Ye Wang, PhD
Ye Wang, PhD
Chair and Professor
Humanities and Social Sciences
University of Missouri-Kansas City
Dr. Ye Wang is Professor and the Chair of the Department of Communication and Journalism. Her publications focus on interactivity and engagement on websites and social media. She has published in leading journals like Journal of Business Research, Journal of Health Communication, Journal of Product & Brand Management, Health Education & Behavior, etc.. Dr. Wang has been collaborating with data scientists on human-AI approach to extracting consumer insights from unstructured text data such as social media content, using computational methods. She was awarded the Research Fellowship of the American Academy of Advertising twice (2017 and 2020). She is a co-PI of NSF’s Open Collaborative Experiential Learning (OCEL.AI) project. Dr. Wang is also an affiliate faculty member with UMKC’s Center for Digital and Public Humanities, the School of Science and Engineering
A Case Study of Using Natural Language Processing to Extract Consumer Insights from Tweets in American Cities for Public Health Crises
The COVID-19 pandemic was a “wake up” call for public health agencies. Often, these agencies are ill-prepared to communicate with target audiences clearly and effectively for community-level activations and safety operations. The obstacle is a lack of data-driven approaches to obtaining insights from local community stakeholders. This study demonstrates how to combine human and Natural Language Processing (NLP) machine analyses to reliably extract meaningful consumer insights from tweets about COVID and the vaccine. This case study employed LDA topic modeling, BERT emotion analysis, and human textual analysis and examined 180,128 tweets scraped by Twitter API’s keyword function from January 2020 to June 2021. The samples came from four medium-sized American cities with larger populations of people of color. The NLP method discovered four topic trends: “COVID Vaccines,” “Politics,” “Mitigation Measures,” and “Community/Local Issues,” and emotion changes over time. The human textual analysis profiled the discussions in the selected four markets to add some depth to our understanding of the uniqueness of the different challenges experienced. Recommendations on communicating vaccination are offered based on the findings: (1) the strategic objective should be empowering the public; (2) the message should have local relevance; and, (3) communication needs to be timely.