Monday, 16 January 2017

How Social Media Can Be a Researcher’s Miracle or Downfall

Cassie Phillips is a freelance technology writer who also dabbles in social media. She’s a firm believer that everyone can find a use for social media whether to make friends or conduct a research experiment. Like technology, she finds social media is just another tool to add to one’s arsenal. @securethoughtsc

The idea of combining social media and research at first might be at odds with one another, but they actually complement one another. Research involves the production, use and consumption of knowledge. Before social, scientists and researchers disseminated information via conferences, journals, peer reviews and publication. What brings all of these events together is collaboration. This is where the true benefits of social become apparent.

Finding Information
You probably already have a system in place to find journals and articles that will suit your research. This can include using information portals, attending meetings and even focusing on certain peer-reviewed journals. While still useful, this takes time and can also lead to information overload. Social media can help you find more relevant information and sift through the noise. Following researchers within your discipline can help you find articles and journals that may be particularly valuable to you.

On the flip side, you still need to verify the sources you find online. Anyone can publish an article or post on the internet, so it's more important than ever to check sources and make sure what you're reading is legitimate.

Knowledge Creation
Most researchers view data generation as the main aspect of the job. For the most part, this means finding other literature that supports your research. However, the other important aspect is ensuring you publish and disseminate the information at the right time. So where does social media fit especially when there are risks in communicating your research while it’s still going on? After all, it can reduce your chances of getting published while also providing ammunition against you should you make a mistake. And with social, there’s also the possibility your account might get hacked, especially if your internet connection isn’t secure, though luckily there are ways to protect yourself.

So what are the benefits? Consider this example. Marianne Hatzopoulou, a civil engineer professor, wanted to research the impact of air pollution on cyclists. She turned to Twitter and sent out a couple of tweets encouraging people to fill out a survey. A popular cycling blog found the survey and then wrote an article. This then got picked up by a local newspaper, which then led to coverage on a radio show and a major network.

Spreading the World

Perhaps the most attractive quality of social media is its ability to disseminate information. Above all, social media is about engagement and communication, making it ideal for researchers to reach a wider audience.

Of course, depending on the type of article you produce, you’ll reach a very particular audience. More scholarly and academic articles will likely attract other researchers in your discipline. However, this means you’ll likely alienate the layperson as they won’t want to wade through pages of information.

Since social media is such an effective tool in attracting attention, it might backfire. Always double check before publishing anything on social media to ensure the post doesn’t come off as offensive or in poor taste. Always read a post multiple times before hitting the send or publish button. One poorly worded tweet can reach thousands of people and ultimately lower your credibility not only among your followers but the scientific community as well.

While there are obvious benefits to using social media, it still doesn’t replace face-to-face interactions. If used improperly, it may end up hurting your reputation and research more than it helps. At the end of the day, it all depends on how you approach it and how you engage with your community.

Monday, 9 January 2017

“The Big Data rich and the Big Data poor”: the new digital divide raises questions about future academic research

Data is being created faster than ever before. However, as Kate Metzler explains, limited access to this big data is creating a digital divide between large companies and the broader scholarly community. To compound this problem, there is also a big data analysis skills gap that further hinders the progress of social science. Without access to these datasets or the expertise to analyse them, research is confronted with a replication crisis and is vulnerable to commercial motivations.
“Data is the new oil.” Clive Humby, mathematician and architect of Tesco’s Clubcard, is credited with saying this first in 2006, and it’s been repeated numerous times in the last decade. The comparison between data and oil refers to its value being extracted through refinement; or in the case of data, through analysis. Unlike oil, data is being created at a faster pace than it can be consumed, or analysed. We’re awash with data. You may have heard it said that “90% of all the data in the world has been generated over the last two years.” Or, as Hal R. Varian, Chief Economist at Google, puts it another way: “A billion hours ago, modern homo sapiens emerged. A billion minutes ago, Christianity began. A billion seconds ago, the IBM PC was released. A billion Google searches ago … was this morning.”
The capacity to collect and analyse massive datasets has already transformed fields such as biology, astronomy, and physics, and for many, the ‘big data revolution’ promises to ask, and help us answer,fundamental questions about individuals and collectives. But who gets access to all this data we’re producing through our increasingly networked and digital lives, and for what purpose?
Image credit: Divided by David Wan. This work is licensed under a CC BY 2.0 license.
In 2012, danah boyd and Kate Crawford offered a provocation that the limited access to big data was creating a new digital divide between “the Big Data rich and the Big Data poor.” It’s only companies, and the social scientists working within these companies, that have access to really large social and transactional datasets. The broader scholarly community usually does not because companies refuse to release it or because purchasing it costs too much.
Recently, I conducted a survey of more than 9,000 social scientists to learn more about researchers who are engaged in research using big data and the challenges they face, as well as the barriers to entry for those looking to do this kind of research in the future. 32 per cent of respondents who are currently engaged in big data research reported that getting access to commercial or proprietary data was a “big problem” for them:
Figure 1: Challenges facing big data researchers (n = 2273)
But it isn’t only the question of who can access data that leads to divides. As boyd and Crawford point out, and our survey supports, there is also a skills gap holding social science back: the level of quantitative and programming skills required for big data research make it a challenge for educators to introduce it into traditional social science degree courses as there is little time or expertise amongst teaching faculty:
Figure 2: Challenges facing educators teaching big data (n = 1212)
Why does it matter?
So who cares if academic social scientists can’t do big data, either because they can’t access the data and/or don’t have the skills they need to engage with it? Why not just have companies like Twitter and Facebook analysing social media data? Some have even gone so as far as to argue that academics should not engage in research that can be done better by industry.
There are a couple of reasons why this is problematic. Firstly, because replication is the engine of science, and irreproducible research slows progress. If only researchers within companies can access and analyse big social datasets, “those without access can neither reproduce nor evaluate the methodological claims of those who have privileged access”.
And secondly, and arguably most importantly, the motivations of industry researchers and social scientists may differ in ways that may really matter. Big data research conducted by companies is usually in service of a single overarching goal: to sell you more stuff. Social scientists with the right skills and access to the right data may use their research to contribute to the body of knowledge, with the aim of better understanding and improving social outcomes.
The questions boyd and Crawford pose at the start of their paper summarize this perfectly. They ask:
“Will large-scale search data help us create better tools, services, and public goods? Or will it usher in a new wave of privacy incursions and invasive marketing? Will data analytics help us understand online communities and political movements? Or will it be used to track protesters and suppress speech? Will it transform how we study human communication and culture, or narrow the palette of research options and alter what ‘research’ means?”
As of yet, the answers to these important questions are unclear.
Read more in the recent SAGE Publishing white paper revealing full results of the survey, “Who is Doing Computational Social Science? Trends in Big Data Research.”
About the author
Katie Metzler is Head of Methods Innovation at SAGE Publishing. Katie is responsible for content strategy and innovation for SAGE’s award winning online platform for researchers, SAGE Research Methods, which includes SAGE Research Methods Cases, SAGE Research Methods Datasets and SAGE Research Methods Video. In addition to heading up the London commissioning team for the SAGE Research Methods platform, she is part of a new team at SAGE whose mission is to improve social science by equipping every researcher with the skills and tools they need to work effectively with big data and new technology. At SAGE, we believe big data and new technology are fundamentally changing how we make sense of the world and that social science needs to play a critical role where this impacts on society.