In a highly digital world, the extensive information technologies (ITs) have shifted social relationships out of localized contexts and have dramatically reconfigured the way individuals create and develop their social networks. As IT and social landscape become inseparable, individuals’ self-conceptions and behavioral patterns have been pervasively challenged, giving way to “new concepts that embrace social-technological intertwinement,” and to derivative implications for people and communities (Carter and Grover, 2015, p. 391). It follows that new constructs and correlations are needed to interpret the dynamics of human behavior and, thus, the patterns of social networks development. In this front, both seminal and recent literature have posited that a milestone in the study of social networks is to explore and understand the interplay between similarity and social ties (Montoya et al., 2008; Mackinnon et al., 2011; Zhao et al., 2012; Zubcsek et al., 2014; Dunbaret al., 2015; Bahns et al., 2016, etc.). The overarching assumption is that similarity plays a very important role as it stands for the linchpin of relationships initiation and formation (Bahns et al., 2016), and at the same time, it is a propelling factor for online social networks development, be they offline or online (Crandall et al., 2008; Lewis and Wimmer, 2010). Given the wide array of definitions and research directions on social network development, hereinafter, we will refer to it pursuant to Collin et al.’s (2011) dimensions, namely, strengthening and building communities over time, strengthening existing relationships, reinforcing sense of belonging and collective identity, developing new relationships, creating convergence of online and offline spaces. These dimensions are in accordance with Scott’s (2000) parameters of social network development, namely: size, intensity (i.e. an indicator of the relationship strength and closeness to a social network), durability (i.e. the activation degree of a social relationship), density (i.e. the level of interconnectedness within a social network) and dispersion (i.e. indicator of the existence of various social groups within a network, e.g. from both online and offline environments). Even though similarity is deemed to play a key role in achieving a better awareness of the interaction and communication patterns defining peers relationships in social networks, few studies have approached it within integrative and interdisciplinary frameworks, as Gehlbach et al. (2016, p. 343) clearly stated: “as compelling and robust as the similarity-relationship research is, important scientific and applied gaps plague our understanding of these associations.” Moreover, the authors underline that their study is the first experimental investigation addressing actual similarities as a means to developing ongoing relationships and, thus, “striving to contribute to the scientific theories linking similarity and relationships” (Gehlbach et al., 2016, p. 343). Likewise, Mackinnon et al. (2011) claimed the same research gap, affirming that “though it is well-documented that people are more likely to be in relationships with similar others, scant research has examined how this general tendency plays out in day-to-day social situations.” In this respect, the authors urge that this phenomenon has “profound implications worthy of further pursuit” (p. 880).

مقاله سال 2017

Since it came to the fore in the late 1980s, information and communication technology (ICT) has drastically changed the organization and functioning of society, bringing us into a new regime that has been called the information society. The Internet in particular has taken over ever more social, economic and technological functions from other systems of communication and collaboration, and this at an absolutely staggering speed. At the same time, it has been opening up a seemingly infinite variety of new forms of interaction. It is being used for applications as diverse as ordering groceries, organizing political protests, financing new ventures, sharing commodities, discussing global problems, keeping in touch with friends, monitoring factories remotely, guiding traffic, publishing documents, keeping stock in warehouses, distributing calculations across thousands of independent computers, “crowdsourcing” tasks to anonymous workers, and remotely following courses.

This explosion in the number of actual and potential developments of the Internet is overwhelming (Heylighen, 2016a). The resulting confusion makes it very difficult to discern stable trends—except for a general growth in Internet use. Forecasting how these myriad competing advances will shape the future information society seems especially daunting. Still, there exists a paradigm that promises to bring some order to this tangle of volatile, uncertain, complex, and ambiguous (VUCA) developments: theGlobal Brain (Bernstein et al., 2012; Goertzel, 2002; Heylighen, 2011; Mayer-Kress and Barczys, 1995; Russell, 1995)].

The Global Brain can be defined as the self-organizing, adaptive network formed by all people on this planet together with the information and communication technologies that connect them into a cohesive system. The idea is that global interactions have made the people on this planet interdependent to such a degree that together they form a single superorganism (Heylighen, 2007; Stock, 1993), i.e. an organism (global society) whose components are organisms themselves (individual people). As the Internet becomes faster, smarter, and more encompassing, it increasingly interconnects people and computers into a single information-processing network, which plays the role of a nervous system for this superorganism (Heylighen, 2011, Heylighen, 2002). The function of a nervous system is to coordinate the different activities taking place inside this organism, thus increasing their efficiency and coherence, while minimizing any friction or conflict. It moreover provides a repository of knowledge, which functions like a world memory (Wells, 1937) or global expert system (Skulimowski, 2013) that would be able to answer any questions. The knowledge function is supported by the emerging Semantic Web, a suite of protocols for representing knowledge in a machine-understandable way (Berners-Lee and Fischetti, 1999; Heylighen, 2016c). The communication with the superorganism’s physical body is supported by the Internet of Things, another emerging technology for the integration of physical objects into the ICT network (Atzori et al., 2010; Rifkin, 2014).