Sentiment Analysis: Beginner Text Mining
Using Language Processing to Assess Social Media Reactions
Enroll in Course
This course is for you if:
- You have open text (or free text) data like emails sent to your organization, comments on your social media posts, or notes on prospects that you want to use for analysis.
- Your organization has conducted a survey with open-text responses and you want to find out if there is a theme among them.
- Your direct mail letters have lost their freshness and you need to be inspired by your donor pool.
- You would love to know if there is a specific job title that is correlated to your higher-end donors.
This course uses social media posts and reactions to show you how to get at all of these needs as well as any other need that you may have around written text. Using what is now called Large Language Modeling, this sentiment analysis course will show you how to take sentences and paragraphs, split them into words and phrases, and then analyze those words and phrases against a reaction (which you can, after the course, use giving as the reaction to analyze against).
As your starter text mining journey, you will learn how to download reactions and comments to your organization’s Facebook and X (Twitter) posts, and then process them to identify what specific words and phrase that your organization uses that attract the best reactions. Natural language processing skills, including adding sentiment like "good," "bad", "angry", etc., is also demonstrated.
The course includes:
- Videos explaining the theory of natural language processing and attaching sentiment to words and phrases
- Walk throughs of exercises where you use your own organization's data for immediate insights
- Links to the software recommended and videos on how to download and install the packages
- Resources listed on every lecture to give you more information on the topics
Your outcome from the course will be an analysis of the reactions to your organization's Facebook and Twitter posts. Once you have the skill, you'll be able to analyze any variety of text from any source, including contact reports, prospect emails, and survey responses, to name a few.
Your Instructor
Marianne Pelletier has over 35 years of experience in fundraising, with the majority in prospect research and prospecting. She is one of the first adopters of donor modeling and data mining techniques, and is now a world-renown leader on this segment of the research profession. Her prospect research experience began when she was a research analyst for Harvard and Lesley Universities. She later served as a department director for Carnegie Mellon University and Cornell University.
Pelletier’s career also includes running an annual giving program with average increased revenues of 27% per year and providing software consulting through the Datatel Corporation, teaching clients both how to use their new software and assisting them with better analysis and more efficient processing. She occasionally serves as a best practices consultant through CampusWorks.
Pelletier is a recipient of a lifetime achievement award from the New England Development Research Association and a Woman of the Year designation by the National Association of Professional Women, along with earning an entry into the Marquis Who's Who in America annual directory. She has served as a volunteer for both election campaigns and social service agencies. She has served on the boards of the New England Development Research Association, the Upstate New York chapter of Apra, and has served as secretary for the Apra International board. She currently serves as a trustee for Habitat for Humanity of Tompkins County and the Finger Lakes chapter of AFP.
Pelletier is a graduate of Rockford University, and earned her MBA at Southern New Hampshire University. Her recent workbook, Building Your Analytics Shop: A Workbook for Nonprofits, was a finalist for the Terry McAdam Award in 2016.