Graphs are useful as they let you go beyond the individual relationships between items and see overall patterns.
Los Angeles, CA (PRWEB) May 02, 2013
Connections in this graph represent significant correlations between sentiment towards connected beers, which vary in terms of strength. For example, people who like Newcastle Brown Ale also like Harp, and they therefore are connected and appear close to each other in the graph. A graphing algorithm placed beers that were more related closer to each other and beers that had fewer/weaker connections further apart. Ranker also ran a classification algorithm that clustered beers according to preference and colored the graph according to these clusters.
While different people will see different patterns when looking at the same graph, a few trends were evident to the Ranker team.
- The classification algorithm revealed six main taste/opinion clusters, which could be labelled: Really Light Beers (e.g. Natural Light), Lighter Mainstream Beers (e.g. Blue Moon), Stout Beers (e.g. Guinness), Craft Beers (e.g. Stone IPA), Darker European Beers (e.g. Chimay), and Lighter European Beers (e.g. Leffe Blonde). The interesting parts about the classifications are the cases on the edge, such as how Newcastle Brown Ale appeals to both Guinness and Heineken drinkers.
- The opposite of light beer, from a taste perspective, isn't dark beer. Rather, light beers like Miller Lite are most opposite craft beers like Stone IPA and Chimay.
- Coors light is the light beer that is closest to the mainstream cluster. Stella Artois, Corona, and Heineken are also reasonable bridge beers between the main cluster and the light beer world.
"One of the strengths of Ranker's data is that we collect such a wide variety of opinions from users that we can put opinions about a wide variety of subjects into a graph format. Graphs are useful as they let you go beyond the individual relationships between items and see overall patterns," explained Ravi Iyer, Ranker's Data Scientist.