This post is first in a series that looks at the inferences you can make using social media data. The current analysis is a by-product of the Me Meme Twitter client that recently soft launched. Me Meme organizes your timeline into separate feeds based on your interests, helping you conquer information overload. It leverages Panoptez, a hosted Model as a Service from Zato Novo.

Prevailing wisdom says that who you associate with says a lot about you. By analyzing your social media graph, I can confirm that this claim has merit. Remarkably, it can also reveal non-obvious interests that provide insights into a person. This knowledge can be used for marketing, sales, or even plain-old relationship building.

First a bit of background. Panoptez, is a suite of models that I’ve developed and am licensing. They are components that are used to build custom data-driven applications. (See The Models as a Service Era has arrived for more information on this idea.) An example is the interplay between Panoptez and Me Meme. Panoptez provides the intelligence of extracting groups of people with similar interests and generating representative keywords that describe those groups. Me Meme uses this model output to display a Twitter timeline in separate feeds, so that each feed only contains tweets by the people in the group. Like a newspaper organized by sections, your feed becomes organized based on your individual interests. So Panoptez makes inferences, and Me Meme applies it to a specific problem.

What’s fascinating is the level of insight that can be gleaned from something as simple as a social graph. Take, for example, the NYC venture capitalist Matt Turck. What does his social graph say about him? Here are some of the groups Panoptez found within his social graph.

These groups appear to isolate Matt’s interests. But how do we know for sure that these interests are accurate? Since I don’t know Matt personally, I can’t just ask him. Thankfully Matt blogs and has an informative bio that we can use a form of validation:

So his bio validates a number of the groups identified by Panoptez. This is further confirmed by his blog posts:

• The French Startup Ecosystem: At a Tipping Point
• The State Of Big Data in 2014: a Chart
• Introduction to the Internet of Things (Video)
• The Rise of the Female Hardware Entrepreneur

What have we learned from this post? For a given user, we’ve managed to extract key interests of that user by simply analyzing the user’s social graph. Throw in a dash of natural language processing to generate summary labels for the groups, and we have a powerful model for understanding users. All of this can be provided as a simple hosted model/data service that requires no infrastructure build-out nor a data science team. Contact me at [email protected] to learn more about Panoptez and Me Meme.

Appendix

For those interested in leveraging Panoptez, there are two ways to access it (after subscribing to the service). The preferred approach is via a REST API and data feed. Alternatively, it is possible to work with the Panoptez R library directly. This analysis only requires three function calls:

> uc <- user_community(user.id)
> list_communities(uc)

  0   1   2   3   4   5   6   7   8   9  10
  8  21   4   9 639  26  29  22 115 114   6

> head(print_community(1,uc),10)
                         location               name     screen_name                                                                                                                                                   description
75334187                    Paris       Tatiana jama     Tatianajama             Co Founder & CEO @Selectionnist @Dealissime (acquired by LivingSocial) // Partner @50Partners @PartechEntrepreneur #BA #Passionate about startups
560454290    San Francisco, Paris            Algolia         algolia                                     Algolia is a powerful Search as a Service API built for developers to deliver relevant results in their apps and website.
41675415   Paris, London, Europe       Roxanne Varza    roxannevarza startup lead @microsoft / @msftventures. cofounder @tech_eu @girlsintech_uk @gitparis & @failcon paris. ex techcrunch france editor @TCFR. epilepsy advocate.
4354801                     Paris      Marie Ekeland       bibicheri                                                                                                                  VC @Elaia_Partners, Co-President @FRDigitale
5870292                NYC, Paris Frédéric Montagnon  fred_montagnon              Founder & CEO at Secret Media Inc. Entrepreneur. French. Engineer. Ex Codanova, OverBlog, Nomao, Ebuzzing. Blues, monoski and herbal tea addict.
116907977                New York     French Morning FrenchMorningNY                                                                                                       Le twitter du 1er web magazine des Français d'Amérique.
38021678        Paris – Montreuil     Fleur Pellerin   fleurpellerin                                                             Secrétaire d'Etat au commerce extérieur, à la promotion du tourisme et aux Français de l'étranger
2205307848                 France     La French Tech    LaFrenchTech                             La #Frenchtech est le nom collectif pour désigner tous les acteurs de l’« écosystème de #startups » français. #innovation #france
267794397           Paris, France        Liam Boogar      LiamBoogar         Editor @RudeBaguette - France's Startup Blog - We cover Web, Mobile & Tech in the Paris startup scene, balancing breaking news with in-depth analysis
112671889              Everywhere      Kima Ventures    kimaventures                                                                                           Xavier Niel @xavier75 and Jeremie Berrebi @jberrebi Angel Seed Fund