What is it?
RLetters currently allows users to perform the following sorts of textual analyses on sets of articles:
- Compute term frequency information (for single words or multiple-word phrases)
- Compare word usage in two different datasets
- Graph dataset by publication date
- Determine statistically significant pairs of words (collocations) or associations between words at a distance (cooccurrences)
- Compute network of words used around a focal word
- Extract references to proper names (locations, people, organizations)
- Export dataset as citations in a variety of formats
And the Solr backend that powers RLetters allows users to perform a wide variety of complex searches:
- Searching on the basis of particular fields (“year:2010”, “authors:Johnson”, or “title:fish”)
- Boolean operators (“darwin OR huxley”)
- Wildcard search ("*fish” or “wom?n”)
- Text stemming (“evolution” matching “evolutionary” or “evolutionist”)
- Fuzzy matching (matching words similar to the requested term)
- Proximity searching (two terms within N words of one another)
How to get it
The current version of RLetters is v2.0.1, released on January 12, 2015. You can download that release, and read more about installing and deploying RLetters. You can check out a live deployment of RLetters by visiting the evoText project.
RLetters is developed by Charles Pence and his research group. It was originally developed as part of the evoText Project, led by Grant Ramsey and Charles Pence. The project was supported in 2015–2016 by the National Science Foundation, NSF #SES-1456573. Our early efforts in content licensing were gratefully assisted by the University of Notre Dame Hesburgh Libraries. The work has also been supported by the National Evolutionary Synthesis Center (NESCent), NSF #EF-0905606.