TY - CHAP T1 - Levels of trace data for social and behavioural science research T2 - Big Data Factories: CollaborativeĀ Approaches Y1 - 2017 A1 - Kevin Crowston ED - Sorin Matei ED - Sean Goggins ED - Nicolas Jullien AB -

The explosion of data available from online systems such as social media is creating a wealth of trace data, that is, data that record evidence of human activity. The volume of data available offers great potential to advance social and behavioural science research. However, the data are of a very different kind than more conventional social and behavioural science data, posing challenges to use. This paper adopts a data framework from Earth Observation science and applies it to trace data to identify possible issues in analyzing trace data. Application of the framework also reveals issues for sharing and reusing data.

JF - Big Data Factories: CollaborativeĀ Approaches PB - Springer Nature SN - 978-3-319-59186-5 ER -