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Text & Data Mining: Keeping Up

Designed to introduce you to text & data mining (TDM) at Carnegie Mellon University

Keeping Up with TDMThere are many books, articles, videos, and other information sources that deal with TDM.  This page aims to provide a starting point as well as select sources for keeping up with all things TDM.  If you don't find what you need on this page, please contact your liaison librarian.  In addition, please feel free to suggest sources for inclusion here.

I will first start with two blogs that include the most comprehensive list of web resources for anything text or data mining related, including analyitics, big data, and data science resources:

  • Data Mining Research - a great blog for information including books, news, and a fairly comprehensive list of other blogs.

  • Data Science Central - the industry's online resource for big data practitioners. From Analytics to Data Integration to Visualization, it provides a community experience that includes a robust editorial platform, social interaction, forum-based technical support, the latest in technology, tools and trends and industry job opportunities.

  • KDnuggests - this website includes rankings of blogs, software lists, jobs, links to available data sets, and much more.

  • Planet Bigdata - an aggregator of blogs about big data, Hadoop, and related topics.

Below are a select list of specialized blogs:

  • NovelTM - This is a project blog that aims to to enliven the understanding of the novel, and to establish the methodological foundations of a new disciplinary formations.  It seeks to explore impact how we think about the nature of reading and the way we increasingly access our cultural heritage today by bringing the unique knowledge of literary studies to bear on larger debates about text mining and the place of information technology within society.

  • The Stone and Shell -  In his blog, Ted Underwood, an English Professor at the University of Illinois, says "the question is no longer whether we’re going to do text mining, but how much control we’re going to have over the tools we use."  Thus he pursues this question in his blog, focusing on the eighteenth and nineteenth centuries

  • Social Media, Data Mining & Machine-Learning - The title says it all.  In addition, this blog is a great place for information on conferences, upcoming calls for proposals from journals in the relevant area.

There are hundreds of titles available at CMU libraries.  Use "data mining" or "text mining" as a subject search to retrieve them.

Here are select titles available online to CMU faculty, staff, and students.

  • Data mining: the textbook (2015) - read online
  • Discovering knowledge in data (2014) - read online
  • Practical data mining (2012) - read online
  • Text mining and analysis: practical methods using SAS - read online
  • Trends and Applications in Knowledge Discovery and Data Mining (2014) - read online

Bretts, Megan R. (2012). Topic Modeling: A  Basic Introduction.  Journal of Digital Humanities. 2(1).

Roth, Steffen (2014).  Fashionable Functions: A Google Ngram View of Trends in Functional Differentiation (1800-2000).
International Journal of Technology and Human Interaction, 10(2), 34-58.