Mögliche Datenquellen

Praktische Anleitungen

  • Bryce Boe. 2017. PRAW: The Python Reddit Api Wrapper. Read the Docs.

  • Michael Bukachi. 2019. “Extracting YouTube Comments with YouTube API & Python”. Gotrained Python Tutorials.

  • Matthew J. Connelly u. a. 2019. Diplomatic Documents Data for International Relations: The Computational and Historical Resources on Nations and Organizations for the Social Sciences (CHRONOS) Database. Working Paper. https : //

  • Jonathan D. Fitzgerald. 2018. “Working with The New York Times API in R”. Storybench.

  • Pascal Jürgens und Andreas Jungherr. 2016a. A Tutorial for Using Twitter-Data in the Social Sciences: Data Collection, Preparation, and Analysis. Social Science Research Network (SSRN). doi:10.2139/ssrn.2710146. 2710146.

  • Dana Lindquist. 2019. “Using New York Times API and jq to collect news data”. Medium.

  • Jörg Matthes und Matthias Kohring. 2008. “The Content Analysis of Media Frames: Toward Improving Reliability and Validity”. Journal of Communication 58 (2): 258–279. doi:10.1111/j.1460-2466.2008.00384.x.

  • Christian Rauh, Pieter De Wilde und Jan Schwalbach. 2017. The ParlSpeech data set: Annotated full-text vectors of 3.9 million plenary speeches in the key legislative chambers of seven European states. Cambridge: Harvard Dataverse. doi:10.7910/DVN/E4RSP9.

  • Felippe Rodrigues. 2018. “How to scrape Reddit with Python”. Storybench.

  • Matthew A. Russell. 2019. Mining the Social Web. 3. Aufl. Sebastopol: O’Reilly Media.

  • Zachary C. Steinert-Threkeld. 2018. Twitter as Data. Cambridge: Cambridge University Press.