Authors: Jason Leavey (@jasonleavey)
The report is a nice overview: summarising the main benefits of social media in public policy - how it can be used to enhance collaboration ("developing policy via wiki"), improve consultation (crowd-sourcing opinions and polls from the general public) and in primary research (collecting and analysing large data sets), and giving a round-up (at the end of the report) of some nice and oft-reviewed case studies (UN's Global Pulse, FixMyStreet, MapKibera, Electionista etc.) There is also some lovely name-dropping of up-and-coming organisations and collaborative projects putting social media analysis on the academic map (e.g. COSMOS and CASM.)
The best bits are where the author teases out the controversies embedded in the use of social media. Some of these are not so new, just new-ish in that we have to apply them to the web.
One problem is sample bias - presumably impacting all three of the aforementioned uses of social media. Not everyone is online - and even if all the influencers are online, which is why the private sector trends towards giving netizens more attention than non-netizens sometimes, the government and academia can't quite accustom themselves to this efficient yet exclusionary approach.
This goes hand in hand with sacrificing precision for timely accuracy. The report points out that Government tends to answer yesterday's questions tomorrow. One of the experts interviewed for the report says that great data that arrives five minutes after a decision is made is useless while 'pretty good' data that arrives three months prior to the decision-making is priceless (I'm paraphrasing here.)
This touches on the data deluge - it's not data overload, mom, it's filter failure - that academics, government, private and public (including the general public) contend with each day. How do you decide which bits are worth investigating and which vast swaths of data need to be ignored so we can actually get something done?
Another concern, touched on more lightly than in other reports, is credit. Like copyright, credit online is not something most netizens tend to respect. Encouraging academics and researchers to share more of their work and analysis online must take into account that they want credit for their data-driven insights. Using huge data sets to tease out amazing opportunities for government (who is not always a big spender) should at least garner the researcher some street cred if not the moolah that such insight earns in private industry.
Then there is the obvious culture-change required to promote sharing - as one journalist interviewed pointed out, many government officials have to be more afraid of not sharing the right information than of sharing the wrong information, and today's officials too often feel the opposite as a result of years of being 'risk averse' (as opposed to the buzz phrase of this month, 'risk aware'. Lawyers will have a field day with that one.)
Then there is the trouble of trust - how can government provide a sustainable, legal, transparent (transparent and legal - good luck to them!), and more importantly ethical framework that will not only make use of all the lovely information that citizens are sharing with them now but not freak anyone out about how that personal and private information is or may be used? The usual talk is of being accountable and proportional in the use of personal data, of balancing public goods with private concerns, of making it all anonymous. But what this means in practice is very nebulous and subjective, and once the government loses our trust, it's not like we can switch service providers with our next purchase. Worse luck, apparently studies indicate a loss of trust in one government service provider impacts the trust citizens hold in all service providers connected to that government (let's extend that argument - so PRISM may have something to do with all this fuss about healthcare in the USA? Heavens, I hope not. I'm a huge fan of public healthcare systems.)
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