Listening in, a snooper's charter, or data for good?

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Our Community Mirror working paper is published by Nesta today as part of their Data For Good programme. During this project we have been trialling the use of 'social media listening' technology - beloved of corporate marketing departments and surveillance agencies - to learn about what makes a community tick. Instead of simply using this information to market products or to monitor the population like Orwell's Big Brother, is it possible to use such data to help drive community action?

Something odd happened to me on Twitter last Thursday. I’d been having a problem trying to vote in the morning, so I sent a tweet to my local council explaining the issue at the polling station on Amhurst Road in Hackney – which is also the street I live on. Immediately, a Twitter account with the username @amhurstroad retweeted me. Curious as to what was going on with this hyper-local re-tweeter, I clicked on this account, and found no explanation other than a series of other retweets from various sources that all mentioned ‘Amhurst Road’.

I had never before had any interaction with this mysterious account. Who or what is behind it? Are they observing me? Do they know where I live? Why are they interested in tweets about my road – and what do they plan to do with this information? Will they use this information for good, or not? The lack of an obvious purpose to the account’s agenda was slightly unnerving, but gently intrusive online background noise is so commonplace now that I simply shrugged and got on with my day.

Many of us now produce huge volumes of highly personal information about ourselves online: what we buy, what we like, what we think about our local area and the things that happen to us each day, our relationship status, how we vote. IT-savvy businesses and government departments have quickly cottoned on to the fact that, taken in aggregate with many other people’s online activity, this information is a useful form of data.

This data is being used in different ways, such as companies tracking Facebook and Google algorithms to target certain adverts at us, or Amazon and YouTube’s uncanny (and sometimes unflattering) assessments of what books and videos they think we would enjoy consuming next. Such applications of our personal information may seem mundane or inevitable - if a bit creepy - but of late more ethically troubling instances of such online data gathering have become apparent. These range from the unauthorised Facebook ‘mood experiment’ in which the social media platform tested whether it could manipulate users’ emotions by deliberately exposing them to ‘happier’ or ‘sadder’ communications, to the ‘snooper’s charter’ and controversial revelations about the indiscriminate collection of online data by the government agencies NSA and GCHQ.

But what if the same kinds of ‘social media listening’ technology could be employed for social good? What if the techniques that are currently being used mainly to sell us things or keep us under surveillance could be used to identify the needs and assets in a local area, and even help to bring people together to make their community stronger?

Enter the Community Mirror. Over the past few months, the RSA has been collaborating with Jimmy Tidey, a researcher at the Royal College of Art, who is exploring how to use data from social media (mainly blogs and Twitter) to find out what a geographic community values about a particular area. Can people’s Tweets tell us which roads are dangerous, which alleyways are dirty, or which people might be interested in coming together to save a local library? Can online activity give us an idea about which social groups are – or could be – really effective at supporting people’s wellbeing and bringing communities together, even if these small groups are operating ‘under the radar’, largely unknown to local councils and other powerful organisations?

And who would this information be for anyway? Could it help government or charitable services target their resources more effectively from the ‘top’, or would it be better to present this data back to local people and say: ‘this is what your community looks like and these are the issues people are talking about – what would you like to do now?’

Today, the innovation charity Nesta is publishing a working paper prepared by Jimmy and my former colleague Gaia Marcus, detailing the first test of the Community Mirror work last year. Following some community mapping the RSA had done through interviews and ethnographic research in Hounslow, west London as part of a different project, our team ran the Community Mirror online tool to compare this face-to-face research with the local information gathered through digital means.

The preliminary results were encouraging, as both the working paper and a chapter by the RSA’s Rowan Conway in Nesta’s Data for Good essay collection explain. The digital tool mapped 294 community assets (people, places, organisations or things that seem to have a positive impact on an area) across the Hounslow Borough, and picked up an impressive 31% of the local assets that research participants told us about in the face-to-face research. We think these signs are encouraging and suggest that there is potential for digital tools to help with some of the heavy-lifting in community mapping, a technique that is increasingly being seen as a valuable part of Asset Based Community Development – getting to know the strengths and key features of an area in order to help local people make it better using the means and assets at their disposal.

Now we’re taking the Community Mirror a step further. ‘LocalNets.org’ is an improved version of the tool that we’re using in Bretton, Peterborough, as part of our Big Lottery funded Connected Communities programme which looks at mental wellbeing and social inclusion in seven sites around the UK. With Jimmy and our research partners at the University of Central Lancashire, we have used the Community Mirror to map community assets and identify people and organisations in Bretton who have an interest in helping to strengthen the local community, as well as how they are linked: who is already talking to who, and where there are ‘missed connections’ where introducing people to each other could have a positive impact. We invited these people to a public meeting at which we played back the data we had picked up online (as well as some offline research we have done in the area previously). Now we’re supporting those local people as they work together to come up with new initiatives to make a difference in the community, using insight from their own experiences in conjunction with the additional community-level information from the Community Mirror. We’ll let you know how it goes over the next few months via this blog, and with a big report at the culmination of the Connected Communities work in the autumn.

So, back to that mysterious Twitter user who is obsessed with my street. Is he, she, they or it also working to use data for good in the same way as the Community Mirror? Will they aggregate all Twitter users' complaints and positive statements about life on Amhurst Road into some kind of database that can be used to improve the area somehow? Is it a local journalist looking for a scoop? Or is it some kind of sinister tracker who is following my every move with the intention of selling my data to marketers or reporting me to GCHQ? Without the open, shared approach to information that is key to the Community Mirror – that reflective element that allows the observed to see themselves - then this is far from clear.

 

The working paper about the Community Mirror project was written by Gaia Marcus and Jimmy Tidey and can be found athttp://www.nesta.org.uk/publications/community-mirror-data-driven-method-below-radar-research 

Rowan Conway's article, 'Listening In: using social monitoring tools to understand the social economy', is at pp. 32-36 of  Nesta's accompnaying report 'Data for Good: How big and open data can be used for the common good'. This can be found at http://www.nesta.org.uk/sites/default/files/dataforgood.pdf

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