Study: Data Mining Can Help Monitor Evolving Consumer Responses to Social Issues
A new study has found that data mining can be used to help monitor evolving consumer responses to social issue campaigns, considering the dynamic nature of public opinion.
The research by Huan Chen, University of Florida College of Journalism and Communications (UFCJC) Advertising associate professor, and research colleague Yang Feng, “Evolving Consumer Response to Social Issue Campaigns: A Data-Mining Cast of COVID-19 Ads on YouTube,” was published in the Journal of Interactive Advertising on June 15.
Chen and Feng, who will join UFCJC in the fall as Advertising Assistant Professor in Artificial Intelligence, proposed a data-mining approach to monitor evolving consumer responses to social issue campaigns. The goal was to identify top-ranked comments on a social issue campaign in the dynamic social media environment and then retrieve popular opinion from the top-ranked comments from a longitudinal perspective.
According to the authors, “To illustrate how to use the approach, we tracked the development of popular opinion contained in top-ranked comments posted about five COVID-19 brand videos that adopted different frames (i.e., employee appreciation, donation, call to action, frontline worker appreciation, and brand promotion).”
They add, “Results indicated that popular opinion resonates with the donation, frontline worker appreciation, and brand promotion frames, whereas popular opinion subverts the employee appreciation and call-to-action frames. Future research should use the proposed approach to reveal the development of evolving consumer comments and then adopt another method, such as experimental design, to explore the impact of the type of campaign frames on the development of evolving consumer comments.”