We are excited to announce that the finalists for the NYU Coleridge Initiative’s Rich Context Competition have been selected. The competition challenged computer scientists to find ways of automating the discovery of research datasets, fields and methods behind social science research publications. 20 teams from 8 countries submitted letters of intent and four finalists have been chosen. We will be live webcasting the finalists’ presentations as well as the announcement of the winner on February 15.
Virtual Reality technology is opening previously locked doors to researchers in the social sciences. But how viable is it really as a research tool? We take a look back over the history of experimental research in human perception and response to consider the future of VR in experimental design.
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).
Calling all social scientists. How were you trained? How are you keeping up (or not) with new developments in this rapidly changing digital world? How are you training your students?
This was the subject of an event sponsored by SAGE Ocean as part of the ESRC’s 2018 Festival of Social Science. In case you are not aware, Sage, who have been at the forefront of publishing qualitative work, have now launched SAGE Ocean – an initiative “to help social scientists to navigate vast datasets and work with new technologies”.
Last week, a mix of PhD students, early career and tenured researchers met in Cologne to discuss their latest projects around bias and discrimination on social media, and the algorithms underpinning many of the most pervasive services we use today.
Watch these short videos as leading academics present at this year’s inaugural Social Science Foo Camp discuss the opportunities and challenges presented by big data and the move to more computational methods.
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)
Last month we were lucky enough to have Pablo Barberá, Assistant Professor of Computational Social Science at the London School of Economics deliver the 5th SAGE Ocean Speaker Series.
Mirsad Hadžikadić, President of the Computational Social Science Society of the Americas (CSSSA) kicked off this year’s annual conference in Santa Fe.
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
A little over a week ago, I posted a blog celebrating 39 women in computational social science. We knew there would be so many more amazing researchers to add, and the social science community duly delivered, suggesting plenty of women that should also be celebrated. Therefore, rather fittingly on #AdaLovelaceDay we have published an updated list. The number has now more than doubled, and we hope that it is a good start for anyone looking for a supervisor for their PhD, or just wanting to see what other doctoral fellows are working on.
I want to share with you this list of 39 female researchers that are all crushing it in the social sciences and humanities with their innovative use of computational methods and very cool explorations of cutting edge tech. Follow them, read their papers and collaborate!
This month the Product Innovation team at SAGE have launched the SAGE Labs site that will showcase the experiments and projects that the team are currently working on.
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.