Regularity and Variability: Growth Patterns of Online Friendships

Regularity and Variability: Growth Patterns of Online Friendships

Lun Zhang (Department of Journalism and Communication, University of Chinese Academy of Sciences, Beijing, China) and Jonathan J. H. Zhu (Department of Media and Communication, City University of Hong Kong, Kowloon, Hong Kong)
Copyright: © 2014 |Pages: 13
DOI: 10.4018/IJWSR.2014100102

Abstract

Social network sites (SNSs) have brought revolutionary changes to individuals' social interactions. The growth of online personal relationships is crucial for understanding current interpersonal communications and network dynamics. In the context of a Chinese SNS, this study provides an empirical presentation of the growth patterns of individuals' online friendships. This study uncovers the regularity as well as the variability of such growth patterns. On the one hand, the friendship growth patterns show regularity in that the time trajectory of friendship growth for most users levels off at some point of their friendship formation. On the other hand, the growth patterns of online friendships also demonstrate variability. There are three essentially different growth patterns emerged: the logistic pattern (i.e., S-shape), the double-logistic pattern (i.e., double-S shape), and the power pattern (i.e., rotated-L shape). By employing multinomial logistic regression, this study further found that network connectedness lead to the differences in these growth patterns of online friendships. However, a user's personal strategy of online friendship formation is found to have a nil effect on explaining the differences in growth patterns of online friendships. This paper concludes by discussing the theoretical and practical implications of the growth patterns of online relationships.
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Introduction

Social network sites (SNSs) have brought revolutionary changes to individuals’ social lives by permeating numerous aspects of social interaction, such as information transmissions, resource exchanges, and sentimental attachments (Butler, 2001; Caplan, 2003). Thanks to the synchronicity and unboundedness of space in communications, SNSs have loosened the constraints of time and space for offline social interactions. Individuals’ social ties in the offline world can be maintained via SNSs by moving their offline social relationships to this new platform (Ellison, Steinfield, & Lampe, 2007). Moreover, SNSs have liberated users to establish new connections that are outside their pre-existing social groups. Different from the formation of traditional offline social relationships, these new types of connections can be established based on individuals’ common interests rather than their shared geographical location or institutional affiliation that are critical to offline tie formations (Di Gennaro & Dutton, 2007). These revolutionary changes of accumulation of social relationships online have contributed to the process of socialization and allocation of social resources (Campbell, Marsden, & Hurlbert, 1986; Hartup, 1989). In this regard, the growth of online relationships is now crucial for understanding interpersonal communications.

A review of the literature reveals that very little is yet known about the growth patterns of personal online social relationships. Previous research has paid little attention to the growth patterns of personal social relationships for individuals. Instead, previous studies tend to over-emphasize the aggregated pattern of friendship growth as a whole network. For example, several studies describe the evolution of a network size and other topological characteristics of SNSs (e.g., degree distribution, clustering coefficient, and density of the network) (Ahn, Han, Kwak, Moon, & Jeong, 2007; Kumar, Novak, & Tomkins, 2010). Some studies focus on the growth of online social networks in terms of the extent that they are contributed by the shared similarities of individuals’ attributes, the network distance between members, and the process of personal preferential attachment (i.e., people tend to link to well-connected nodes) (Kossinets & Watts, 2006; Mislove, Koppula, Gummadi, Druschel, & Bhattacharjee, 2008). Although these studies have drawn an overall picture of the growth of online relationships, they have not furthered the understanding of the growth patterns of social relationships at the individual level; that is, can any regularity and/or variability of online friendship growth be found for individuals?

With the success of SNSs, the availability of online friendship formation data with time stamps, coupled with advanced methods that have been proposed in recent years to deal with data at scale, provides possibilities to examine the growth of social relationships in a more rigorous way than has been possible before. In describing the friendship growth of individuals, many of the challenges derive from the difficulty in accessing appropriate datasets. A dataset may contain a complete collection of online social ties with time stamps so that researchers can track the growth of the social relationships for each individual from the very beginning when that individual joins the network. Previous studies have drawn samples at two or more time points (Van Tilburg, 1998; Wang & Wellman, 2010). However, snapshot data with very few time points within each individual have been proven to be inappropriate for revealing the intricacies of changing patterns of social relationships.

The first goal of this study is to identify, describe, and categorize the growth patterns of personal friendships for each individual . Based on the findings of this first objective, this study will further examine the factors that contribute to the differences in the growth patterns of online friendships.

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