Difference between revisions of "TextAnalysis"
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*[http://toolingup.stanford.edu/?page_id=981 Stanford's Introduction, from ''Tooling Up for Digital Humanities''] | *[http://toolingup.stanford.edu/?page_id=981 Stanford's Introduction, from ''Tooling Up for Digital Humanities''] | ||
*[http://people.cs.umass.edu/~wallach/workshops/nips2011css/papers/OConnor.pdf For the social scientists] | *[http://people.cs.umass.edu/~wallach/workshops/nips2011css/papers/OConnor.pdf For the social scientists] | ||
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| + | ==Python== | ||
| + | * [http://www.pythonlearn.com/book.php Python for Informatics], an applied but comprehensive introductory Python text with sections on text parsing | ||
| + | * [http://fbkarsdorp.github.io/python-course/ Python Programming for the Humanities] | ||
| + | * [https://www.python.org/downloads/ Download and install Python] | ||
| + | * [https://www.jetbrains.com/pycharm/ Download and install PyCharm], an Integrated Development Environment (IDE) for Python | ||
==R== | ==R== | ||
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* Matthew Jockers, Text Analysis With R for Students of Literature (PDF [http://onesearch.northeastern.edu/NU:NEU_ALMA51213317900001401&tabs=viewOnlineTab available for download] via the NEU Library) | * Matthew Jockers, Text Analysis With R for Students of Literature (PDF [http://onesearch.northeastern.edu/NU:NEU_ALMA51213317900001401&tabs=viewOnlineTab available for download] via the NEU Library) | ||
* [http://cran.at.r-project.org Download and install R] | * [http://cran.at.r-project.org Download and install R] | ||
| − | * [http://www.rstudio.com Download and install RStudio] | + | * [http://www.rstudio.com Download and install RStudio], an Integrated Development Environment (IDE) for R |
* [http://www.rseek.org RSeek] (search tool for finding resources on R) | * [http://www.rseek.org RSeek] (search tool for finding resources on R) | ||
* [http://www.cyclismo.org/tutorial/R/types.html Simple data types in R] | * [http://www.cyclismo.org/tutorial/R/types.html Simple data types in R] | ||
Revision as of 04:39, 24 February 2016
Resources for Exploring Text Analysis
- "Where to Start," courtesy of Ted Underwood
- Stanford's Introduction, from Tooling Up for Digital Humanities
- For the social scientists
Python
- Python for Informatics, an applied but comprehensive introductory Python text with sections on text parsing
- Python Programming for the Humanities
- Download and install Python
- Download and install PyCharm, an Integrated Development Environment (IDE) for Python
R
- Matthew Jockers, Text Analysis With R for Students of Literature (PDF available for download via the NEU Library)
- Download and install R
- Download and install RStudio, an Integrated Development Environment (IDE) for R
- RSeek (search tool for finding resources on R)
- Simple data types in R
Topic Modeling
- Megan R. Brett's "Basic Introduction" (conceptual)
- Scott Weingart's "Guided Tour" (comprehensive, lots of links)
- Ben Schmidt's article about Latent Dirichlet allocation's (LDA's) limitations
Tools
- MALLET (An open-source, Java-based LDA package)
- GUI Tools that use MALLET
- Stanford Topic Modeling Toolbox
word2vec
- Ben Schmidt's Blog Post on Vector Space Models
- which links to his R wrapper package for word2vec
Miscellaneous text analysis tools
- Voyant Tools
- Laurence Anthony's AntConc, a GUI concordancing and text analysis toolkit
- CasualConc, a Mac OSX-native toolkit (AntConc's Mac version is ported)
- David McClure's TextPlot (a Python package that produces force-directed network of words in a text, based on estimated kernel densities)
- Bookworm
Corpus building
Some places to get text
Plain text
- Project Gutenberg
- Early English Books Online (EEBO) (some texts TEI-encoded)
- Early Caribbean Digital Archive (ECDA)