Anti-rumor dynamics is proposed on the basis of rumor dynamics and the characteristics of anti-rumor dynamics are explored by both mean-field equations and numerical simulations on complex network. The main metrics we study are the timing effect of combating rumor and the identification of influential nodes, which are what an efficient strategy against rumor may concern about. The results indicate that, there exists robust time dependence of anti-rumor dynamics and the timing threshold emerges as a consequence of launching the anti-rumor at different delay time after the beginning of rumor spreading. The timing threshold as a critical feature is further verified on a series of Barabási-Albert scale-free networks (BA networks), where anti-rumor dynamics arises explicitly. The timing threshold is a network-dependent quantity and its value decreases as the average degree of the BA network increases until close to zero. Meanwhile, coreness also constitutes a better topological descriptor to identify hubs. Our results will hopefully be useful for the understanding of spreading behaviors of rumor and anti-rumor and suggest a possible avenue for further study of interplays of multiple pieces of information on complex network.
This study examined how the presence of substance cues interacted with arousing content level in public service announcements (PSAs) to affect human motivational activation, and as a result, affect cognitive information processing. A 2 (arousing content level: high vs. low arousing content fear appeal PSAs) × 2 (substance cue: absence vs. presence) × 4 (repetition) within-subject factorial design experiment was conducted. Overall, the results indicated that the presence of substance cues in high arousing content fear appeal messages elicited defensive processing, yielding poor audio recognition memory sensitivity and a more conservative criterion bias. However, the addition of substance cues to low arousing content fear appeal messages increased audio recognition sensitivity. The presence of substance cues decreased visual recognition regardless of the arousing content level. Implications and future research are discussed.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.