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How long will this article be remembered? How long will people reference it in their conversations, and for how many years will other authors cite its findings in their own works? A community’s attention to a cultural object decays as time passes, a process known as collective forgetting. Recent work models this decay as the result of two different processes. One linked to communicative memory—memories sustained by human communication—and the other linked to cultural memory—memories sustained by the physical recording of content. Collective forgetting has significant impacts on communities, yet little is known about how the collective forgetting dynamic changes over time. Here, we study the temporal changes of collective memory and attention by focusing on two knowledge communities: inventors and physicists. We use data on patents from the United States Patent and Trademark Office (USPTO) and physics papers published by the American Physical Society (APS) to quantify those changes over time. The model enables us to distinguish between two branches of forgetting. One branch is short-lived, going directly from communicative memory to oblivion. The other branch is long-lived, going from communicative memory to cultural memory before going on to oblivion. The data analysis shows an increase in the forgetting rate for both communities as the amount of information in each of them grows. That growth of information forces knowledge communities to increase their selectivity regarding what is stored in their cultural memory. These findings confirm the forgetting as annulment hypothesis and show that knowledge communities can slow down collective forgetting and improve selectivity processes.

Online social-media platforms are a vital arena in which socio-political perspectives are put forth, debated, and spread. Prior work suggests that certain moral-emotional language drives online contagion, but theoretical and empirical findings remain debated, inhibiting constructive interventions. We substantially advance this ongoing debate using a diverse range of topics and both mainstream and extremist social media platforms. We find two countervailing dynamics predict the rise and fall of posting engagement online. First, we confirm that content infused with a greater number of moral words is associated with increased engagement; still, contrasting with prior work, we find no evidence that it is driven specifically by moral-emotional words as opposed to the more general and larger lexicon of moral language. Second, we identify a striking reversal in the relationship between moral language and engagement, a phenomenon we call “moral penalty.” We find that as the ratio of moral to non-moral words surpasses a threshold, the process of engagement around a post reverses with marked decreases in engagement and online diffusion. These findings help clarify links between morality and online engagement and contagion: infusing messages with moral language increases their spread to a point after which embedding posts in morality may backfire.

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Is it possible to derive organizing principles of higher education systems from the applicants' choices? Here, we introduce the Higher Education Space (HES) as a way to describe the complex relationship between degree programs. The HES is based on the application of methods from network science to data on the revealed preferences of applicants to the higher education systems of Chile and Portugal. Our work reveals: 1) the existence of a positive assortment of featuressuch as gender balance, application scores, unemployment levels, demand-supply ratio, etc -along the network structure of the HES; 2) that the decaying of the prevalence level of a feature from a focal degree program extends beyond the dyadic relationships captured by the HES; 3) temporal variations in different features do not spillover/propagate throughout the system in the same way; 4) differences in unemployment levels reported among pairs of degree programs are minimized when taking into consideration the connectivity structure of the HES, largely outperforming the differences in matched pairs using traditional similarity measures; and 5) grouping of degree programs based in the network structure of the HES provides an applicant perspective that complements existing classification systems. Our findings support the HES as a multi-dimensional framework that can effectively contribute to the governance of higher education systems. Chilenas 6 The first option is often considered to reveal the true preference of an applicant.

In this study we explored the extent to which problems and instructional strategies affect social cohesion and interactions for information seeking in physics classrooms. Three sections of a mechanics physics course taught at a Chilean University in Coquimbo were investigated. Each section had a weekly problem-solving session using different sets of well and/or ill-structured problems (i.e., algebra-based and open-ended problems respectively), as well as instructional strategies for guiding the problem solving sessions. Data was collected on networks of information seeking and perceptions of good physics students, during a problem solving session. We used social network analysis (SNA) for constructing variables while conducting the study. Results suggest that the teaching and learning strategies to guide problem solving of well and ill-structured problems yield different levels of social interaction among classmates, and significant levels of activity in seeking out information for learning and problem-solving. While strategies for guiding problem solving lend to significant differences for network connectivity, well and ill-structured physics problems predict similar levels of social activity.