BackgroundIn spite of the scale-free degree distribution that characterizes most protein interaction networks (PINs), it is common to define an ad hoc degree scale that defines “hub” proteins having special topological and functional significance. This raises the concern that some conclusions on the functional significance of proteins based on network properties may not be robust.MethodologyIn this paper we present three objective methods to define hub proteins in PINs: one is a purely topological method and two others are based on gene expression and function. By applying these methods to four distinct PINs, we examine the extent of agreement among these methods and implications of these results on network construction.ConclusionsWe find that the methods agree well for networks that contain a balance between error-free and unbiased interactions, indicating that the hub concept is meaningful for such networks.
Background Worldwide obesity rates have prompted 16 countries to enact policies to reduce children’s exposure to unhealthy food marketing, but few policies address online advertising practices or protect adolescents from being targeted. Given adolescents spend so much time online, it is critical to understand how persuasive Instagram food advertisements (ads) are compared with traditional food ads. To strengthen online food marketing policies, more evidence is needed on whether social media ads are more persuasive than other types of ads in shaping adolescents’ preferences. Objective This study examined whether adolescents could identify food companies’ Instagram posts as ads, and the extent to which Instagram versus traditional food ads shape adolescents’ preferences. Methods In Part 1, participants aged 13-17 years (N=832) viewed 8 pairs of ads and were asked to identify which ads originated from Instagram. One ad in each pair was selected from traditional sources (eg, print; online banner ad), and the other ad was selected from Instagram, but we removed the Instagram frame—which includes the logo, comments, and “likes.” In Part 2, participants were randomized to rate food ads that ostensibly originated from (1) Instagram (ie, we photoshopped the Instagram frame onto ads); or (2) traditional sources. Unbeknownst to participants, half of the ads in their condition originated from Instagram and half originated from traditional sources. Results In Part 1, adolescents performed worse than chance when asked to identify Instagram ads (P<.001). In Part 2, there were no differences on 4 of 5 outcomes in the “labeled ad condition.” In the “unlabeled ad condition,” however, they preferred Instagram ads to traditional ads on 3 of 5 outcomes (ie, trendiness, P=.001; artistic appeal, P=.001; likeability, P=.001). Conclusions Adolescents incorrectly identified traditional ads as Instagram posts, suggesting the artistic appearance of social media ads may not be perceived as marketing. Further, the mere presence of Instagram features caused adolescents to rate food ads more positively than ads without Instagram features.
Background Social media platforms have created a new advertising frontier, yet little is known about the extent to which this interactive form of advertising shapes adolescents’ online relationships with unhealthy food brands. Objective We aimed to understand the extent to which adolescents’ preferences for Instagram food ads are shaped by the presence of comments and varying numbers of “likes.” We hypothesized that adolescents would show the highest preferences for ads with more “likes” and comments. We predicted that these differences would be greater among adolescents who were “heavy social media users” (ie, >3 hours daily) vs “light social media users” (ie, <3 hours daily). Methods We recruited Black and non-Latinx White adolescents (aged 13-17 years; N=832) from Dynata, a firm that maintains online participant panels. Participants completed an online survey in which they were randomized to view and rate Instagram food ads that either did or did not show comments. Within each condition, adolescents were randomized to view 4 images that had high (>10,000), medium (1000-10,000), or low (<100) numbers of “likes.” Adolescents reported ad preferences and willingness to engage with the brand. Results Adolescents rated ads with medium or high numbers of “likes” higher than ads with few “likes” (P=.001 and P=.002, respectively). Heavy social media users (>3 hours/day) were 6.366 times more willing to comment on ads compared to light users (P<.001). Conclusions Adolescents interact with brands in ways that mimic interactions with friends on social media, which is concerning when brands promote unhealthy products. Adolescents also preferred ads with many “likes,” demonstrating the power of social norms in shaping behavior. As proposed in 2019, the Children’s Online Privacy and Protection Act should expand online advertising restrictions to include adolescents aged 12 to 16 years.
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