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Other theories may provide complementary insight into diffusion dynamics of dismisinformation. The multilevel model of meme diffusion (M³D) proposes that in information-dense ecosystems, any given message or message stream competes in an attention economy at both individual and collective levels (Magarey & Trexler, 2020; Ryan et al., 2020; Spitzberg, 2014, in press ; Stano, 2020; Zollo, 2019). In essence, humans are limited information processors facing an information ecology containing an almost infinite amount of information. In contrast to human selection, which by its nature is miserly, media contents, like nature, are profligate. Evidence suggests that people’s attention spans are decreasing as their media consumption continues to use more minutes per day of almost everyone’s quotidian activities (Spitzberg, 2019; Twenge, Martin et al., 2019; Twenge, Spitzberg et al., 2019). As Simon (1971) proposed axiomatically:

In an information-rich world, the wealth of information means a dearth of something else: A scarcity of whatever it is that information consumes. What information consumes is rather obvious: It consumes the attention of its recipients. Hence a wealth of information creates a poverty of attention and a need to allocate that attention efficiently among the overabundance of information sources that might consume it.

(pp. 40–41)

In such contexts, bright and shiny memes that become viral tend to attract attention and divert attention away from other potentially more important or legitimate sources of information. Indeed, a distinguishing feature of fake news as a rhetorical trope is their imitation and capture “of the time-sensitive media cycle—a daily routine of mass media consumption” (Avramov et al., 2020, p. 517), suggesting there may be prototypical lifecycles to conspiracy theories and fake news (Leal, 2020). Such attention gravity becomes a rather direct threat in pandemic contexts, as herd immunity requires high levels of compliance with health protocols just at the time that people may be most vulnerable to messages promoting noncompliance. Even at liberal estimates of herd immunity for SARS-CoV-2 at 43% of the population (Britton et al., 2020), if over half of the population is commonly exposed to or consumes fake news and/or conspiracy theory messages about the virus (e.g., Freeman et al., 2020a, 2020b; cf. McManus et al., 2020), it can threaten the achievement of such crucial health thresholds. To the extent that “belief in conspiracy theories is demographically mainstream” (Butter & Knight, 2016, p. 6), herd immunity will remain tenuous in its attainability. Ironically, even though conspiracies are likely to fail due to the inability of a critical mass of conspirators to keep such a secret (Grimes, 2016), the critical mass of those who believe such theories tends to make the theories more powerful than their plausibility would imply.

The very format of much of social media can create inattention to specific but relevant content and source information (Baptista & Gradim, 2020; Pearson, 2020). An analysis of a 10% sample of all global tweets demonstrates the emergence of the word “virus” in tweets in the top 100 ranks across languages during the COVID-19 pandemic, illustrating the competition for attention (Alshaabi et al., 2020). Just as importantly, however, this study also found that “attention across all but 2 of the 24 languages … dropped through February before resurging in late February and through March” (p. 9), suggesting important time periods in which mass prevention efforts might drop from public focus, which could in turn have significant implications for the resurgence of the disease, recognizable as “abrupt shocks in time series as populations shifted rapidly to heightened levels of awareness” (p. 9). There is also likely to be variegation in the attention paid to certain narratives compared to others. Research on a large sample (2.25 million comments from approximately 130,000 distinct authors) of conspiracy-related posts on Reddit used topic-modeling (Klein et al., 2018). Consistent with other research (Bessi et al., 2015), Klein et al. identified three patterns across a heterogenous set of topics: (i) Some true believers care more about historical events, whereas the other true believers tend to explore more conjectural conspiracies; (ii) some conspiracists focus on only one theory; and (iii) many of those who engage conspiracy theory (arguing for or against) tend to focus on pseudo-scientific topics (e.g., vaccines, chemtrails, etc.). This is important because it suggests that some factions of conspiracy theory and fake news may be more easily targeted by message campaigns and may vary in their attention span for such targeting.

Despite extensive recent interest in theorizing the role of conspiracy theory and fake news in society, it seems clear that “a unified or more cohesive theory” is needed (Weiss et al., 2020, p. 25). There certainly is no single or unified theory at present that is adequate to the need (Huneman & Vorms, 2018), and it seems likely that disciplinary approaches including neurobiology, memetics and communication, psychology, sociology, and big data analytics will serve complementary approaches to understanding the phenomenon (Andrade, 2020, p. 3).