2018
DOI: 10.1016/j.socnet.2018.01.006
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Individuals’ power and their social network accuracy: A situated cognition perspective

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Cited by 41 publications
(44 citation statements)
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“…In recent years, a wide body of literature has growth with the objective to determine the influence that some personality variables (e.g., extroversion and neuroticism) exert on the variability of the network structure and on individual performance in social networks. Lastly, the comparative analysis of behavioral—real—social networks versus the cognitive—perceptual—evaluation of social networks could be a promising field of research for understanding the relational factors impacting the degree of power that individuals achieve in a variety of social contexts [58,59,60].…”
Section: Discussionmentioning
confidence: 99%
“…In recent years, a wide body of literature has growth with the objective to determine the influence that some personality variables (e.g., extroversion and neuroticism) exert on the variability of the network structure and on individual performance in social networks. Lastly, the comparative analysis of behavioral—real—social networks versus the cognitive—perceptual—evaluation of social networks could be a promising field of research for understanding the relational factors impacting the degree of power that individuals achieve in a variety of social contexts [58,59,60].…”
Section: Discussionmentioning
confidence: 99%
“…This research approach focuses on the individual background as a whole, without positioning the individual or organization into a particular variable or hypothesis. In other words, making the individual or organization as a whole as a whole [21]- [23].…”
Section: Methodsmentioning
confidence: 99%
“…Traditional expert finding algorithms assume a positive correlation between the authority level of an expert and the relevance of his/her authored research to the related query (Wang et al, ;Zhu et al, 2014). Because of the development of information technology and online social networks, network analysis has suggested that the social network structure can influence the behaviour of a group (Ellison, Steinfield, & Lampe, 2010;Guo, Shi, & Jin, 2017;Lesser, Naamani-Dery, Kalech, & Elovici, 2017;Marineau, Labianca, Brass, et al, 2018;Mcmillan, Felmlee, & Osgood, 2018;Ott, Light, Clark, & Barnett, 2018;Richey, 2008;Verduyn, Ybarra, Résibois, Jonides, & Kross, 2017). Apparently, traditional expert finding algorithms did not consider the social influence or the importance of the structure of the social network to which experts belonged.…”
Section: Expert Authoritymentioning
confidence: 99%