In the lead up to International Women’s Day on Friday March 8th, we posed a series of questions to leading academics. Here Laura K. Nelson, explores how we nurture an academic landscape that is more accessible to women.

It’s an exciting time to be in social science. Social media, digital identities and the world of big data has opened up new ways for social scientists to study and examine social phenomenon.

Some examples include using online search patterns to predict the spread of disease, tracking near real-time Twitter data to understand political movements or using location data to understand interpersonal interactions.

The move to a digital world has created a innovative new area of social science called computational social science (CSS).

While computers and instantaneous communications seem to have increased the complications of our daily lives, in the hands of researchers, these tools can move us toward a form of simplicity that furthers understanding of complex dynamics.

Being a data scientist with a sociological background is extremely valuable in trying to answer research questions to advance contemporary humanity. It goes beyond programming skills or just applying algorithms to data.

I recently got jazzed about two findings coming out of the world of computational social science, primarily because they hit so close to my home (hello, junior faculty feeling the pressure to produce)

Throughout history humanity has had the urge to predict the future. The Greeks consulted the Delphi Oracle, whereas the Romans inspected sheep entrails and modern day sages poke around tea leaves to get the skinny on the future. This desire to predict the future has found its way into finance where modern day Haruspices pop up on television to make confident boasts about the future direction of the share du jour. All, but the very fortunate of these modern day prophets fail at their impossible task.  

Widely used apps like Facebook, Twitter or Google Maps count millions of users and are already deeply entrenched in our daily social life. However, while we know that mobile map applications are used quite often, we know very little about how they are used

What the Cambridge Analytica debacle and the resulting U.S. Senate hearing revealed in no uncertain terms is that the U.S. does not have adequate data privacy laws

Computational Social Science boils down to Social Scientists using data processing and data science computation tools (think R, Python etc) to analyze data about people and relationships.

In June, I attended the second iteration of the Summer Institute for Computational Social Science (SICSS), an intensive two-week program held at Duke that was intended to bring together researchers from across the social science and data science disciplines to learn and discuss topics in computational social science (CSS). Each day, the organizers Chris Bail and Matt Salganik taught mini-lectures on different CSS topics, we split into groups to work on activities together, and a speaker came in to present their research.

Today, there is a new window of opportunity to adopt agent computing as a mainstream analytic tool in economics. Here, I discuss four major aspects in which this technology can improve economic policymaking: causality and detail, scalability and response, unobservability and counterfactuals, and separating design from implementation. In addition, I highlight the crucial role that policy agencies and research funders have in this endeavor by supporting a new generation of computationally-enabled social scientists.

Agent computing is a simulation tool that has been successfully adopted in many fields where policy interventions are critical. Economics, however, has failed in doing so. Today, there are new opportunities for bringing agent computing into economic policy. In this post, I discuss why this technology has not been adopted for economic policy and point out new opportunities to do it.

News media serves as a window into the society its readership represents. A newspaper’s description of a social group both demonstrates and constructs perceptions of that group within its audience. Understanding long-term trends or spatial differences in the representation of minority groups in news media can contribute to ongoing theoretical debates about the role and perception of minority groups in society. 

Fifty years after the "Summer of Love" transformed American youth culture, Andrew Anglin, the proprietor of the neo-Nazi website The Daily Stormer, announced to his followers that the summer of 2017 would be "The Summer of Hate."

With so much diverse data to dig into, the future of quantitative social science is exciting, particularly for those studying the granularities of individual-level behavior. In doing so, we must make sure that this research is ethical, robust and ultimately useful

Nowadays, issues related to the diffusion of fake news, rumours, hoaxes, as well as the diffusion of malware and viruses in online social networks have become so important as to transcend the virtual ecosystem and interfere with our businesses and societies. Currently, we are unable to effectively deal with these issues.

By Timo Hannay

Here's a multiple-choice question: Is the internet (a) the most open, egalitarian and empowering means of communication ever devised, or (b) a dystopian nightmare populated by hucksters, trolls and miscellaneous abusers of human rights? The answer is, of course, (c) all of the above and much else besides. This stark contrast between the internet's light and dark sides has become a defining characteristic of the digital age, but is not an inevitable consequence of the mostly innocuous technologies on which it's built. Rather, it is the product of their bewilderingly diverse and eccentric user base – otherwise known as humanity.

The first-ever “Social Science FOO Camp” was held a couple of weeks ago at the headquarters of Facebook in Menlo Park, California