<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Digital Scholarship | Clifford B. Anderson</title><link>https://www.cliffordanderson.net/tags/digital-scholarship/</link><atom:link href="https://www.cliffordanderson.net/tags/digital-scholarship/index.xml" rel="self" type="application/rss+xml"/><description>Digital Scholarship</description><generator>HugoBlox Kit (https://hugoblox.com)</generator><language>en-us</language><lastBuildDate>Fri, 02 Oct 2015 00:00:00 +0000</lastBuildDate><image><url>https://www.cliffordanderson.net/media/icon_hu_1f25fc939507c92a.png</url><title>Digital Scholarship</title><link>https://www.cliffordanderson.net/tags/digital-scholarship/</link></image><item><title>New 'Text Mining' Tech Tools Boon for Vanderbilt Researchers</title><link>https://www.cliffordanderson.net/blog/text-mining-tools/</link><pubDate>Fri, 02 Oct 2015 00:00:00 +0000</pubDate><guid>https://www.cliffordanderson.net/blog/text-mining-tools/</guid><description>&lt;p&gt;Vanderbilt University scholars can now take advantage of new technological tools to extract and analyze huge amounts of text, with the potential for increased research opportunities across disciplines. Owen faculty members Catherine Lee, Michael Stuart and Richard Willis have been working with Vanderbilt Libraries to conduct a semantic analysis of historical earnings conference calls of publicly traded firms, using a new application program interface to the LexisNexis Academic database.&lt;/p&gt;
&lt;p&gt;Integral to the Owen research project and others is the campus&amp;rsquo;s growing XQuery expertise. &amp;ldquo;As the demand for digital scholarship support rises across campus, libraries are building on their deep knowledge of databases with new programming skills, like XQuery,&amp;rdquo; says Clifford Anderson, director for scholarly communications at the library. &amp;ldquo;In particular, XQuery is a good match for the digital humanities; digital humanists frequently look for patterns among large quantities of loosely structured documents.&amp;rdquo;
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