The Communist Manifesto. Novelist Don DeLillo’s account of a big moment in baseball. Works by Wittgenstein and Focault. And a famous –and shocking – behavioral experiment.  These are a few of the supremely inspiring works which have influenced some of the leading social scientists at work today.

During the recording of every Social Science Bites podcast, the guest has been asked the following: Which piece of social science research has most inspired or most influenced you? And now, in honor of the 50th Bites podcast to air, journalist and interviewer David Edmonds has compiled those responses into three separate montages of those answers. The second appears here, with answers – presented alphabetically – from Bites’ guests ranging from Sarah Franklin to Angela MacRobbie.

Their answers are similarly diverse. Sociologist Franklin, for example, who studies reproductive technology, namechecked two greats – Marilyn Strethern and Donna Haraway -- who directly laid the foundation for Franklin’s own work. “I would hope,” she reflected, “that I could continue toward those ways of thinking about those issues now and in the future.”

David Goldblatt meanwhile, who studies the sociology of football, picked influencers whose contributions are apparent in his work but less academically straightforward. He chose The Communist Manifesto (“the idea that history was structured and organized has never left me”) and the first 60 pages of American novelist Don DeLillo’s Underworld, which describes ‘the Shot Heard Round the World,” a famous home run from baseball’s 1951 World Series. Goldblatt terms it the “greatest piece of sports writing ever.”

Other guests in this 15-munte podcast recall important studies that set the scene for their own work, or important figures that left them wanting to emulate their scholarship. And not everyone cited academics in their own fields. Witness Peter Lunt citing Ludwig Wittgenstein and MacRobbie Michel Focault, while Jennifer Hochschild named an historian, Edmund Sears Morgan. She called his American Slavery, American Freedom “a wonderful book, everyone should read it – including the footnotes.” The book’s thesis, that “you had to invent slavery in order to be able to invent liberalism,” sticks with her to this day.

Other Bites interviewees in this podcast include Jonathan Haidt, Sarah Harper, Rom Harre, Bruce Hood, Daniel Kahneman, Sonia Livingstone, Anna Machin and Trevor Marchand. To hear the first montage, click HERE. 

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Social Science Bites is made in association with SAGE Publishing. For a complete listing of past Social Science Bites podcasts, click HERE. You can follow Bites on Twitter @socialscibites and David Edmonds @DavidEdmonds100

It’s said that in the last two years, more data has been created than all the data that ever was created before that time. And that in two years hence, we’ll be able to say the same thing. Gary King, the head of the Institute for Quantitative Social Science at Harvard University, isn’t certain those statements are exactly true, but certain they are true in essence. And he’s even more certain that the growth in the amount of data isn’t why big data is changing the world.

As he tells interviewer Dave Edmonds in this Social Science Bites podcast, roughly 650 million social media messages will go out today. So to someone trying to make statements about what those messages contain, he posited, would having 750 million messages make anything better? “Having bigger data,” King says, “only makes things more difficult.”

Or to be blunter, “The data itself isn’t likely to be particularly useful; the question is whether you can make it useful.” Which leads to King’s real passion: the analysis of big data. It’s not the ‘big’ or the ‘data’ that really turns the screw; it’s the analysis.

In this conversation, King, uses text analysis as an example of this big data analysis. He notes that some of the tools that text analysis uses are “mathematically similar” to another project he worked on, trying to determine health priorities in the third world by figuring out what’s killing people there. In both cases, the individual, whether someone with a disease or someone with a viral tweet, is less important than the trend.

That, explains King, spotlights the difference between computer scientists’ goals and social scientists’ goals: “We only care about what everybody’s saying.” He then talks about work examining social media and censorship in China. While the work clearly falls into an area that King, a political scientist, would be interested in, the genesis was actually as a test case for the limitations of the text analysis program. But it nonetheless gave useful insight into both how the Chinse government censors material, and why.

King is the Albert J. Weatherhead III University Professor at Harvard. He’s been elected a fellow or eight honorary societies, including the National Academy of Science, the American Association for the Advancement of Science, and the American Academy of Political and Social Science. King also has an entrepreneurial bent – he mentions the company Crimson Hexagon that was spun out of the text analysis work during this interview – and has founded or invented technology for companies like Learning Catalytics and Perusall.

And here’s some, if not ‘big’ data, at least ‘bigger’ data, to consider: This interview marks the 50th Social Science Bites podcast produced by SAGE Publishing. For a complete listing of past Social Science Bites podcasts, click HERE. You can follow Bites on Twitter @socialscibites and David Edmonds @DavidEdmonds100.

Which piece of social science research has most inspired or most influenced you?

This question has been posed to every interview in the Social Science Bites podcast series, but never made part of the audio file made public. Now, as we approach the 50^th Social Science Bite podcast to be published this March 1, journalist and interviewer David Edmonds has compiled those responses into three separate montages of those answers.

In this first of that set of montages, 15 renowned social scientists – starting in alphabetical order from all who have participated – reveal their pick. As you might expect, their answers don’t come lightly: “Whoah, that’s an interesting question!” was sociologist Michael Burawoy’s initial response before he named an éminence grise – Antonio Gramsci – of Marxist theory for his work on hegemony.

The answers range from other giants of social, behavioral and economic science, such as John Maynard Keynes and Hannah Arendt, to living legends like Robert Putnam and the duo of Richard Thaler and Cass Sunstein (and even one Social Science Bites alumnus, Stephen Pinker). Some of the answers involve an academic’s full oeuvre, while others zero in on a particular book or effort. John Brewer, for example, discusses his own background in a Welsh mining town and how when he went to college he encountered Ronald Frankenberg’s Communities in Britain: Social Life in Town and Country. “That book made sense of my upbringing and committed me to a lifetime’s career in sociology,” Brewer reveals.

And not every answer is a seminal moment. Danny Dorling, for example, names a report by his Ph.D. adviser, computational geographer Stan Openshaw, who took two unclassified government reports to show the futility of nuclear war. And not every answer is even an academic work. Recent Nobel laureate Angus Deaton reveals, “I tend to like the last thing I’ve ever read,” and so at the time of our interview (December 2013), named a journalist’s book: The Idealist by Nina Munk.

Other Bites interviewees in this podcast include Michelle Baddeley, Iris Bohnet, Michael Billig, Craig Calhoun, Ted Cantle, Janet Carsten, Greg Clark, Ivor Crewe, Valerie Curtis, Will Davis and Robin Dunbar.

Human beings are social animals, notes economist Michelle Baddeley, and as such the instinct to herd is hardwired into us. And so while this has changed from (in most cases) physically clumping into groups, it does translate into behavior linked to financial markets, news consumption, restaurant-picking and Brooklyn facial hair decisions.

In this latest Social Science Bites podcast, Baddeley – a professor in economics and finance of the built environment at University College London -- tells interviewer David Edmond how modern herding often follows from an information imbalance, real or perceived, in which a person follows the wisdom of crowds. The decision to join in, she explains, is often based an astute reading of risk; as she quotes John Maynard Keynes, “It’s better to be conventionally wrong than unconventionally right.” As a real world example of that, she points to the plight of the junior researcher, whose career is best advanced by serving up their innovative insights along conventional lines.

Apart from reputational damage control, there are pluses and minuses to human herding, Baddeley notes there are advantages to finding safety in numbers: “It’s a good way to find a hotel.” But there are pernicious outcomes, too, like groupthink. In that vein, the economist says she finds partisan herding “more prevalent in a ‘post truth age,’” as individuals join thought groups that reinforce their existing world-view. And it doesn’t help, her research finds, that people are more likely to herd the less well-informed they are.

This has also had dire consequences in financial markets (Baddeley was principal investigator on a Leverhulme Trust project focused on neuroeconomic examination of herding in finance), where pushing against the grain makes for a short career for anyone other than the luckiest professional stockpicker.

Baddeley’s early education was in Australia and her first professional work was as an economist with the Australian Commonwealth Treasury. She then completed masters and doctorate work at Cambridge. Her most recent book is 2013’s Behavioural Economics and Finance  and other works include Running Regressions - A Practical Guide to Quantitative Research (2007) and Investment: Theories and Analysis (2003).

For Alex “Sandy” Pentland, one of the best-known and widely cited computational social scientists in the world, these are halcyon days for his field.  One of the creators of the MIT Media Lab and currently the director of the MIT Connection Science and Human Dynamics labs, Pentland studies ‘social physics,’ which takes a data-centric view of culture and society.

In this Social Science Bites podcast, he tells interviewer Dave Edmonds about the origins of social physics in the barren days before the advent of widespread good data and solid statistical methods and how it blossomed as both a field and for Pentland’s own research. Now, with both plentiful data and very sophisticated statistics, “we can revisit this vision of understanding society, understanding culture, as an alive, evolving animal using these modern techniques.”

The key change, he explains, has been in the amount and the diversity of data -- even if that’s a scary thought from a privacy point of view, “But from a social science point of view it’s Nirvana. For the very first time you can look at complicated, real-time continuous interaction of many different groups carrying out real activities.”

Pentland’s own experimental trajectory reflects those advances, with his early work mediated as much by what was lacking (a good way to deal statistically with language) as what was at hand. This led him to study how much of an individual’s behavior was due to older, pre-language signaling and how much due to more modern linguistic structure. But with time and computational advances, his work ramped up to study how groups of people interact, even up to the scale of a city. That in turn created some fascinating and widely cited insights, such as the more diverse a city’s social ties the more successful, i.e. rich, e city will be.

Some of the methodology involved in doing computational social science is also explored in the podcast, as Pentland describes giving an entire community new mobile phones as one part of the data-gathering process (with privacy protecting institutional controls, he notes) even as “we pestered them with a million questionnaires of standard social science things” during the same study period.

Pentland is well-known in both the public and private spheres as a leading big data researcher, with Forbes recently dubbing him one of the "seven most powerful data scientists in the world." In addition to his work at MIT, he chairs the World Economic Forum’s Data Driven Development council and has co-founded more than a dozen data-centered companies such as the Data Transparency Lab, the Harvard-ODI-MIT DataPop Alliance and the Institute for Data Driven Design. Among his disparate honors are as a 2012 best-article award from the Harvard Business Review,  winning the DARPA Network Challenge run as a celebration of the 40^th anniversary of the internet, and being honored for his work on privacy by the group Patient Privacy Rights.