Wednesday, December 2, 2009

"2.0" community's stars carbon emissions via the social web

Experimentation is perhaps the most important attitude for understanding the ever changing landscape of a world constantly reshaped by infotech. From continuous experimentation hopefully comes some experience which can be used for execution of plans; we've got the 3Es of success and the cycle goes on and on.



In this post I'd like to share some thoughts about an experiment that started like all of BusinessQuests' experiments: with a weird question. Today's weird question: is there a way to find out how much carbon dioxide the "2.0" crowd of thinkers and star players is generating just by traveling the world to attend conferences, make speeches, shake hands and send those lovely "tweets" about the weather in Paris or the taste of vodka in Moscow?






Purpose of the experiment


The purpose of the experiment was therefore to find out how close I could get to assessing the carbon dioxide emissions of people like Robert Scoble, Peter Kim, Gerd Leonhard, Bradley Horowitz, Joi Ito, Lawrence Lessig... using only public information that I gathered from the "social web". So this is about using "2.0" tools on the thought leaders and stars of the "2.0" crowd, all of whom are very connected and tend to travel a lot to speak and meet in real life during conferences, not all of them interesting it must be said.

Why does it matter?


There's more to this attempt to assess carbon emissions of prominent figures of today's web than the results per se. It goes deeper to the question of what uses can actually be made of public information that we publish very willingly as part of our being part of the global networked community of what Richard Florida dubbed the "creative class", what some call the community of the ├╝ber-connected, the "2.0" bunch.


Whether the results are accurate to the gram of CO2 or not is not that relevant; the fact that the emissions can be estimated with published user data is much more relevant though because it means there is probably a way for people running private intelligence services or marketing organizations (sometimes a nuance without a difference) to do pretty accurate estimates of other dimensions in the lives of the connected crowd from revenues to groups supported to books bought to relationships and addresses... It's food for thought and that's not only for those of use who are active participants to social media and social platforms' permanent beta.


The results


So here are the results (spreadsheets here), using just Google Docs and an amazing gadget called Panorama Analytics for creating pivot tables on Google Sheets. The chart gives average emissions of carbon dioxide for prominent "2.0" figures who were kind enough to allow open access to their travel information on social travel site Dopplr.



For convenience, given that the load time of the Panorama gadget may be long, there's an Excel version of the chart below:

BQShot-20091202-022227


How was this done?


The total distance traveled by each of the people listed here was
broken down into plane, train and car travel making three sets of
assumptions (called scenario 1, scenario 2 and scenario 3) about the
relative importance of each transportation means in the traveler's
total travel distance. The traveler's date of activation of the Dopplr
account was used to calculate the number of months over which the total
distance was traveled and the free carbon footprint calculator provided
by the website www.carbonify.com was used toestimate the carbon impact of each traveler for each of the three scenarios.


Implications


From people to industries to institutions, the ubiquitous network and network based applications are profoundly transforming the way things get done. For all the generous talk about the openness, creativity and sharing enabled by social media, the central issue of what public information says about each one of us is getting hotter and hotter even as people from different background converge to bring solutions to address "digital identity", "e-reputation", "brand protection", "buzz", "intelligence", "monitoring"...


Since the very availability of such information and the thought of how it could be used undoubtedly sends shivers down many spines, it follows very logically that the kind of information we processed in this experiment is also information that has real marketing value because it makes sense. It has meaning. Something that is not necessarily true of all the detailed metrics and analysis we get from sophisticated tools that measure visits, bounces, clics, actions, hits, views or deliveries. At the end of the day less may very well be more if that "less" goes more to the heart of behavior tying back to real life of real people with real dreams, hopes, fears, joys and aspirations. That is the real core challenge for marketers today.


2 comments:

  1. Interesting analysis - but you should realize that you're dealing with a fundamentally flawed data set.

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  2. Yes I do realize the data is not necessarily correct and I was hoping someone would actually make this point because it shows that not all data that is available on social media is usable for analysis, something that many marketing agencies and service providers seem to underestimate. Obviously there's a difference between information declared by people and information captured by machines on the occasion of usage... I won't go into this now.
    Whether the data set is flawed or not, the fact is that data about you can be used for people to derive conclusions and convey messages about you. These conclusions and messages may be erroneous, but they have a basis that is your own usage data. For now it's not a problem, but what will happen when such data is used in lawsuits or by tax administrations to estimate real revenues of contractors... There is unquestionably a set of issues to be raised with publicly available data about people, organizations and brands and these are insufficiently addressed today.

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