Abstract

THE impact of online social networks on our lives is growing; their ubiquitous presence grants connectivity and access to near-unlimited information to over one billion individuals all over the world. The availability of massive data about individuals' behavior, activity, and interactions on large platforms such as Facebook and Twitter has opened a new research paradigm, which now falls under the umbrella of computational social science (Lazer, et al., 2009; Borgatti, Mehra, Brass, & Labianca, 2009).
Major questions related to complex human phenomena have been tackled, such as the untangling of large-scale human interactions (Liben-Nowell, Novak, Kumar, Raghavan, & Tomkins, 2005; Ferrara, 2012; De Meo, Ferrara, Fiumara, & Provetti, 2014) and mobility patterns (Gonzalez, Hidalgo, & Barabasi, 2008), the effects of the intro-duction of new norms and behaviors (Centola, 2010, 2011), the" contagion" of ideas or emotions (Golder & Macy, 2011; Kramer, Guillory, & Hancock, 2014; Ferrara & Yang, 2015a), people coordinating to protest about social issues (González-Bailón, Borge-Holthoefer, Rivero, & Moreno, 2011; Conover, Ferrara, Menczer, & Flammini, 2013), the effects of social influence (Aral & Walker, 2012; Bond, et al., 2012), and the spread of diseases and epidemics (Chew & Eysenbach, 2010). Many studies have exploited data to predict the behavior of these sociotechnical systems (Vespignani, 2009, 2012; Cho, 2009; Szabo & Huberman, 2010; Dhar, 2013; Fan & Gordon, 2014), yet some have called for caution when using human digital trails and big data. A number of studies have incurred fallacies such as" big data hubris," the …

Date

August 12, 2019

Authors

Emilio Ferrara

Book

The Oxford Handbook of Networked Communication

Pages

378-397

Publisher

Oxford University Press