Conceptualizing Deviance by Bright Candace Forbes;

Author:Bright, Candace Forbes;
Language: eng
Format: epub
Tags: undefined
Publisher: Lexington Books/Fortress Academic
Published: 2012-08-15T00:00:00+00:00

Chapter 6

Approach Three

Birds of a Feather Approve of Deviant Behavior Together

What roles do social networks play in approval of deviant behavior? While studies have been undertaken to test attitude transference processes (c.f., Krohn et al. 1982, 1988; Mears 1998; Warr and Stafford 1991; Haynie and Osgood 2005; Hochstetler et al. 2002; Hwang and Akers 2006), these studies have neither taken advantage of the statistical tools provided by social network analysis (SNA), nor social media outlets as sources of data. SNA is an innovative approach to understanding the social norms that underlie the labeling of deviance. The majority of studies that claim to utilize social network analysis merely measure association: frequency of association, duration of relationship, priority of relationships, and intensity of variable of interest in relationships (Liska 1987). Short (1957), for instance, is considered a break-through study of the effects of association on deviant behavior using these variables. According to Short’s correlation statistics, exposure to a variable increases one’s acceptance of that variable. This, however, is not SNA until SNA methods are applied to the data (Hawe, Webster, and Shiell 2004). Following deviant socialization theories, this research applies SNA to attitude transference within networks.

This research hypothesizes that the collectivist leaning of the South Korean population will yield greater social influence in the attitude transference of South Korean respondents. Collectivist countries, as is South Korea, show higher levels of conformity than individualist countries, which implies that networks in collectivist countries will exert greater social influence (Bond and Smith 1996).

This research tests for network density,[1] homophily of attributes, social correlation[2] of tolerance levels, and approval thresholds. The purpose of testing for density is that more variation is expected in the networks of individuals who have a low density. More variation is then expected to mean less correlation between tolerance levels of the ego and alters.[3] Finally, social correlation of tolerance levels is analyzed to develop a measure of social thresholds—how many individuals in a group have to approve of a behavior before the ego also approves of the behavior?

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