Social Networks Under Stress

Abstract

Social network research has begun to take advantage of finegrained communications regarding coordination, decisionmaking, and knowledge sharing. These studies, however, have not generally analyzed how external events are associated with a social network's structure and communicative properties. Here, we study how external events are associated with a network's change in structure and communications. Analyzing a complete dataset of millions of instant messages among the decision-makers in a large hedge fund and their network of outside contacts, we investigate the link between price shocks, network structure, and change in the affect and cognition of decision-makers embedded in the network. When price shocks occur the communication network tends not to display structural changes associated with adaptiveness. Rather, the network "turtles up". It displays a propensity for higher clustering, strong tie interaction, and an intensification of insider vs. outsider communication. Further, we find changes in network structure predict shifts in cognitive and affective processes, execution of new transactions, and local optimality of transactions better than prices, revealing the important predictive relationship between network structure and collective behavior within a social network.

Social Networks and Loneliness During the COVID-19 Pandemic

“…Moreover, very little research in the social sciences has examined changes in networks in response to large-scale exogenous shocks (Romero, Uzzi, and Kleinberg 2016). While research has found an increase in network cohesion and network shrinkage in response to natural disasters (Forgette et al 2009;Phan and Airoldi 2015), as well as a tendency to "turtle up" or an intensification of strong-tie interactions and clustering following price shocks (Romero et al 2016), further research is needed to understand how networks have changed during COVID-19. We utilize longitudinal social network data collected pre-COVID (June 2019) and compare them with data collected in June of 2020 to examine changes in social networks following a period of intense social isolation.…”

Conspiracy vs science: A large-scale analysis of online discussion cascades

“…Text mining provides technical support for further investigation of contents beyond merely structural or temporal properties of cascades. A number of studies have adopted the word-emotion association lexicon to make automatic evaluation of sentiments and emotions embedded in texts [8,11,41,48]. In addition, topic modeling is another widely used method to quantify the underlying topic concerns that characterize a set of documents [6,21,35,45,48,50].…”

The Effect of Collective Attention on Controversial Debates on Social Media

“…Moreover, we are particularly interested in the network response to external stimuli that lead to increased collective attention in the controversial topic -an issue that only very recently has seen some attention in the literature (Romero, Uzzi, and Kleinberg 2016). 3 Dataset…”