The COVID-19 pandemic has posed significant challenges for higher education, including the ability to conduct field research and travel. In an effort to address these challenges AU’s School of International Service Doctoral Program will present a virtual fireside chat on Friday, November 13, 2020, featuring our very own Dr. Derrick Cogburn discussing “Big Data Analytics and Text Mining.” The event will take place from 12 pm to 1 pm EST.
Register today at the link.
While universities, faculty, and students are facing tremendous challenges maintaining an active research program during the pandemic, they also have access to an unprecedented suite of methodological opportunities unleashed by the ongoing open data explosion, from the numerous high-quality data repositories serving as recipients of National Science Foundation and other publicly funded research projects, to the existence of powerful open-source data analytics tools, such as R and related packages.
In this fireside chat, Dr. Cogburn will discuss strategies for researchers to exploit such opportunities while also maintaining a healthy work/life balance in the age of COVID-19. In addition, he will discuss academic and non-academic job opportunities and career strategies within this context and will highlight differences across disciplines and the skills required to enhance career success during the pandemic.
Professor Cogburn will also discuss how students can hone these methodological skills in his cross-listed spring/fall seminar “SIS/KSB-ITEC 724: Big Data Analytics and Text Mining”. Participants of the course will learn how to use the R tidyverse and tidytext approaches to text analytics as well as the more traditional tm text mining packages. The course takes a decidedly statistical “bag-of-words” approach to text mining and sentiment analysis but also exposes students to the natural language processing (NLP) approach, referred to as entity recognition (NER). Participants in the course will learn data wrangling using dplyr, data visualization using the powerful ggplot2, and how to build interactive data visualizations using html widgets and R Shiny. In addition, students will learn how to use distributed/cloud computing by learning to conduct text mining on Zorro, the American University High-Performance Computer.