Most individuals have few close friends, leading to potential isolation after a friend's death. Do social networks heal to fill the space left by the loss? We conduct such a study of self-healing and resilience in social networks. We compared de-identified, aggregate counts of monthly interactions in approximately 15,000 Facebook networks in which someone had died with similar friendship networks of living Facebook users.
Despite the shift from multilateral negotiations on legally binding mitigation commitments to the decentralized nonbinding Intended Nationally Determined Contributions (INDCs) approach in global climate policy, governments and other stakeholders continue to insist that fairness principles guide the overall effort. Key recurring principles in this debate are capacity and historical responsibility.
Social life continues to increasingly occur in digital environments and to be mediated by digital systems. Big data represents the data being generated by the digitization of social life which we break down into three domains: digital life, digitalized life, and digitized traces. We argue that there is enormous potential in using big data to study a variety of phenomena that remain difficult to observe.
The bitterly factious 2016 U.S. presidential election campaign was the culmination of several trends that, taken together, constitute a syndrome of chronic ailments in the body politic. Ironically, these destructive trends have accelerated just as science has rapidly improved our understanding of them and their underlying causes. But mere understanding is not sufficient to repair our politics.
When people share updates with their friends on Facebook they have varying expectations for the feedback they will receive. In this study, we quantitatively examine the factors contributing to feedback expectations and the potential outcomes of expectation fulfillment.
Feedback expectations; Computer-mediated communication; Social Media; Facebook; Information Sharing
This study reports the results of a multiyear program to predict direct executive elections in a variety of countries from globally pooled data. We developed prediction models by means of an election data set covering 86 countries and more than 500 elections, and a separate data set with extensive polling data from 146 election rounds. We also participated in two live forecasting experiments.
This project explores whether a real time sentiment index, constructed using the universe of Reuters news, can help in forecasting GDP and predicting extreme events, such as large reversal in capital flows, in emerging markets.