Yang Feng
Associate Professor | University of Florida
Gainesville, FL, UNITED STATES
Yang Feng's research focuses on the role of AI as an information delivery agent as well as a powerful research tool.
Biography
Yang Feng's research focuses on the role of AI as an information delivery agent as well as a powerful research tool. In particular, she examines the impact of algorithm-shaped norms on consumer responses to social media advertising using machine-learning approaches in addition to surveys and experiments. She also investigates the use of emerging technologies, including augmented reality, virtual reality, and 360-degree videos, to generate interactive advertising messages. Her research on augmented reality and privacy issues has been featured in mainstream media, such as Washington Post and Good Morning America.
Areas of Expertise (7)
Consumer Psychology
AI
Artificial Intelligence
Advertising Campaign
Advertising Research and Strategy
Audience Analytics
Consumer Insights
Media Appearances (1)
Dr. Yang Feng on GMA Virtual Match
Good Morning America tv
2020-12-21
Advertising professor Yang Feng was on Good Morning America this morning talking about the use of VR/AR by brands.
Articles (2)
Leveraging Artificial Intelligence to Analyze Consumer Sentiments within Their Context: A Case Study of Always #LikeAGirl Campaign
Journal of Interactive AdvertisingYang Feng, Huan Chen
2022-10-19
Because practitioners and scholars are increasingly using artificial intelligence (AI) to analyze consumer sentiments toward social media–based campaigns, we compared various supervised machine-learning (ML) algorithms (four traditional ML-based algorithms and two proprietary deep-learning-based models from Amazon and Google) in terms of their performances in classifying user comments into a sentiment category.
Evolving Consumer Responses to Social Issue Campaigns: A Data-Mining Case of COVID-19 Ads on YouTube
Journal of Interactive AdvertisingYang Feng, Huan Chen
2022-06-15
Based on previous literature on comment-ranking algorithms and the role of popular opinion, we propose a data-mining approach to monitor evolving consumer responses to social issue campaigns. In particular, the proposed approach can (1) identify top-ranked comments on a social issue campaign in the dynamic social media environment and then (2) retrieve popular opinion from the top-ranked comments from a longitudinal perspective.
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