Analyzing Social Media Data to Understand Consumers' Information Needs on Dietary Supplements

TL;DR

This study uses topic modeling on social media questions to identify consumers' information needs regarding dietary supplements, aiming to improve online resources and understanding of consumer interests.

Contribution

It applies CorEx topic modeling to social media data to accurately categorize consumer questions about dietary supplements, revealing key information needs.

Findings

High accuracy (90-100%) in topic identification

Identified 38 health-related categories from social media questions

Generated insights to improve dietary supplement information resources

Abstract

Despite the high consumption of dietary supplements (DS), there are not many reliable, relevant, and comprehensive online resources that could satisfy information seekers. The purpose of this research study is to understand consumers' information needs on DS using topic modeling and to evaluate its accuracy in correctly identifying topics from social media. We retrieved 16,095 unique questions posted on Yahoo! Answers relating to 438 unique DS ingredients mentioned in sub-section, "Alternative medicine" under the section, "Health". We implemented an unsupervised topic modeling method, Correlation Explanation (CorEx) to unveil the various topics consumers are most interested in. We manually reviewed the keywords of all the 200 topics generated by CorEx and assigned them to 38 health-related categories, corresponding to 12 higher-level groups. We found high accuracy (90-100%) in identifying questions that correctly align with the selected topics. The results could be used to guide us to generate a more comprehensive and structured DS resource based on consumers' information needs.