A new Summer Institute in Computational Social Science organized by Howard University and Mathematica promises to bring the power of computational social science to the issues of systemic racism and inequality in America. This marks the first time the successful SICSS model is being hosted by a Historically Black College or University.

When reading a visualization, is what we see really what we get? There are a lot of ways that visualizations can mislead us, such that they appear to show us something interesting that disappears on closer inspection. Such visualization mirages can lead us to see patterns or draw conclusions that don’t exist in our data. We analyze these quarrelsome entities and provide a testing strategy for dispelling them.

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.

SAGE Campus are pleased to announce that we are launching two new courses to our suite of online data science courses for social scientists. The new short courses, Research Design in Social Data Science and Collecting Social Media Data, are aimed at those studying, teaching or working in social science disciplines who are looking to take their first steps toward working with big-data driven approaches to social science 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.

SAGE Research Methods has launched a new Data Science video collection, with hours of educational material for researchers of all levels and backgrounds.

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.

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.

Open Review: better books higher sales, and increased access to knowledge

Nesta confirmed they are to launch a new Centre for Collective Intelligence Design this summer. The centre will seek to harness the potential of Artificial Intelligence (AI) with a particular focus on the combination of human and machine intelligence.

"Positions in data science require a unique set of job skills that many professionals simply don’t possess.  The level of programming knowledge, understanding of statistics and business sense make for a difficult position to fill. Because of this, many businesses find it difficult to hire appropriately for the position of data scientist." Kayla Matthews gives pointers on ways that companies, looking for data scientists, could stand out in this demanding market for data engineers.