Go back:
Keehyung Kim | University of Oklahoma
<aside> <img src="/icons/megaphone_gray.svg" alt="/icons/megaphone_gray.svg" width="40px" />
Welcome to AFM 345: Business Applications of Social Media Analytics! 😊
This course was taught by me during Spring 2024 for Undergraduate students enrolled at School of Accounting and Finance, University of Waterloo. Note that some materials were offered exclusively to the enrolled students only.
If you use any part of the materials, please kindly reference this site (http://keehyung.com) and the author (Keehyung Kim). Enjoy!
</aside>
With social media analytics, you can gain in-depth insights into key performance of your business and such insights help improve your standing and influence on social media. Data-driven decision making is critical in today’s business world, and social media analytics gives you a leg up when it comes to ideating campaigns and publishing posts.
This course introduces social media analytics and its applications for extracting managerial insights in accounting and finance. We will cover a variety of data analytics methods from network analysis through text analysis. A main theme of this course is information extraction for decision making - including measuring network metrics, community clustering, identifying influencers, text mining, and sentiment analysis. We will largely focus on business applications of data analytics methods utilizing social media data.
Please check “Course Outline” pdf file for more details.
The proposed course schedules here are tentative, which is subject to change based on progress.
All the course materials (e.g., slides, assignments) can be found here: https://www.dropbox.com/scl/fo/9v9086v9jv4dcsyhqnp3s/AKZPz-UGCStTwMOAa7KaRmI?rlkey=s4szrr66wbemq69mev1pv0lh7&st=x8ul9i66&dl=0