[Humanist] 28.688 text-mining
Humanist Discussion Group
willard.mccarty at mccarty.org.uk
Sun Feb 1 08:59:11 CET 2015
Humanist Discussion Group, Vol. 28, No. 688.
Department of Digital Humanities, King's College London
Submit to: humanist at lists.digitalhumanities.org
Date: Sat, 31 Jan 2015 09:41:26 -0800
From: Stéfan Sinclair <sgsinclair at gmail.com>
Subject: Re: text mining (Vol 76, Issue 28)
In-Reply-To: <mailman.3.1422702003.16001.humanist at lists.digitalhumanities.org>
I'd encourage you to have a look at The Programming Historian if you haven't already: http://programminghistorian.org/.
Another fantastic resource is "Text Analysis with Topic Models for the Humanities and Social Sciences": https://de.dariah.eu/tatom/.
Another link of interest is the Methods Commons http://hermeneuti.ca/methods, which contains a set of recipes (the tools mentioned aren't always functional, but the recipes are more about conceptual tasks anyway).
I'm also in the process of writing, with Geoffrey Rockwell, an introductory guide to Literary Text Mining with iPython: http://nbviewer.ipython.org/github/sgsinclair/alta/blob/master/ipynb/ArtOfLiteraryTextAnalysis.ipynb. I'm filling this in during the winter term, so it's definitely a work in progress. There are a ton of guides out there and we hope to orient this one more closely to humanistic perspectives (even if the first version may be more mechanical than we hope later revisions will be).
Prof. Stéfan Sinclair, Digital Humanities, McGill University
Department of Languages, Literatures & Cultures
Office 341, 688 Sherbrooke St. W, Montreal, Quebec, Canada H3A 3R1
Tel. (1) 514-398-4400 x094950
>> On 28.01.2015, at 07:52, Humanist Discussion Group <willard.mccarty at mccarty.org.uk> wrote:
>> Humanist Discussion Group, Vol. 28, No. 679.
>> Department of Digital Humanities, King's College London
>> Submit to: humanist at lists.digitalhumanities.org
>> Date: Tue, 27 Jan 2015 08:46:16 -0600
>> From: "Drew VandeCreek" <drew at niu.edu>
>> Subject: text mining
>> I am an historian trying to learn about text mining. I have posted an elementary question or two on the list before.
>> Today I ask you - Are there any materials, published or otherwise, aimed at providing the novice with a basic introduction to text mining (i.e., how it works, steps that typically comprise a project, etc.) and/or slightly more advanced materials providing the reader/user with a discussion of the types of questions that researchers using text mining technology typically pose, perhaps a review of some major software packages available, and and how to determine which software package is appropriate for a particular research question?
>> Drew E. VandeCreek
>> Director of Digital Initiatives
>> University Libraries
>> Northern Illinois University
>> DeKalb, IL 60115
>> (815) 753-7179
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