quanteda is developed to achieve following core objectives in quantitative text analysis.

  1. Simplicity and flexibility
    • Create flexible tools for different analytic purposes
    • Provide consistent and intuitive commands for R users
  2. Best practice
    • Facilitate transparent and reproducible workflows
  3. High efficiency
    • Exploit multi-core CPU’s to process large datasets
    • Store large datasets in small RAMs of laptop computers
  4. Inter-operability
    • Allow quanteda to be used in conjunction with other R packages


quanteda is created by Kenneth Benoit in collaboration with a team of core contributors: Kohei Watanabe, Paul Nulty, Adam Obeng, Haiyan Wang, Stefan Müller, Ben Lauderdale, and Will Lowe.


Contributions in the form of feedback, comments, code, and bug reports are most welcome. How to contribute:


quanteda project is supported by the European Research Council grant ERC-2011-StG 283794-QUANTESS.

European Research Council


quanteda’s citation information is available on the Github page.