In computational social science there are great hopes and enthusiasms connected with the availability of new data sources. In this episode, we will be talking about working with one of these new data sources: digital trace data.

Once people interact with digital devices (such as smart phones and smart devices) and services (such as Facebook or Twitter), their digitally mediated interactions leave traces on devices and services. Some of those are discarded, some are stored. Some are available only to the device maker or service provider, some are available to researchers. This last category of digital trace data, those that are stored and available to researchers, has spawned a lot of research activity and enthusiasm over a new measurement revolution in the social sciences. But somewhat more than ten years into this "revolution", the limits of digital trace data for social science research are becoming just as clear as their promises. Before we look at studies using digital trace data, it is therefore necessary that we look a little more closely at what they are, what characteristics they share, and how this impacts scientific work with them.

Chapters:

00:00 - Introduction
00:18 - Digital trace data
12:11 - Digital trace data in political science
15:42 - Making sense of online censorship decisions
21:24 - It's attention, not support!
30:03 - Learning about the world with computational social science
33:49 - Conclusion

Script to episode with references and further readings:

http://digitalmedia.andreasjungherr.de/css.html#digital-trace-data-typical-approaches-in-computational-social-science-2