Date of Award
Doctor of Philosophy (PhD)
Joseph N. Cappella
What makes health news articles attractable and viral? Why do some articles diffuse widely by prompting audience selections (attractability) and subsequent social retransmissions (virality), while others do not? Identifying what drives social epidemics of health news coverage is crucial to our understanding of its impact on the public, especially in the emerging media environment where news consumption has become increasingly selective and social. This dissertation examines how message features and social influence affect the volume and persistence of attractability and virality within the context of the online diffusion of New York Times (NYT) health news articles. The dissertation analyzes (1) behavioral data of audience selections and retransmissions of the NYT articles and (2) associated article content and context data that are collected using computational social science approaches (automated data mining; computer-assisted content analysis) along with more traditional methods (manual content analysis; message evaluation survey). Analyses of message effects on the total volume of attractability and virality show that articles with high informational utility and positive sentiment invite more frequent selections and retransmissions, and that articles are also more attractable when presenting controversial, emotionally evocative, and familiar content. Furthermore, these analyses reveal that informational utility and novelty have stronger positive associations with email-specific virality, while emotion-related message features, content familiarity, and exemplification play a larger role in triggering social media-based retransmissions. Temporal dynamics analyses demonstrate social influence-driven cumulative advantage effects, such that articles which stay on popular-news lists longer invite more frequent subsequent selections and retransmissions. These analyses further show that the social influence effects are stronger for articles containing message features found to enhance the total volume of attractability and virality. This suggests that those synergistic interactions might underlie the observed message effects on total selections and retransmissions. Exploratory analyses reveal that the effects of social influence and message features tend to be similar for both (1) the volume of audience news selections and retransmissions and (2) the persistence of those behaviors. However, some message features, such as expressed emotionality, are relatively unique predictors of persistence outcomes. Results are discussed in light of their implications for communication research and practice.
Kim, Hyun Suk, "Attractability and Virality: The Role of Message Features and Social Influence in Health News Diffusion" (2014). Publicly Accessible Penn Dissertations. 1331.