?

In this post, I share results from a novel experiment on Tinder. We collect a unique dataset while swiping Tinder using different profile names and with heterosexual and homosexual search preferences. From this, we uncover vastly different patterns in matching and messaging behavior between sexes. More dramatically, we find strong evidence for name based discrimination on Tinder.

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A match made in heaven: Tinder and Statistics — Insights from an unique Dataset of swiping

Tinder is hugely popular and offers fascinating data on online dating. Still, there are barely any analysis of tinder data. In this endeavor we change that, by analyzing an unique dataset of tinder profiles. The data contains thousands of female and male profiles collected by swiping as a hetero- and homosexual male. Using descriptive statistics, visualization and natural language processing we uncover exciting patterns.

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Investigating bike rentals in Cologne - Part 2: Map visualization

In this multi part post, I will take a look at the bike rental system in Cologne. In the first part we applied web-scraping and XML parsing to retrieve data and build a dataset of bike locations. Now, we will deal with geospatial tools and map visualization in order to search for interesting patterns in the bike-rental data.

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