Date: Fri, 30 Jan 2015 09:00:37 +0000
<p style="color: #224422; font-family: 'Lucida Bright', Georgia, serif; font-size: medium;"> My quest this week is noteworthy a.i. researcher <a href="https://twitter.com/randal_olson">Randy Olson</a> who joins me to share his work creating the <a href="http://www.randalolson.com/2014/10/27/the-reddit-world-map/">Reddit World Map</a> - a visualization that illuminates clusters in the reddit community based on user behavior.</p> <p style="color: #224422; font-family: 'Lucida Bright', Georgia, serif; font-size: medium;"> Randy's blog post on <a href="http://www.randalolson.com/2014/10/27/the-reddit-world-map/">created the reddit world map</a> is well complimented by a more detailed write up titled <a href="http://arxiv.org/abs/1312.3387">Navigating the massive world of reddit: using backbone networks to map user interests in social media</a>. Last but not least, an interactive version of the results (which leverages <a href="http://gephi.github.io/">Gephi</a>) can be found <a href="http://rhiever.github.io/redditviz/clustered/">here</a>.</p> <p style="color: #224422; font-family: 'Lucida Bright', Georgia, serif; font-size: medium;"> For a benevolent recommendation, Randy suggetss people check out <a href="http://stanford.edu/~mwaskom/software/seaborn/">Seaborn</a> - a python library for statistical data visualization. For a self serving recommendation, Randy recommends listeners visit the <a href="http://www.reddit.com/r/dataisbeautiful">Data is beautiful</a> subreddit where he's a moderator.</p>
