Please use the most stable release (version 2.0), which is available at https://zenodo.org/record/10956#.VXWcakZWJ-8.
Lexos is an integrated workflow of tools to facilitate the computational analyses of texts, presented in a web-based interface. Functionality provided includes the ability to "scrub" texts (remove punctuation, lemmatize, consolidate characters, remove stopwords, etc), cut or segment texts, and a suite of options for analysis and visualizations, including creating and downloading Document Term Matrices (DTM) of token counts (both word- and character-ngrams or tf-idf); cluster analysis (hierarchical or k-means, with silhouette scores); rolling-window analyses of substring, word, or regex-pattern occurrences; bubble visualizations (of term frequencies); and word clouds (of term frequencies or MALLET-produced topic modelling results). More functionality is being added on an ongoing basis.
Lexos is written primarily in Python 2.7.3 using the Flask microframework, based on Werkzeug and Jinja 2. A heavy dose of Javascript and CSS is included on the front-end. We increasingly incorporate the wiz from D3.js in our visualizations and the power in the scikit-learn modules for text and statistical processing. The directions for setting up the development environment for testing (using localhost:5000) on your local machine are stored in the 0_InstallGuides directory. Please use the most stable release (version 2.0), which is available at https://zenodo.org/record/10956#.VXWcakZWJ-8.
chardet, flask, gensim, matplotlib, numpy, pip, scikit-learn, scipy
The PDF Viewer extension needs to be enabled in the Chrome browser on MacOS.
See the file LICENSE for information on the terms & conditions for usage and a DISCLAIMER OF ALL WARRANTIES.
LeBlanc, M.D., Jensen, B., Kleinman, S. (2015). Lexos. v. 2.0. https://github.com/WheatonCS/Lexos/.
