Abstract
This pedagogical paper describes how a graduate course in Text Mining was developed and taught in a fully online format at Quinnipiac University. The software used was SASTM Enterprise Miner. This paper discusses the design, software used and the methodology followed in the course. A critical component of the course required the students to delve deep into social media data by completing a detailed project on analyzing sentiment analysis using large files of social media data. A sample report of this project, which was a key deliverable for the course, is described at length in this paper.
Recommended Citation
Subramanian, Ramesh; Cote, Danielle; and Locke, Jacelyn, "Using SAS software to enhance pedagogy for Text Mining and Sentiment Analysis using social media data" (2016). Proceedings of the 2016 Pre-ICIS SIGDSA/IFIP WG8.3 Symposium: Innovations in Data Analytics. 2.
https://aisel.aisnet.org/sigdsa2016/2