underwood seven ways humanists

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    http://-/?-http://tedunderwood.com/2012/08/14/where-to-start-with-text-mining/http://tedunderwood.com/http://-/?-http://tedunderwood.com/http://void%280%29/https://people.cs.umass.edu/~wallach/workshops/nips2011css/papers/OConnor.pdfhttp://tedunderwood.com/2012/08/14/where-to-start-with-text-mining/http://tedunderwood.com/author/tedunderwood/http://tedunderwood.com/2015/06/04/seven-ways-humanists-are-using-computers-to-understand-text/
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    o ow

    Follow The Stone

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    Build a website with WordPress.com

    https://wordpress.com/?ref=lofhttp://void%280%29/https://prezi.com/hjkj8ztj-clv/map-of-digital-humanities/
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    Detail from an xkcd

    cartoon.

    http://textvis.lnu.se/http://www.laurenceanthony.net/software.htmlhttp://www1.cs.columbia.edu/~delson/pubs/ACL2010-ElsonDamesMcKeown.pdfhttp://moviegalaxies.com/https://xkcd.com/657/http://www.chroniclecareers.com/article/The-New-Modesty-in-Literary/150993/
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    http://-/?-http://tedunderwood.com/2011/11/09/identifying-the-terms-that-characterize-an-author-or-genre-why-dunnings-may-not-be-the-best-method/http://www.laurenceanthony.net/software.htmlhttp://voyant-tools.org/http://sappingattention.blogspot.com/2011/10/comparing-corpuses-by-word-use.htmlhttp://www.ark.cs.cmu.edu/literaryCharacter/http://www.nltk.org/http://en.wikipedia.org/wiki/Categorical_variablehttps://books.google.com/ngrams
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    Words that are consistently more common i n works by William Wordsworth than in other

    poets from 1780 to 1850. Ive used Wordles graphics, but the words have been selected by

    a Mann-Whitney test, which measures overrepresentation relative to a context not by

    Wordles own ( context-free) method.

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    A detail from Fig 7 in So and Long,

    Network Analysis and the Sociology of

    Modernism.

    http://-/?-http://gephi.github.io/http://viraltexts.org/http://www.nytimes.com/2015/04/14/books/stanford-literary-lab-maps-emotions-in-victorian-london.html?_r=0
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    A model treehouse, by Austin and

    Zak CC-NC-SA.

    http://txtlab.org/?p=459
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    A very simple, imagi nary statistical model that

    distinguishes pages of poetry from pages of

    prose.

    http://www.quora.com/What-are-ways-to-prevent-over-fitting-your-training-set-datahttp://www.willamette.edu/~gorr/classes/cs449/overfitting.htmlhttp://llc.oxfordjournals.org/content/23/4/409.full.pdf?keytype=ref&ijkey=z3J27nmCeJkZuTzhttp://onlinestatbook.com/2/regression/intro.htmlhttp://scikit-learn.org/stable/tutorial/statistical_inference/supervised_learning.htmlhttp://www.ats.ucla.edu/stat/r/dae/logit.htmhttps://www.stat.berkeley.edu/~aldous/157/Papers/shmueli.pdfhttp://figshare.com/articles/Understanding_Genre_in_a_Collection_of_a_Million_Volumes_Interim_Report/1281251
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    https://people.cs.umass.edu/~wallach/workshops/nips2011css/papers/OConnor.pdfhttp://tedunderwood.com/2015/05/18/how-quickly-do-literary-standards-change/
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    https://www.python.org/http://www.rstudio.com/http://dsl.richmond.edu/dispatch/pages/homehttp://journalofdigitalhumanities.org/2-1/http://www.sciencedirect.com/science/journal/0304422X/41/6http://tedunderwood.com/2012/04/07/topic-modeling-made-just-simple-enough/
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    http://www.chroniclecareers.com/article/The-New-Modesty-in-Literary/150993/http://athanasius.stanford.edu/Readings/Responses.pdfhttp://boundary2.dukejournals.org/content/40/2/147.abstracthttp://arxiv.org/pdf/1101.0891.pdfhttp://llc.oxfordjournals.org/content/23/4/409.full.pdf?keytype=ref&ijkey=z3J27nmCeJkZuTzhttps://muse.jhu.edu/journals/new_literary_history/toc/nlh.46.1.htmlhttps://people.cs.umass.edu/~wallach/workshops/nips2011css/papers/OConnor.pdfhttp://nowviskie.org/dissertation.pdfhttp://www.jstor.org/stable/10.2979/victorianstudies.56.3.498http://www1.cs.columbia.edu/~delson/pubs/ACL2010-ElsonDamesMcKeown.pdf