Academics face various pressures, from research teaching and administrative duties. The best way to create a positive culture in academia is to share. However, it may sometimes feel like there is no incentive to share teaching materials, if I have spent so many hours developing this work, why should I just hand it over to someone, “what’s in it for me?”
It’s all about incentives. The current academic ecosystem incentivises publication in high impact factor journals and grant capture above all else, but there is more to being an academic than producing journal articles and winning grants. Luckily there are an increasing number of initiatives that are helping academics get credit for more of the work they do and increase their broader impact. This post rounds up some of the most interesting efforts.
The beginning of term is nearing. You’re teaching a new module on Computational Social Science (CSS). The field is developing rapidly and so are best practices around teaching the theory, methods and techniques to students.
Where do you start when you’re putting together your teaching materials? Do you visit the websites and blogs of academics who are experienced in teaching CSS to look for resources? Do you search online for syllabi, reading lists and tutorials? Maybe you scour YouTube for videos to include in your slides?
Together with a group of UK academics, the SAGE Ocean team have been digging into where academics go to find teaching materials and what the barriers are for academics who want to share, reuse and give and get credit for the materials they produce for teaching. This post includes thoughts from the group on what’s needed to promote a stronger culture of sharing teaching materials in CSS. And we’ve curated a list of our favorite resources for you too!
As the participants gear up for the 2019 Summer Institute in Computational Social Science (SICSS), starting June 16th at Princeton and the 11 alumni-led partner locations situated right across the globe, we caught up with the founders of the SICSS, Chris Bail and Matt Salganik to find out how it all got going, the move to a data intensive society and the benefits of learning data science skills to make the most of this new data.
Sam Gilbert demonstrates the value of big search data for social scientists, and suggests some practical steps to using internet search data in your own research.
As the leader of a data science team at the Urban Institute, I get to work on interesting issues that intersect data science and social science every day. By data science, I mean technical tools, architectures, and processes that are borrowed from computer science and are atypical in the social sciences. This is a slightly more limited definition than most would have for the term data science, but because so much of what defines a data scientist at Urban also defines a researcher — cleaning data, analyzing it, visualizing results, etc. — my definition draws a finer line.
Earlier this year Allen AI were announced as the winners of the NYU Coleridge Initiative’s Rich Context Competition. The goal of the competition was to automate the discovery of research datasets and the associated research methods and fields of social science research publications. You can find out about all the finalists and their work here.
We caught up with Allen AI to talk about the work and their involvement in this year’s competition.
Watch our panel event from the ESRC Festival of Social Science on what skills social scientists will need to be able to do the social research of the future.
SAGE Research Methods has launched a new Data Science video collection, with hours of educational material for researchers of all levels and backgrounds.
At the end of February we ran a most enthralling event experience. Three panelists, two hosts and about 20 attendees all put their headsets on from their labs, offices and homes to join a virtual classroom decorated with trees, a castle, a slightly scary tiger and a hippo, to talk about the future of VR in social science research.
Find out more about the field of collective intelligence by tuning into these vox pops, filmed
The second annual Social Science Foo Camp took place at Facebook’s headquarters in Menlo Park at the start of this month, convening an eclectic mix of more than 200 social scientists, technologists, funders, policy makers, businesspeople and writers.
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.
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.
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)
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.