The serial‐order effect wherein originality increases over time is one of the most robust findings in modern psychology. This effect, found in either individual or group sessions, is based on associative and spreading activation mechanisms: Mental association takes place in temporal sequential order from commonly (closely) to unusually (distantly) related semantic concepts stored in long‐term memory. Thus, data from previous studies might suggest that, in collective problem‐solving, we endure long meetings and pay closer attention to ideas presented toward the end of the meeting. However, members in innovative organizations have been reported to typically generate ideas on their own before group brainstorming. We hypothesized that in the subsequent group brainstorming session members would state their most appealing ideas first due to impression management. Our results from the individual‐then‐group hybrid brainstorming paradigm show that idea quality during the group session peaks early and then decays, in terms of both the number of high‐quality ideas produced and the proportion of ideas that are high‐quality. This “reverse” serial‐order effect implies that meeting for a reasonably brief time and looking into ideas shared early during the meeting may lead to better decisions—if individuals generated ideas prior to the meeting. We also found that flexibility (the rate at which new idea categories were introduced) dropped rapidly, but at a certain point of time, it stopped decreasing. This potentially suggests that extended group interaction after individual idea generation could bring greater idea diversity rather than higher overall quality. In addition, we found that the updated, cognitively constrained organizational norm for brainstorming, which likely narrows the scope of search, led to greater idea quantity (fluency), quality, and flexibility than the traditional, unconstrained norm. Our work challenges the traditional application of spreading activation theory to interpersonal, group, or organizational settings and calls for attention to the specific communicative processes of problem‐solving and decision‐making in question.

With the rise of digital media, conspiracy theories infamous for their emotional manipulation have challenged science epistemology and democratic discourse. Despite extensive literature on misinformation and the role of emotion in persuasion, less is understood about how emotion is used in conspiracy and debunking messages on video platforms and the impact of emotional framing on public engagement with science on social media. Our article fills this gap by analyzing thousands of YouTube videos that propagate or debunk COVID-19 conspiracy theories from March to May 2020. We found that conspiracy and debunking videos used the emotions of trust and fear differently depending on the issue framing of the conspiracy. Our article also reveals a dilemma facing debunking messages—when debunking videos used more trust-related emotions, these videos received more likes yet fewer views. These findings shed new light on the role of emotion on user engagement with misinformation and its correction on digital platforms.

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Ongoing research into how states coordinate foreign disinformation campaign has raised concerns over social media’s influence on democracies. One example is the spread of Russian disinformation in the 2016 U.S. presidential election. Russia’s Internet Research Agency (IRA) Twitter accounts have been known to deliver messages with strategic attempts and political goals. We use publicly-available IRA Twitter data created during and after the 2016 US election campaign (2016 and 2017) to examine the nature of strategic message features of foreign-sponsored online disinformation and their social media sharing. We use computational approaches to identify unique syntactic features of online disinformation tweets from IRA compared to American Twitter corpora, reflecting their functional and situational differences. More important, we examine what message features in IRA tweets across syntax, topic, and sentiment were associated with more sharing (retweets). Implications are discussed.