Section: Research Policy & Development

Social networks are widely used as sources of data in computational social science studies, and so it is of particular importance to determine whether these datasets are bias-free. In EPJ Data Science, Jürgen Pfeffer, Katja Mayer and Fred Morstatter demonstrate how Twitter's sampling mechanism is prone to manipulation that could influence how researchers, journalists, marketeers and policy analysts interpret their data.

You can access the article here.

Citation: Jürgen Pfeffer, Katja Mayer and Fred Morstatter (2018). Tampering with Twitter's Sample API. EPJ Data Science, 2018, 7:50, https://doi.org/10.1140/epjds/s13688-018-0178-0

Authors: Mayer, K., Jürgen Pfeffer, Katja Mayer and Fred Morstatter

Tags: big data