Yesterday we posted about a company developing algorithms that comb through key factors including content of posts, and location, among others
….. to provide a very to develop a identify and “unify social profiles” for users who may be using different names or handles on each of their social networks.
The post elicited strong interest and 2 replies that I want to highlight.
The first is from Niv Singer, Chief Technology Officer at Tracx … the man, and the company referenced.
Here’s Mr. Singer’s enlightening reply … very interesting:
I am Niv Singer, “the guy” you quoted in your post above.
Conrad Gessner, a Swiss scientist, described how the modern world overwhelmed people with data and that this overabundance was both “confusing and harmful” to the mind. However, Gessner, who lived in the 16th century, warned about the dangers unleashed by the printing press. If we look back at history, every new technology – the printing press, the radio, the television, the internet, and now Social Media and specifically Facebook – seems scary at first.
It’s very important to make a distinction between public information and private information. Tracx only collects *public information*, and we give utmost respect to privacy. For instance, content you share on public platforms such as Twitter is collected. From Facebook, we only collect posts marked as “Public”. We never ever collect, or even have access to, emails, chats, closed forums, etc.
Identity unification is indeed a challenge, and we developed quite a sophisticated algorithm at tracx in order to do so. The first generation of listening platforms enabled the analysis of content that mentions specific keywords. What we do at tracx is to construct entire conversations, even if only some of the related posts or comments are relevant to what our clients are trying to analyze, to provide context. In order to do so, and give a more accurate picture of the persons involved, our algorithms try to figure out whether certain users from different social networks are, in fact, the same person.
The identity unification algorithms only rely on signals from publicly available information. For instance, if your Foursquare check-in is also posted to your Twitter or Facebook timelines, we can make an educated guess that all three users actually belong to the same person.
From my experience, people with a strong presence in social networks, have accounts in many different services, and these accounts are usually linked together (you can check out my Gravatar and Google+ Profiles to see how I meticulously listed all the different accounts I have).
Tracx, as well as other platforms, help companies provide better customer care – by having a representative get back to someone who complained. We help cable companies, for example, select the best shows by listening to conversations about them. We help policy makers make informed decisions, again, by listening. I believe we, the people, gained a lot of power in the past few years, and our voice is now heard. We help the organizations to listen.
Niv Singer / @nivs
http://www.tracx.com / @tracx
The 2nd reply that caught my attention was from an MSB alum:
I just got back from a private equity/venture capital show where there were two well funded groups whose biz model is too confuse “data unifiers” to help people keep their consumer, political, etc. preferences private (or at least obscured under relentless “noise”). It was interesting to say the least.
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In combination, the two replies reminded me Kevin Slavin’s TED talk on battling algorithms.
It’s worth another viewing …, click to view