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Twitter's tampered samples: Limitations of big data sampling in social media

Bereich: Forschungspolitik & Entwicklung

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.

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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

 

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

Tags: big data

Kategorie: Zeitschriften

Publikations Datum: 2018

Bezug: Online (download)