Data Mining Methods For The Content Analyst: An Introduction To The Computational Analysis Of Content

Data Mining Methods For The Content Analyst: An Introduction To The Computational Analysis Of Content

Synopsis

This research reference introduces readers to the data mining technologies available for use in content analysis research. Supporting the increasingly popular trend of employing digital analysis methodologies in the humanities, arts, and social sciences, author Kalev Leetaru provides an invaluable guide to these techniques for researchers in these disciplines. This work provides crucial answers for researchers who are not familiar with data mining approaches and who do not know what they can do, how they work, or how their strengths and weaknesses match up to the strengths and weaknesses of human coded content analysis data. Written in accessible and easy-to-understand language, each chapter explains a set of core concepts or analytical strategies from the data mining world, provides examples of how they work, and describes their limitations and strengths. Every technique is considered with regard to its theory of operation; the contexts in which it is appropriate; the nuances to consider when using the technique; and the applicable methodological concerns. Offering valuable insights and guidance for using automated analytical techniques in content analysis research, this guide will appeal to both novice and experienced researchers throughout the humanities, arts, and social sciences.

Product details

If you enjoyed this product share it with others

Customer Reviews

• Be the first to review Data Mining Methods For The Content Analyst: An Introduction To The Computational Analysis Of Content

see all reviews