Online social networks play an increasingly important role in communication between friends, colleagues, business partners, and family members. This development sparked public and scholarly debate about how these new platforms affect dynamics of cultural diversity. Formal models of cultural dissemination are powerful tools to study dynamics of cultural diversity but they are based on assumptions that represent traditional dyadic, face-to-face communication, rather than communication in online social networks. Unlike in models of face-to-face communication, where actors update their cultural traits after being influenced by one of their network contacts, communication in online social networks is often characterized by a one-to-many structure, in that users emit messages directly to a large number of network contacts. Using analytical tools and agent-based simulation, we show that this seemingly subtle difference can have profound implications for emergent dynamics of cultural dissemination. In particular, we show that within the framework of our model online communication fosters cultural diversity to a larger degree than offline communication and it increases chances that individuals and subgroups become culturally isolated from their network contacts.

Changes in dietary macronutrient composition and/or central nervous system neuronal activity can underlie obesity and disturbed fuel homeostasis. We examined whether switching rats from a diet with high carbohydrate content (HC; i.e., regular chow) to diets with either high fat (HF) or high fat/high protein content at the expense of carbohydrates (LC-HF-HP) causes differential effects on body weight and glucose homeostasis that depend on the integrity of brain melanocortin (MC) signaling. In vehicle-treated rats, switching from HC to either HF or LC-HF-HP feeding caused similar reductions in food intake without alterations in body weight. A reduced caloric intake (-16% in HF and LC-HF-HP groups) required to maintain or increase body weight underlay these effects. Chronic third cerebroventricular infusion of the MC receptor antagonist SHU9119 (0.5 nmol/day) produced obesity and hyperphagia with an increased food efficiency again observed during HF (+19%) and LC-HF-HP (+33%) feeding. In this case, however, HF feeding exaggerated SHU9119-induced hyperphagia and weight gain relative to HC and LC-HF-HP feeding. Relative to vehicle-treated controls, SHU9119 treatment increased plasma insulin (2.8-4 fold), leptin (7.7-15 fold), and adiponectin levels (2.4-3.7 fold), but diet effects were only observed on plasma adiponectin (HC and LC-HF-HP

There is public and scholarly debate about the effects of personalized recommender systems implemented in online social networks, online markets, and search engines. Some have warned that personalization algorithms reduce the diversity of information diets which confirms users’ previously held attitudes and beliefs. This, in turn, fosters the emergence opinion polarization. Critics of this personalization-polarization hypothesis argue that the effects of personalization on information diets are too weak to have meaningful effects. Here, we show that contributions to both sides of the debate fail to consider the complexity that arises when large numbers of interdependent individuals interact and exert influence on one another in algorithmically governed communication systems. Summarizing insights derived from formal models of social networks, we demonstrate that opinion dynamics can be critically influenced by mechanisms active on three levels of analysis: the individual, local, and global level. We show that theoretical and empirical research on these three levels is needed before one can determine whether personalization actually fosters polarization or not. We describe how the complexity approach can be used to anticipate and prevent undesired effects of communication technology on public debate and democratic decision-making.

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