Smokers' Engagement Behavior on Facebook: Verbalizing and Visual Expressing the Smoking Cessation Process
Jezdancher Watti1, Máté Millner1, Kata Siklósi1
1Department of Behavioral Sciences, Albert Szent-Györgyi Medical School, University of Szeged, 6722 Szeged, Hungary.
Smokers use specific language and Facebook reactions when discussing smoking cessation. The "Haha" reaction may indicate less engagement, while "Love" suggests positive progress in quitting.
Area of Science:
- Digital Health
- Behavioral Science
- Social Media Analysis
Background:
- Social media platforms like Facebook are increasingly used for health support.
- Understanding user engagement with online health interventions is crucial for effectiveness.
- Smokers utilize "processes of change" and "motivational language" in online comments.
Purpose of the Study:
- To investigate the relationship between linguistic elements (processes of change, motivational language) and Facebook reaction buttons.
- To determine how different Facebook reactions correlate with engagement in smoking cessation discussions.
Main Methods:
- Analysis of 821 comments from smokers responding to image-based smoking cessation content on Facebook.
- Identification and categorization of "processes of change" and "motivational language" within comments.
- Comparison of linguistic categories with the usage patterns of Facebook reaction buttons (Like, Love, Haha).
Main Results:
- Users employing the "Haha" reaction showed significantly higher "sustain talk" compared to "Like" or "Love" users.
- Combining comments with the "Love" reaction was associated with significantly more "change talk" than not using reactions.
- Facebook reactions can serve as indicators of engagement in the smoking cessation process.
Conclusions:
- The "Haha" reaction may signal negative engagement, "Like" neutral engagement, and "Love" positive engagement in smoking cessation interventions.
- Facebook reactions offer a method to evaluate user engagement with online smoking cessation support.
- This study provides insights into interpreting social media reactions for digital health interventions.
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