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 Coding Analysis Toolkit
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Welcome to the Coding Analysis Toolkit (CAT)

CAT is a free service of the Qualitative Data Analysis Program (QDAP), and hosted by the University Center for Social and Urban Research, at the University of Pittsburgh, and QDAP-UMass, in the College of Social and Behavioral Sciences, at the University of Massachusetts Amherst. CAT was the 2008 winner of the "Best Research Software" award from the organized section on Information Technology & Politics in the American Political Science Association.

For the CAT Quick Start Guide, you can view the PDF file CAT Quickstart Guide or watch the CAT Tutorial - February 23, 2009

May 5, 2010 - CAT is now an open source project! You can host your own version of CAT from the project source code at:
http://sourceforge.net/projects/catoolkit/

Read about the latest innovations in text analytics on the Texifter blog or via a specially curated @scoopit page

CAT Statistics
There are currently 7,259 primary CAT accounts and 1,154 sub-accounts. CAT users have uploaded 6,780 coded datasets and 10,515 raw datasets. They have coded a total of 1,856,570 items and adjudicators have made 166,314 validation choices in CAT.

QDAP Texifter DiscoverText PCAT CAT
What can you do in CAT?

Efficiently code raw text data sets
Annotate coding with shared memos
Manage team coding permissions via the Web
Create unlimited collaborator sub-accounts
Assign multiple coders to specific tasks
Easily measure inter-rater reliability
Adjudicate valid & invalid coder decisions
Report validity by dataset, code or coder
Export coding in RTF, CSV or XML format
Archive or share completed projects
What file types can CAT import?

Plain text
HTML
CAT XML
Merged ATLAS.ti coding
CAT Resources


Have you tried DiscoverText?
Featuring the Facebook Graph & Twitter APIs
What features in CAT do you like?

"I am sitting in a coffee shop coding on my iPad and it looks and works great. I love touch screen coding. Thanks!"

"Adjudication process/Post-adjudication statistics: (Especially in pre-testing) It is a good way to tease out how/why coders are in agreement or disagreement. The process makes coding more accurate and reliable by allowing a collaborative effort in figuring out what codes really mean and how they should be applied to the project."

"Web browser oriented coding is very practical. Not requiring additional downloads or program set up make CAT the best!"

"The simplicity of CAT's lay out is convenient, as is the adjudication feature. The screens are visually compelling."

"Things I like: Reliability comparisons. Ease of coding. Simplicity of the User Interface."

"Easy comparison of quotations coded by different groups.

"Reliability analyses."

"The ease of coding."

"Reliability and the instructions for getting Atlas.ti files into the correct format are great."

"First, for small kinds of text, it is really EASY to use. It's much quicker to learn than a similar package. So, if you need to go through a lot written material, but don't necessarily need very sophisticated tools, then this is a user-friendly way to go.

"I like the simple coding. I think that I will also like the ability to have multiple users code my data as a reliability check, but I've not yet done this as part of any project of my own."

"The validation tool; it saves me time."

"The kappa measurement tool is great because it's easy and quick to use."

"The reliability reports and adjudication features are essential for understanding how coders are performing, and they are intuitive and easily accessible in CAT.

"I also find the memo feature to be critical in understanding the coding process on a group level, where different coders can relay information to one another directly within the coding environment, outside of e-mail."

"The comparison tools are very useful; once you have loaded your dataset correctly it is a quick and easy way to generate Kappa scores."

"We have concrete numbers for inter-coder reliability!"

What would you tell anyone thinking of trying to use CAT for research?

"If you don't like using your mouse or fingerpad, you don't need to if you use CAT. Dragging [a mouse] is...a drag."

"I would strongly support researchers CAT usage and would encourage them to contact the administrator to further improve the program."

"CAT is a great tool to use for research projects. It enables coders to work in an efficient manner in which accuracy can be measured constructively."

"I've already recommended it to several colleagues. I tell folks it is the best, easiest way to compare coding in multi-coder teams."

"Great for text, doesn't work for video (yet). Make sure you know what it is giving you before trying to use it (as with any statistical analysis program)."

"Do it! :)"

"It is a great and easy way to code and analyze data"

"Other qualitative researchers: This is a great program. Read about it, then use it!"

"It is pretty easy to use, and free....we have already started telling our colleagues about it and assisting them with it."

"It's a great way to file / classify / code and memo data."

"It's simple; it's free."

"I would say it's an excellent tool for coding discrete data, such as open-ended survey responses."

"CAT is ideal for de-contextualized coding, and for coding self-contained units or those documents where you're not necessarily concerned with where in the document a theme occurs, only that it does in fact occur."

"The fact that it's Web-based makes it very accessible, and it has a very experienced and reliable team supporting it."

"It provides a number of different handy analytic tools. In one package it allows you to do coding, validation, and other analyses."

"If you have the right type of data, especially data in the form of a series of discrete units of text, it allows you, and more importantly any number of coders (needing only limited expertise in the use of CAT) to code your data very quickly."

"It's a good resource for making sure a large team of coders don't drift"

© 2007-2012 - CAT is maintained by Texifter, LLC and powered by Microsoft ASP.NET, with hosting in a FISMA-compliant environment and project support provided by the Qualitative Data Analysis Program (QDAP), in the University Center for Social and Urban Research, at the University of Pittsburgh and QDAP-UMass, in the College of Social and Behavioral Sciences, at the University of Massachusetts Amherst.
Content on this website was made possible with the following grants from the National Science Foundation: IIS-0917773, IIS-0705091 and IIS-0704210 "Collaborative Research III-COR: From a Pile of Documents to a Collection of Information: A Framework for Multi-Dimensional Text Analysis" as well as IIS-0429293 "Collaborative Research: Language Processing Technology for Electronic Rulemaking." We are also grateful for financial support from the U.S. Environmental Protection Agency and the U.S. Fish & Wildlife Service. Any opinions, findings and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect those of the National Science Foundation.