Networks and tastes

This on CT.

Retailers such as Amazon and Half use social network methods applied to people’s previous purchasing behavior and demonstrated interest to figure out what other items users may want to buy. MovieLens is an interesting example of a non-commercial service that uses information provided by the user about his or her movie preferences (ratings of movies already viewed) to suggest what additional movies may be of interest to the person based on the movie evaluations of others who exhibit similar tastes. Music Plasma suggests what artists are close to each other based on style and epoch. Unfortunately the site doesn’t tell us much about the underlying methodology.[1] Unlike MovieLens, it seems to rely on information about the position of artists in the network based on shared genre and era to make recommendations (i.e. display linkages) instead of relying on listener feedback about shared tastes. I’d be curious to hear about other similar services resembling any of these approaches. For those interested in visualizations of this type, the search engine Kartoo and the Virtual Thesaurus may also be of interest (the latter is quite restricted for non-subscribers though and I have never been able to access enough of it to be particularly impressed). For more on visualization of networks and an explanation of social network analysis basics, see

fn1. A few months ago I contacted them for more information, but got no response.

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