Social scientists need to take their expertise into the data science realm, says Katie Metzler

The power of big data to unlock information, influence decisions and revolutionise outcomes is well known and well documented across a range of industries and sectors.

It’s no secret that commercial businesses are using big data to maximise profit, but with this comes a range of associated risks. In Cathy O’Neil’s book, Weapons of Math Destruction, we are given examples of how big data is being used in ways that most of us would find objectionable.

Predatory targeted advertising carried out by for-profit universities in the US has left thousands of vulnerable students with mountains of debt, and big data and reoffending risk algorithms in the US penal system have been written in a way that ‘guarantees black defendants will be inaccurately identified as future criminals more often than their white counterparts’.

But we shouldn’t discuss the negatives, without also recognising the great work that is simultaneously taking place. Big data is being used to support election monitoring in the Global South, tackle epidemics and cure diseases, and improve the targeting of humanitarian aid to those who need it most. There are inspirational organisations such as DataKind UK, which matches charities and data scientists together, and use data science to find solutions to charities’ problems.

These examples compare opposite ends of the scale, showing that big data is neither inherently good, nor bad. It depends on the way it is used, by whom and in the service of what outcomes.

Within social research big data presents a huge opportunity to help answer fundamental questions about individuals and collectives, formulate new understandings about society and, ultimately, improve societal outcomes. But to make this a reality we need the skills and theoretical knowledge of the social researchers who know how to ask the right questions.  How, then, can we ensure that they bring their expertise to the table?

With the aim of learning more about how big data is being used in social science research, SAGE and the University of Essex conducted a survey of over 9,000 academics in 2016. Analysis on these responses (published in the White Paper ‘Who is Doing Computational Social Science? Trends in Big Data Research’) revealed although there was a considerable appetite among researchers to work with big data, a number of barriers stood in their way, the biggest being a lack of skills being able to deal with the data available.

In particular:

• Researchers already engaged with big data cannot find other collaborators with the right skills and knowledge – 29 per cent of those surveyed stated this as a major problem;
• Two thirds said there were challenges around learning new software of new analytical methods due to time constraints;
• 40 per cent of those surveyed stated that they would like to attend big data training in the future, with a specific interest in text mining and R and Python programming; and
• There is a lack of adequate/available training for data science skills and programming included at degree level with a large number of those surveyed stating that they had sought big data training elsewhere, i.e via MOOCs.

This lack of skills across the sector supporting interdisciplinary collaboration and engagement is something that needs addressing and supporting at undergraduate, early career researcher and researcher level.

So how can we, as individuals and as an industry, begin to address this?

In September of last year, SAGE launched SAGE Campus – a series of online data science courses specifically tailored to social scientists.

We worked closely with academic experts to create course content that equips social scientists with skills that they can apply to their research right away. The first set of courses introduce researchers to the programming language Python, and teach them how to use the programming language R to manage, present and analyse social data.

New and additional courses, set to launch this summer, will teach fundamental skills to those who are unfamiliar with R, as well as offering intermediate and advanced courses for confident Python users. There will also be the opportunity for researchers to acquire skills in specific areas such as social media methods and text mining.

As the practice of both teaching and conducting research continues to evolve, our aim is to provide guidance and publishing innovations that will support researchers well into the future. The launch of SAGE Campus is a major step towards this goal.

By equipping social science researchers with these skills it is our hope they will be able to harness the power of big data research. It is our belief that this will in turn facilitate deeper examinations into complex societal issues, uncovering previously unknown truths about the world around us.

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Businesses are mining data and discovering gold. But the riches hidden in massive public databases remain unexplored. Deciphering this data and analysing it can lead to better policies and favourable outcomes. CPC Analytics, an Indo-German start-up, hopes to solve real-world problems by leveraging this data through relevant analysis, insights and advice.

CPC Analytics was founded three and a half years ago by Sahil Deo and Christian Franz. They studied at the Hertie School of Governance in Berlin and graduated with Masters in Public Policy. Franz has expertise in macroeconomics, statistics and international health policy. Deo brings in expertise in technology and international finance. Complementing them was Viraj Kulkarni, who joined later as partner at CPC, as their chief data scientist. According to Deo, the two worked together on an EU integration project in Berlin and realised they could provide useful contribution. They chose to start a company even before they graduated for offering data-driven policy consulting in economics, health, energy and environment.

CPC aims to work in segments where the big technology companies, consultancies or start-ups are not interested in, especially the public sector space. CPC calls itself a diverse set of ‘curious and driven people’. Through an interdisciplinary approach that brings software engineers, economists, social scientists together, the team offers actionable insights from large and complex data sets. “We see ourselves as a boutique consulting firm to help with specific problems. The two pathways important to us are improving policy making and impact on public debate,” says Franz.

Deo and Franz were clear about keeping this an operation that simultaneously worked from Germany and India; so CPC operates out of Berlin, Pune and Strasbourg. While Franz handles the German front, Deo is in charge of Indian operations. The company straddles both worlds – “Germany where everything is established, and India where everything is super dynamic and open to changes with dramatic shifts” as Franz says.

“Public policy is dominated by older people. No start-ups or younger people are there in this space. But this is changing. Technology is disrupting and older people have no particular advantage,” says Deo. “Fewer firms work with the public sector institutions. We did not have a formal ecosystem, support, peer group or benchmark.”

At the start itself the duo decided they would shut shop if they did not get paid work. Thankfully, they did not need to do this as CPC has made money right from the start and does not face problems like the typical start-up as it keeps operations lean. Clients include WHO, UNAIDS, government of Nepal, Johns Hopkins University, GIZ of Germany, SIDBI, GFA, Rabin Martin, Graduate Institute Geneva, Public Affairs Centre and GFA.

However, work is erratic and Deo says they find the public sector more challenging. If CPC can sustain itself for a few more years it will have the first-mover advantage as sooner or later the public sector will adapt to the new technology landscape. As for now, the focus is on getting projects that are directly awarded and do not need to go through a tender process as they will not even qualify for those, says Deo.

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