The Jesus Movement and social network analysis: - part II. The social network

The intent of this study is to imaginatively shed light on Gerd Theissen's view of the early Jesus Movement with the help of social network analysis. Part I, after a brief introduction to network analysis, discussed Graph Theory, Central Place Theory, Urbanology, and settlement archeology as aids to understand the importance of the Galilean towns Jesus is said to have visited, especially those around the Sea of Galilee. It included some information about lake harbors, Roman roads, and Dead Sea towns (the Babatha archive). It also attempted to see Capernaum as a minor Central Place from which Jesus could travel, both by land and by sea. Part II resumes with a more detailed discussion of social network concepts and then analyzes the Jesus Movement discussed by Theissen as an "Ego-centered network." It offers as an illustration Jesus' natural kinship network, and concludes with reflections about several important critical issues in current Jesus study. (Many works cited in Part II are in "Works Cited," Part I, BTB 29/4 [1999: 171-75]).

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As stated in Part I, J. A. Barnes was the first to transform the network metaphor into way of analyzing social relations (Barnes 1954; 1969a; 1969b; 1972). Drawing on Barnes, other network social analysts have developed network concepts (e.g., Befu 1962; Pospisil 1964; Scrininas & Betaille 1964; Bott 1975; Mitchell 1969; 1973; 1974; Boissevain 1968; 1973; 1974; 1979; 1985; Kapferer 1972; 1973; Marsden 1972; Whitten & Wolfe 1973; Snow, Zurcher, & Ekland-Olson 1980; Wilier & Anderson 1981; Marsden & Lin 1982; Granovetter 1982; Berkovitz 1982; 1984; Burt & Minor 1983; Noble 1983; Wellman 1983; 1988; Wellman & Berkowitz 1988; Wellman, Carrington, & Hall 1988; Yamagishi, Gillmore, & Cook 1988; Walker, Wassereman, & Wellman 1994; Waserman & Faust 1994; Wellman & Berkowitz 1994; Noyes 1995; see the Websites in "Works Cited [Selected]"). These social relationships are key to understanding the social dynamics of the early Jesus movement.

Two Foundational Concepts: "Activity Fields" and Limiting the Analysis

"Activity Fields"

Activity fields are contexts in which persons who share something in common relate to each other; such contexts include family, neighborhood, gender, age, education, work, and friendship (Jay 1964), as well as "categorical orders" such as race, ethnicity, and status (Mitchell 1973: 20).

Limiting the Analysis

In theory it is possible to analyze every possible person (an "infinite network") and every possible social link between them (a "total network"), and thus to construct an unlimited, all-inclusive, universal network (an "unbounded network") (Barnes 1969; Boissevain 1968; 1974; 1985; Mitchell 1969; 1973; Whitten & Wolfe 1973). In practice, network analysts limit the number of persons (a "finite network") and their links (a "partial network"), and thus construct a limited network (a "bounded network," though even bounded networks are usually somewhat pourous; see Scrinivas & Beteille 1964: 165-66). Barnes defined a partial network as "any abstract of the total network based on some criterion applicable through the whole network" (1969:57).

Two Types of "Criteria of Analysis": Structural and Interactional

There are two types of criteria of analysis, "structural" and "interactional." Some analysts, especially anti-Structural Functionalists, argue that the analyst should begin with interactional criteria (Boissevain 1974: 27-28; Noyes 1995: 458); for clarity, I begin with structural criteria.

Four Structural Criteria

Structural criteria of analysis refer to the form a network takes. This form is configured by "the extent to which people who all know one person also happen to know one another" (Mitchell 1974: 288). There are four variables.

Size. Size is the most important structural criterion, though it is not calculated mathematically. Generalization: larger networks provide possibilities for more interactions, but they also have potential for more interpersonal conflict.

Density ("Connectivity"). Density refers to "the ratio of actual existing links to the total number of possible links" (Mitchell 1974: 288). Density is either "high" ("close-knit") or "low" ("loose-knit"). Using NA as the total number of links in the network and N as the total number of persons, here is a mathematical formula for density:

100 NA/1/2 N(N-1)

Figure 1 shows a six-node network with "symmetrical" links (equal exchange between persons of equal status).

[FIGURE 1 OMITTED]

Generalization: high density allows for greater communication and usually involves relationships between persons based on more than one activity field (represented by more than one line; see "multiplexity" below; Noyes 1995: 458). High density also fosters increased social conformity, thus development of norms and attitudes (Boissevain 1985: 557b). Yet, it tends to aid in the ability to recruit persons and mobilize support (Stark 1996), a point also made in "social movement theory" (Morris & Mueller 1992).