Fake News versus User Motivation: Who wins?
“Fake news” has become a phenomenon all ages recognize and have had to confront some level of. Social platforms, notably including Facebook and Twitter, have implemented functionality to attempt to slow the spread of fake news. In this article, I’ll be deconstructing the article “How Types of Facebook Users Approach News Verification in the Mobile Media Age: Insights from the Dual-Information-Processing Model” by Rebecca Ping Yu.
The introduction provides a clear explanation of what the study’s purpose is and why it’s an important topic to explore. It includes a summary of popular social platforms, fake news, and this combination’s impact on societies around the world.
The article explicitly cites the Dual Process Theory as the perspective the author determines analysis through. The Dual Process Theory contends that humans use two processing styles to understand information: a quick, automatic one and a more deliberate, logical one. Using the DIP model, the study “considers both motivation and ability to understand how and when Facebook users verify news.”
The study asks several research questions, but the one most closely related to the DIP model is: What user-types can be identified by taking into account the mixed motivations for Facebook use? The DIP model “suggests that motivations or goals are important precursors of elaboration, such that motivated individuals are more likely to rigorously evaluate information.” Past research has focused on factors such as motivations of Facebook use as a way to determine this relationship, but little has focused on user-types by motivations for information processing, or in this case, the processing of fake news. The author hypothesizes those with higher motivation are more likely to verify news, which is supported by the DIP model and previous research.
The author uses more than 40 resources in its literature review to create a context for each level of its analysis. It does this by beginning the literature review on the validity of the DIP model. It then touches on overarching research related to each research question broken down into the following sections: Facebook user-types by motivation and mode of information processing, mode of information processing and news verification, and the role of mobile Facebook use in the news verification process.
The study disseminated a survey among Taiwanese citizens who were over 20 years old and used Facebook to gain quantitative insight. The survey used control variables, the independent ones, of age, gender, education, income, frequency of news use, and news attention. The latter two were used in the eligibility process. The dependent variables included motivation for Facebook use, level of elaborative and selective processing, and information evaluation. Participants were asked a series of questions in each category and prompted to choose an option they best fit into. For example, “When you encounter news on social media, how often have you (1) checked who the authors of the news are; (2) checked whether contact information for the authors or organization is provided; (3) verified the authors’ qualifications or credentials; (4) considered the authors’ goals for posting news; (5) checked to see if the news is current; (6) sought out other sources to validate the news you see; (7) looked for an official ‘stamp of approval’ or a recommendation from someone you know; (8) considered whether the news represented is opinion or fact; (9) checked to see that the news is complete and comprehensive.”
The study ultimately expanded the DIP model to analyze personal news verification process on Facebook. This is an increasingly important research topic as social media becomes an integral part of our mass media ecosystem. On a personal note, I’ve witnessed social media platforms make or break massive social movements in 2020, which includes the mass spread of either vetted or fake news. The study results did support the hypothesis by finding those with high motivation, labeled as the user-type of omnivores, were more likely to verify news compared to leisure-convenience seekers and lower information-seeking motivations. Most results aligned with previous research but was expanded by terms of further breaking down motivation to information-seeking, information sharing, self-archiving, self-expression, and social interaction.
