ITEC-724 Big Data Analytics and Text Mining (3)

This course helps students understand the tools and techniques used in contemporary analysis of large-scale unstructured textual data with applications for business analytics, international affairs, and a range of social science research topics. While the concept of Big Data is relative, and how it is defined varies from field to field, text-based data is one of the largest sources of data available to the modern investigator. This includes numerous genres of textual data, from email archives, websites, Twitter feeds and other social media, blog posts, speeches, annual reports, published articles, and much more. In the aggregate, these sources can easily run into thousands and thousands of discrete items. This form of Big Data is particularly challenging to the analyst using only traditional forms of content analysis. In this course, students learn techniques to help them begin to see the power of computational approaches to the large-scale analysis of unstructured text-based data. Essentially, this course helps to find the proverbial needle in the data haystack. Crosslist: SIS-724. Grading: A-F only.