Influentials, Networks, and Public Opinion Formation

By Duncan J. Watts, Peter Sheridan Dodds. 2007

1,958 citations recorded by the source corpus.

Subfields: Management Science and Operations Research, Statistical and Nonlinear Physics

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In Management Science and Operations Research

In Statistical and Nonlinear Physics

Citations in the corpus

Inferring networks of diffusion and influence (2010, background): “Cascading behavior, diffusion and spreading of ideas, inno vation, information, influence, viruses and diseases are fund amental processes taking place in networks [12, 28, 30].”
Language Abstraction in Word of Mouth (2010, background): “…to spread product and service information, and word of mouth has received continuous attention from scientists since the seminal work of Katz and Lazarsfeld’s (1955) over five decades ago (Arndt, 1967; Brown & Reingen, 1987; Chevalier & Mayzlin, 2006; Frenzen & Nakamoto, 1993; Watts & Dodds, 2007).”
Heterogeneity, Correlations and Financial Contagion (2011, background): “Such behavior for threshold models has already been observed within the context of public opinion formation in [19], where it was shown that cascades of influence are not driven by a few very influential nodes, but by a critical mass of influenced individuals.”
Creating Social Contagion through Viral Product Design: A Randomized Trial of Peer Influence in Networks (2011, positive): “Louis 2010 studies suggest that cascades of influence are instead driven by “a critical mass of easily influenced individuals” (Watts and Dodds 2007).”
Network Effects and Personal Influences: The Diffusion of an Online Social Network (2011, positive): “Studying the aggregate impact of influencers on diffusion, Watts and Dodds (2007) ran a series of computer simulations.”
Business Intelligence in Blogs: Understanding Consumer Interactions and Communities (2012, methodology): “To verify the role of central bloggers in disseminating information, we performed a simple study to simulate the word-of-mouth process in the blogosphere following a widely cited information cascading model in marketing (Watts and Dodds 2007).”
Learning influence probabilities in social networks (2010, background): “Indeed, Watts [ 22 , 20, 21] challenges the very notion of influential users that are often assumed in viral marketing papers.”
Determinants of consumer engagement in electronic word-of-mouth (eWOM) in social networking sites (2011, background): “Given the collaborative and social characteristics of SNSs, this study focuses on SNSs as an emerging venue for consumer-toconsumer conversations, namely brand-related word-of-mouth (WOM).”
Marketing in Computer-Mediated Environments: Research Synthesis and New Directions (2014, neutral): “The multifaceted, often unanticipated ways in which public opinion can shift in the marketplace—for example, even when opinion leaders are not actively involved (see Watts and Dodds 2007)—underscore the need for continued vigilance and monitoring of UGC.”
Tipping elements and climate–economic shocks: Pathways toward integrated assessment (2016, background): “These underlying factors are social phenomena that can experience positive feedbacks related to network influencer effects [Watts and Dodds, 2007].”
Digital marketing: A framework, review and research agenda (2017, positive): “In their seminal paper, Watts and Dodds (2007) proposed a hypothesis that there is a small group of influencers, the impact from whom can cascade to others.”