This summer we've had the pleasure of welcoming four Masters students from UK universities to work with the SAGE Ocean team. All four students have been quite incredible, and have managed to produce a variety of outputs and substantially contribute to our work. In this blog post, they share testimonials of their time in the team.
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?”
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.
I would argue that computational social science necessitates collaboration, and indeed is tamed by it. A collaborative approach provides the necessary structure, goals, and a critical approach to research methods. In response to the question of what computational social science has helped me achieve, it may seem obvious to mention the concrete projects, the outputs, the measurable outcomes. However, for me computational social science has achieved something more substantial and enduring—a new way of working, a new way of thinking, and a new kind of enthusiasm for research.
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).
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.
Teaching and learning resources from the 2018 Summer Institute for Computational Social Science have been made free to access online, allowing more people to explore in depth the field of computational social science.
"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.