What's real about fake news? : a limited capacity approach to studying online deception comprehension in media multitasking situations
Fake news, largely considered a social media problem (Tandoc, Jenkins, & Craft), can lead to misinformed judgments in important, vital areas, such as healthcare and political processes, or to misguided actions related to responses to deceptive information (Fourney, Racz, Ranade, Mobius, & Horvitz, 2017; Tandoc, 2019). The current health circumstances (i.e., COVID-19 Pandemic) require accurate and immediate news to inform the public about the situation, how to proceed as a community, and how to best protect themselves (e.g., helping them answer questions such as: "Should I wear a mask?", "Should I stay home?", or "Will receiving the COVID-19 vaccine cause a miscarriage?"). To date, there has been much misinformation about the spread of COVID-19, how communities should react, and the correct precautions individuals should take in order to stay healthy and safe (Suciu, 2020). Another impeding force is the increased use of mobile devices is changing the way messages are being processed. Of U.S. adults, 77% own a laptop, 58% have a tablet computer, and 91% own a smartphone (Hilton, 2018). Consequently, media usage behaviors, such as multitasking with several devices, have become widespread (Collins, 2008; Jeong & Hwang, 2012). This study examines the effects of media multitasking on falsity detection in an online experiment with a Qualtrics panel of gen pop (N = 186) where half the sample media multitasked while reading both real and fake news posts and the other half were asked to read real and fake news posts. Results indicated that organic media multitasking behaviors, outside of the experimental procedure, such talking to a spouse or a child or texting on the phone to a friend and media multitasking preferences may be a better indicators of cognitive processing and behavioral intentions in an online media multitasking experiment than manipulating multitasking.
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- In Collections
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Electronic Theses & Dissertations
- Copyright Status
- In Copyright
- Material Type
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Theses
- Authors
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Lynch, Kristen
- Thesis Advisors
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Kononova, Anastasia AK
- Committee Members
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Alhabash, Saleem SA
Chavez, Manuel MC
Richards, Jef JR
Ravizza , Susan SR
- Date Published
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2021
- Program of Study
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Information and Media - Doctor of Philosophy
- Degree Level
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Doctoral
- Language
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English
- Pages
- vi, 179 pages
- ISBN
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9798496513623
- Permalink
- https://doi.org/doi:10.25335/ec3c-1z32