User testimonials

[kbenoit]

Please use this issue to add your testimonials, experiences, feedback, etc. We would love to hear from you.

Updated consent notice 2017-10-06:

Note that in leaving a testimonial, you provide consent for us to reproduce it on our website http://quanteda.io or in other promotional materials for the package, should we choose to do so. We will attribute this only to your GitHub account, which means in effect that it will not add any additional information than what you will have already posted to this issue (which means the comment and your GitHub username).

Thanks very much!

-- @kbenoit and the whole quanteda team

[BobMuenchen]

The quanteda package has become the starting point for all my text analysis projects in R. This is due to its superb ability to prepare the data for analysis regardless of the method one might prefer. Single words are notoriously ambiguous, and quanteda can help find phrases (ngrams), and convert them to single terms before removing any stop words that they may contain. When the data is prepared, quanteda's convert function makes it easy to transfer the data to a wide range of other packages such as topicmodels or lsa.

quanteda also contains functions to create dictionaries that automate the identification of topics, and it can import and apply the wide range of existing dictionaries that exist in several formats.

[cbpuschmann]

Quanteda is an excellent resource for both research and teaching than complements R in a way that is invaluable to me -- only switching to Python would offer comparable benefits. It is far superior to related packages (e.g. tm) and so well documented that I use it centrally when teaching text mining.

I hope that the package's rapid development will continue, with the integration of further exciting features, such as integration with the package topicmodels, supervised ML, easy application of dictionaries/thesauri etc in the future. Quanteda constitutes a major step forward for social scientists interested in text mining.

[jofrerocabert]

Quanteda has been a greatly valuable tool for my research. Text analysis is a rapidly expanding field with new applications appearing rapidly in the social sciences. This package simplifies many of the tasks and allows me to implement more sophisticated classifiers for a more detailed analysis.

[kbenoit]

Thanks so much @BobMuenchen @cbpuschmann and @jofrerocabert !

[cschwem2er]

Quanteda is my favorite toolbox for natural language processing and its so nice to see how much progress you made within the last year. As of now, the package can even be used as a complete NLP backbone for interactive web apps.
In the future I'd love to see better workflow integration with the tidyverse packages and supervised models.
Thank you so much Ken and the whole quanteda team for creating yet another awesome package! =)

[DenisaKost]

I am a political scientist, without a background either in computer science or natural language processing. I have used quanteda to analyse a large volume of textual data in four different languages from the Balkans. This user-friendly package has allowed me to apply quantitative text analysis to make a major theoretical breakthrough in my field of study, which is post-conflict justice and peacebuilding. I have particularly benefited from quanteda’s meticulous documentation, which I consulted regularly to carry out my analysis.

[lmkirvan]

This package is amazing! I use it on a daily basis to perform a large number of text analysis tasks. The responsiveness of Ken and the rest of the team is simply amazing. They really pay attention to and help their users. Others at my federal agency now use it frequently for text analysis in R too (once others saw how clean my code was and how fast it ran it didn't take much convincing).

I personally use it to understand complaints submitted by hundreds of thousands of consumers. The whole agency benefits from being able to understand more text from our stakeholders faster. Kudos to the whole team.

[kbenoit]

Thanks so much @lmkirvan for the kind words, and keep those feature requests and bug reports coming - we welcome the feedback as a way to improve the package!

[andremog]

I participated in one of the text analysis workshops about the quanteda package in April 2017. The package offers a wide range of functions applicable to many use cases. Even though I am relatively new to text analysis methodologies in general, the package has a very intuitive structure for its commands, making them easy to understand. Its powerful commands allow complex analyses with just a few lines of codes, building and replicating results quickly (as all commands run quite fast). The development team is open to user requests (e.g. requests for new features) and willing to help address difficult use cases. Thanks a lot to the team!

[kbenoit]

Thanks @andremog and glad you found the workshop useful!

[SeraphineM]

Quanteda offers a range of powerfull tools and is currently the best package available for doing quantitative text analysis in R. Apart from this, what I particularly like about the package is the easy implementation of dictionaries in various formats. Noteworthy is here also the impressively quick and efficient support of the developers in case of bugs: keep up the good work and thank you!

[kbenoit]

Thanks @SeraphineM !