A Data Analysis Dive Into Reddit's Most Upvoted Comments Using R + Other Topics


Details
Topic 1
Have you ever seen a top comment on a reddit post and noticed the time stamp matches the post (i.e. both happened "7hrs ago")?
Essentially, the question is this: Just how time-lopsided are top comments? This question has various interpretations/corollaries:
- If you make a comment super early, is it more likely to be upvoted?
- If you make a comment later, how unlikely is it to be upvoted?
- Are votes based on content, or just being toward the top (and seen)?
- Because the reddit default sort is "best," users have to scroll to read newer comments; will they, or is there a high "scroll burden"?
- Do these metrics/phenomenon vary by sub?
Join us to learn what an analysis of 3 million reddit comments from 7000 posts in 57 subs reveals.
Topic 2
How does one interpret data and examine the validity/strength of arguments presented in a theories? John debunks a commonly cited Michigan voter fraud theory that has been convincingly presented using data and statistics. Bring an open mind!
Topic 3 - If time allows
The main reasons behind most state road construction projects are to replace or fix aging infrastructure and to alleviate traffic congestion.
Before these construction projects start, the state & cities will make presentations about the benefits. However, after project completion, an analysis to show the level of benefits realization (such as commute time on I-35W between 7-9am has been reduced from 35mins to 16 mins) is never made. John has analyzed vehicle traffic data before and after major Minnesota road constructions. The results are interesting!
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Presenter: John Henderson
John is a Product Development Specialist at a Minnesota Fortune 100. He is a mechanical engineer who has been using R for data analysis and visualization for over 10 years.

A Data Analysis Dive Into Reddit's Most Upvoted Comments Using R + Other Topics