Given that R and Python are both popular languages for doing data science, we wanted to compare stories and comments about both languages from Hacker News.

This could yield insights about the strengths and weaknesses of both languages, their applications in practice, and how their communities interact with Hacker News and each other.

• We tried using the API via R and Google Big Query (GBQ) and preferred the latter.
• We ultimately collected enough data (10k-20k per case per language), but at times had trouble balancing both kinds of data.
  

• Feedback from peers focused on if we’d choose a time period to look at. While this would be interesting, we chose to not to focus on time as much as the relevance of articles.
• Peer feedback focused on what our documents would contain. In the end we had data from titles, stories, and comments.
• One commentor asked if we would do semantic coherence and exclusivity for both groups together or separately. We ended up doing them both separately.

We visualized semantic coherence for Python and R Text and Comments