Fake News Should Be Regulated Because It Influences Both “Others” and “Me”: How and Why the Influence of Presumed Influence Model Should Be Extended

Abstract

We argue that the influence of presumed influence (IPI) model (Gunther & Storey, 2003) should be extended through an additional interaction term between the presumed effects of media on “others” (PME3) and the “self” (PME1). Doing so would enable testing of whether individuals who perceive a mutually shared influence of the media show stronger support for censorship. The IPI model does not suffer from the methodological limitations of the conventional third-person effect literature relying on other–self disparities (i.e., PME3–PME1), but it focuses entirely on the main effect of PME3; thus, insufficient attention is paid to the role of PME1 in explaining the influence of presumed influence. To validate this Extended IPI model, and determine how it compares with other models, we compared individuals’ presumptions about the effects of fake news on others (PFNE3) and themselves (PFNE1), and how PFNE3 and PFNE1 interact to influence individuals’ support for policies prohibiting the potential negative effects of fake news. We found that individuals’ support for government interventions and sanctions for fake news creators and sharers was stronger if they believed that fake news influenced both other people and themselves. The theoretical and methodological implications of the Extended IPI model are discussed.

Acknowledgments

This work was supported by the National Research Foundation of Korea Grant funded by the Korean Government (NRF-2016S1A3A2925033).

Notes

¹ According to Chung and Moon (2016), the PME3 coefficient is the same as the sum of the coefficients of the subtractive and additive terms, whereas the PME1 coefficient is the same as the difference in coefficients of the subtractive and additive terms.

² It would also be possible to detect a significant interaction effect when respondents have low PME3 and PME1. To prevent potential misinterpretation of the statistically significant interaction effect, most statistical textbooks (e.g., Cohen, Cohen, West, & Aiken, 2003, pp. 272–287; Hayes, 2013, pp. 234–238) strongly recommend that interaction effects be probed with both the “pick-a-point approach” (i.e., Table 3 in this study) and an “interaction plot” (i.e., Figure 2 in this study).

³ In general, respondents exposed to fake news, compared with respondents not exposed to it, were more educated, wealthier, and more progressive. They also had stronger ideologies, stronger political efficacy, and a greater interest in politics. Furthermore, they spent more time consuming news but had low trust in journalists; they also participated more actively in politics. For detailed statistics, contact the authors.

⁴ Kakao-talk is the most popular social networking site in South Korea.

⁵ The presumed fake news effect measures are different from conventional measures of presumed media effects in terms of their format and number of items. In the IPI model, presumed media effects were measured via a direct question, such as “How influential do you think the media are on …?” Our measures, on the other hand, were developed based on McGuire’s (1968) persuasion model, which involves assessing respondents’ perceived attention (i.e., first item), acceptance (i.e., second item), and behavior (i.e., third item). Although it is undeniable that this difference in the measures might create a validity problem, we do not think that it would be a serious one. We have two reasons for this: First, our measures and the conventional measures share a key term, “influence,” implying that our measures warrant a minimum level of face validity. Second, as shown by the Cronbach’s alpha coefficients, the first two items are highly related with the third, indicating that these items do not seriously deviate from the third.

Additional information

Notes on contributors

Young Min Baek

Young Min Baek (Ph.D., University of Pennsylvania, 2011) is an associate professor in the Department of Communication at Yonsei University. His research interests include data science, quantitative research methodology, and media effects.

Hyunhee Kang

Hyunhee Kang (M.A., Yonsei University, 2015) is a Ph.D. student in the Department of Communication at Yonsei University. She has a research interest in political communication, including the policy-making process, civic engagement, and media effects.

Sonho Kim

Sonho Kim (Ph.D., University of Pennsylvania, 2011) is a senior research fellow at the Korea Press Foundation. His research interests include digital journalism and institutions of the media.