Sahiti Myneni a,b , Nathan Cobb c , Trevor Cohen a. Finding Meaning in Social Media: Content-based Social Network Analysis of QuitNet to Identify New Opportunities for Health Promotion.
a National Center for Cognitive Informatics and Decision Making in Healthcare , UT School of Biomedical Informatics at Houston
b Innovations in cancer Prevention Research, School of Public Health, The University of Texas Health Science Center at Houston, TX, USA
c The Schroeder Institute for Tobacco Research and Policy Studies, Washington, DC, USA
Preventable illness (63% of global deaths)
Modifiable health behaviors account for 30% of cancer related deaths
(Valente, 2010; Christakis & Fowler, 2008)
Thematic analysis to identify behavioral components
Distributional semantics and
vector space modeling
Social network modeling
Content-specific intervention personalization
100 randomly chosen messages
Thanks for hosting the bonfire tonight. I have been dragging around this lawnbag of 750 unsmoked cigarettes, they have just been piling up over the past 25 days.Iwould like to donate them to the bonfire.
Theme(s): Social Togetherness,
It helped so much to hear from all of you. I have tears of relief right now that I feel in control again
Rewards, Social Togetherness
From Qualitative analysis
sad emotion help
Semantic similarity score
Theme-specific similarity score for each pair of QuitNet users
Validation: Five random QuitNet users chosen
QuitNet dataset recorded in 2007, limited in size
Qualitative analysis until thematic saturation
Evaluation framework can be more robust including multiple users
Modifiable health behaviors contribute to the majority of deaths globally
Online social networks provides global perspective and platform to investigate and intervene
A “structure plus content” method to understand inter- and intra-individual behavioral intricacies
Personalized and targeted solutions to initiate or adhere to a positive behavior change
Translational interventions that harness the power of social relationships
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