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ERIC Number: EJ1351172
Record Type: Journal
Publication Date: 2022-Jun
Pages: 8
Abstractor: As Provided
ISBN: N/A
ISSN: N/A
EISSN: EISSN-1545-679X
An Experiential Learning Project Using Sentiment Analysis of Twitter Posts
Asay, Joel; Crable, Elaine; Sena, Mark
Information Systems Education Journal, v20 n3 p36-43 Jun 2022
In this teaching case, we describe an experiential learning project that allows students to perform sentiment analysis on a set of tweets (posts made on the social media platform, Twitter) by collecting and analyzing posts that include key words selected by the students. Sentiment analysis refers to the process of identifying and categorizing opinions expressed in a piece of text. The project requires students to make edits to an R script, execute the script to save a collection of tweets that contain specific keywords, then open the file and paste the results into a macro-enabled Excel file that is provided. Students then edit the dataset to cleanse the data and write a report to interpret the findings. The assignment requires only a cursory knowledge of programming and Excel. We assign the project to students taking an introductory information systems course but the project could be suitable for courses in business analytics, marketing, social media, computer science, and other subjects.
Information Systems and Computing Academic Professionals. Box 488, Wrightsville Beach, NC 28480. e-mail: publisher@isedj.org; Web site: http://isedj.org
Publication Type: Journal Articles; Guides - Classroom - Teacher
Education Level: Higher Education; Postsecondary Education
Audience: Teachers
Language: English
Sponsor: N/A
Authoring Institution: N/A
Grant or Contract Numbers: N/A