Description
Format: Approximately 6-8 pages, Times New Roman, 12-pt font, 1-inch margins (all sides), double-spaced! Citations and works cited page should be in ASA format (ASA Quick Style guide.pdf / ASA_Style_Citations_4.pdf / citation guide.pdf
n external site.)–Works Cited is most important if you cite something outside of the syllabus readings. The 6-8 pages only includes the main text of the paper (in other words, the page count does not include works cited or any pictures/tables you decide to use).
You may cite lectures parenthetically as well. For example: (Lin, Title of Lecture, Date of lecture). In the works cited page, you may cite this as the following: Lin, Edwin. “Title or subject of lecture” (Course Name, College Name, Location, Date).
Preparation to Write the Paper: Spend 5 weeks+ (approximately 5 hours a week) engaging and initiating with a virtual community. Your goal is to immerse yourself as much as possible in a virtual community (either one that you already have some experience with or a new one) to investigate what being a part of such a community is like. This is like doing ethnography and participant observation in a virtual space. Take notes about people’s reactions to you and the social interactions that occur in such a community. Reflect on your own experiences, feelings, and interactions.
You may create social experiments (without harming anyone) or observe other people’s interaction in the virtual community. You may even conduct interviews (virtually) with people that you meet. And look for connections from your experience to the readings, lectures, and themes from the course.
NOTE: Please follow basic ethical guidelines when conducting research, especially if you decide to do some social experiments or conduct interviews. If you have any questions, please ask me.
Assignment:
Write a 6-8 page paper where you (1) MAKE AN ARGUMENT about the nature of virtual communities and/or social media based on your data you collected from your experience with the virtual community that you chose. Please state your argument clearly in the first page (or paragraph) of the paper.
For example, “In this paper, through participant observation in the sub-Reddit gaming community, I argue that limitations in interactivity prevent the development of strong ties, but using social media to promote and advertise more interactive and engaging events have the potential to create a vibrant, diverse, and vast blended community.” This thesis is very specific in terms of the argument and theories that it will interact with, as well as some of the qualities that it tries to prove. It is also general in that it implies an argument that goes beyond just Reddit (and could be applied to other similar communities). The paper tries to prove that 1) interactivity is a crucial component to developing strong ties over social media, 2) but strong ties are possible and supported through social media, and 3) that these ties are diverse and come from specific forms of engagement that social media can support.
After making your argument clearly, (2) PROVIDE EVIDENCE FROM YOUR DATA as well as (3) UTILIZE AT LEAST TWO READINGS FROM THIS CLASS to make your case. Please provide detailed and specific examples from your participant observation. This means talking about specific interactions and observations. Describe an interaction. What did you post/say? How did they respond? How does this interaction prove your thesis/argument? How do readings (at least 2), theories, and concepts from this class also support your interpretation of your evidence? In other words, how do the readings prove your argument? Conversely, if what you find somehow contradicts the findings in readings, provide more evidence and explanations to show how and suggest why you observed such a difference.
As with the disconnect paper, your interactions with the readings are CRUCIAL and should be the CENTER of the paper. In other words, choose to make an argument that interacts with at least 2 readings in the course. You likely could make MANY arguments with the data you found, but choose something that will allow for deep interaction with the class readings and let that be the focus of your thesis.
The key to this paper is your content and analysis–developing some compelling insight into your experience. Please see rubric Virtual Comm Paper Rubric Students.docx Download Virtual Comm Paper Rubric Students.docxfor more details on how to write a successful paper.
My suggestion on how to approach gathering data for this paper:
Step 1: Spend the first week doing some basic exploration and learning about the virtual community you have joined–try to become a member of that community during this time. Note things that stand out to you and you find interesting. Ask yourself meaningful questions about the community you are participating in.
Step 2: Once you feel like you have a good grasp of the community, review key themes that we have been discussing in the course. Review the syllabus (looking ahead as well as behind where we are in the course) and look for readings and topics that you think are relevant and interesting to your virtual community. Choose at least 2 readings that you think will be good to engage with in your paper as it relates to your virtual community.
Step 3: Go back to your virtual community and gather more data. This time, do not just do general exploration, but rather focus on the key themes, concepts, and ideas that appear in those 2 readings you chose and gather more data surrounding those readings. Ask yourself key research questions that relate to those readings about your virtual community and try to find data that will help you answer the research question
A simple example: Can you make strong ties on the Internet? Several readings on the syllabus asks this question in different ways. You could ask the same kind of question of your virtual community. In step 3, you would do deliberate, targeted interactions to try to answer this question in regards to your virtual community. Then, when you go to write your paper, you would use the readings to help you compare and contrast the data you discovered and whether or not it is possible to make strong ties in your virtual community and discover why it is or isn’t.
FAQ:
1. What kind of virtual community works for this paper? (this is repeated from your proposal assignment)
A virtual community that has a visible, discernible boundary where you can identify members clearly is generally the kind of virtual community that will work for this. So that means saying “Facebook” might be simply too large, but identifying a subgroup on Facebook (like a Facebook Group) would likely work better. For Twitter or Instagram, this could be a hashtag or communities that revolve around a specific person, theme, etc. Look for subgroups rather than overly large communities with unidentifiable boundaries.
Blended communities (communities that are partially virtual and partially offline/face-to-face) work as well, as long as a relatively large portion of interaction takes place online. This would include things like dating apps, Meet Ups, and other communities that have a predominately online interaction space but has a significant physical component as well.
You are welcome to do a virtual community that you have been a part of for awhile–my only concern is that if you are too close to the community, it could blind you to interesting things to notice, simply because you are too close to the culture of that community. You should pick something that interests you, but something new could also be beneficial for this assignment.
One suggestion is to look for niche virtual communities. These are sometimes on random websites, fan pages, forum spaces, reddit subgroups, etc. and are not always found on massively popular and mainstream social media websites. Some of the most interesting virtual communities are more specific and more hidden. These communities can be relatively small, as long as there is daily engagement so that you can plug yourself in and really get to know people.
The virtual community should also have a social media space that allows you relatively meaningful engagements. In other words, if you did some kind of gaming community, look for specific spaces to engage with a set group of people. This could be a guild, discord site, fan page, resource guide/community, etc. Just playing the game will not work as you probably have fairly limited access to engagements and gathering data.
2. I don’t see a reading that really fits with what I want to talk about in my paper. Can I draw on outside readings?
The short answer is no. This is NOT a real research paper. Unfortunately, I don’t have the resources or guidance to feel comfortable unleashing you all to go online to do independent research. Instead, I think of this project more as an introduction to virtual community research that uses simple, flexible research methods as a way to introduce you to the field–perhaps in the future, you can build off of what you do in this class.
As a result, you are only graded on readings that are found on the syllabus. This MAY limit the scope of what you can talk about (see above suggestions on how to approach gathering data for this paper). If there is a course concept that appeared in lecture but I did not assign on the syllabus, you ABSOLUTELY can use this reading if you get approval. Please come talk to me as soon as possible to get permission and a copy of the reading that pertains to the course concept and you can use that in your paper and it will count towards your usage of two readings.
The essay needs to be about a virtual community that is centered round NBA content specifically the golden state warriors.
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The Strength of Weak Ties
Author(s): Mark S. Granovetter
Source: American Journal of Sociology , May, 1973, Vol. 78, No. 6 (May, 1973), pp. 13601380
Published by: The University of Chicago Press
Stable URL: https://www.jstor.org/stable/2776392
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The Strength of Weak Ties’
Mark S. Granovetter
Johns Hopkins University
Analysis of social networks is suggested as a tool for linking micro
and macro levels of sociological theory. The procedure is illustrated
by elaboration of the macro implications of one aspect of small-scale
interaction: the strength of dyadic ties. It is argued that the degree
of overlap of two individuals’ friendship networks varies directly
with the strength of their tie to one another. The impact of this
principle on diffusion of influence and information, mobility opportunity, and community organization is explored. Stress is laid on the
cohesive power of weak ties. Most network models deal, implicitly,
with strong ties, thus confining their applicability to small, welldefined groups. Emphasis on weak ties lends itself to discussion of
relations between groups and to analysis of segments of social structure not easily defined in terms of primary groups.
A fundamental weakness of current sociological theory is that it does not
relate micro-level interactions to macro-level patterns in any convincing
way. Large-scale statistical, as well as qualitative, studies offer a good
deal of insight into such macro phenomena as social mobility, community
organization, and political structure. At the micro level, a large and increas-
ing body of data and theory offers useful and illuminating ideas about what
transpires within the confines of the small group. But how interaction in
small groups aggregates to form large-scale patterns eludes us in most cases.
I will argue, in this paper, that the analysis of processes in interpersonal
networks provides the most fruitful micro-macro bridge. In one way or
another, it is through these networks that small-scale interaction becomes
translated into large-scale patterns, and that these, in turn, feed back into
small groups.
Sociometry, the precursor of network analysis, has always been curiously
peripheral-invisible, really-in sociological theory. This is partly because
it has usually been studied and applied only as a branch of social psy-
chology; it is also because of the inherent complexities of precise network
analysis. We have had neither the theory nor the measurement and sampling techniques to move sociometry from the usual small-group level to
that of larger structures. While a number of stimulating and suggestive
1 This paper originated in discussions with Harrison White, to whom I am indebted
for many suggestions and ideas. Earlier drafts were read by Ivan Chase, James Davis,
William Michelson, Nancy Lee, Peter Rossi, Charles Tilly, and an anonymous referee;
their criticisms resulted in significant improvements.
1360 AJS Volume 78 Number 6
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The Strength of Weak Ties
studies have recently moved in this direction (Bott 1957; Mayer 1961;
Milgram 1967; Boissevain 1968; Mitchell 1969), they do not treat struc-
tural issues in much theoretical detail. Studies which do so usually involve
a level of technical complexity appropriate to such forbidding sources as
the Bulletin of Mathematical Biophysics, where the original motivation for
the study of networks was that of developing a theory of neural, rather
than social, interaction (see the useful review of this literature by Coleman
[1960]; also Rapoport [1963]).
The strategy of the present paper is to choose a rather limited aspect of
small-scale interaction-the strength of interpersonal ties-and to show,
in some detail, how the use of network analysis can relate this aspect to
such varied macro phenomena as diffusion, social mobility, political organization, and social cohesion in general. While the analysis is essentially
qualitative, a mathematically inclined reader will recognize the potential
for models; mathematical arguments, leads, and references are suggested
mostly in footnotes.
THE STRENGTH OF TIES
Most intuitive notions of the “strength” of an interpersonal tie should be
satisfied by the following definition: the strength of a tie is a (probably
linear) combination of the amount of time, the emotional intensity, the
intimacy (mutual confiding), and the reciprocal services which characterize
the tie.2 Each of these is somewhat independent of the other, though the
set is obviously highly intracorrelated. Discussion of operational measures
of and weights attaching to each of the four elements is postponed to future
empirical studies.3 It is sufficient for the present purpose if most of us can
agree, on a rough intuitive basis, whether a given tie is strong, weak, or
absent.4
2 Ties discussed in this paper are assumed to be positive and symmetric; a comprehensive theory might require discussion of negative and/or asymmetric ties, but this
would add unnecessary complexity to the present, exploratory comments.
3 Some anthropologists suggest “multiplexity,” that is, multiple contents in a relationship, as indicating a strong tie (Kapferer 1969, p. 213). While this may be accurate
in some circumstances, ties with only one content or with diffuse content may be
strong as well (Simmel 1950, pp. 317-29). The present definition would show most
multiplex ties to be strong but also allow for other possibilities.
4 Included in “absent” are both the lack of any relationship and ties without substantial significance, such as a “nodding” relationship between people living on the
same street, or the “tie” to the vendor from whom one customarily buys a morning
newspaper. That two people “know” each other by name need not move their relation
out of this category if their interaction is negligible. In some contexts, however
(disasters, for example), such “negligible” ties might usefully be distinguished from
the absence of one. This is an ambiguity caused by substitution, for convenience of
exposition, of discrete values for an underlying continuous variable.
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American Journal of Sociology
Consider, now, any two arbitrarily selected individuals-call them A and
B-and the set, S = Cy D, E, … , of all persons with ties to either or both
of them.5 The hypothesis which enables us to relate dyadic ties to larger
structures is: the stronger the tie between A and B, the larger the propor-
tion of individuals in S to whom they will both be tied, that is, connected
by a weak or strong tie. This overlap in their friendship circles is predicted
to be least when their tie is absent, most when it is strong, and intermediate
when it is weak.
The proposed relationship results, first, from the tendency (by definition)
of stronger ties to involve larger time commitments. If A-B and A-C ties
exist, then the amount of time C spends with B depends (in part) on the
amount A spends with B and C, respectively. (If the events “A is with B”
and “A is with C” were independent, then the event “C is with A and B”
would have probability equal to the product of their probabilities. For
example, if A and B are together 60% of the time, and A and C 40%,
then C, A, and B would be together 24% of the time. Such independence
would be less likely after than before B and C became acquainted.) If C
and B have no relationship, common strong ties to A will probably bring
them into interaction and generate one. Implicit here is Homans’s idea that
“the more frequently persons interact with one another, the stronger their
sentiments of friendship for one another are apt to be” (1950, p. 133).
The hypothesis is made plausible also by empirical evidence that the
stronger the tie connecting two individuals, the more similar they are, in
various ways (Berscheid and Walster 1969, pp. 69-91; Bramel 1969,
pp. 9-16; Brown 1965, pp. 71-90; Laumann 1968; Newcomb 1961, chap.
5; Precker 1952). Thus, if strong ties connect A to B and A to C, both C
and B, being similar to A, are probably similar to one another, increasing
the likelihood of a friendship once they have met. Applied in reverse, these
two factors-time and similarity-indicate why weaker A-B and A-C ties
make a C-B tie less likely than strong ones: C and B are less likely to
interact and less likely to be compatible if they do.
The theory of cognitive balance, as formulated by Heider (1958) and
especially by Newcomb (1961, pp. 4-23), also predicts this result. If strong
ties A-B and A-C exist, and if B and C are aware of one another, anything
short of a positive tie would introduce a “psychological strain” into the
situation since C will want his own feelings to be congruent with those of
his good friend, A, and similarly, for B and his friend, A. Where the ties
are weak, however, such consistency is psychologically less crucial. (On
this point see also Homans [1950, p. 255] and Davis [1963, p. 448].)
Some direct evidence for the basic hypothesis exists (Kapferer 1969,
p. 229 n.; Laumann and Schuman 1967; Rapoport and Horvath 1961;
5 In Barnes’s terminology, the union of their respective primary stars (1969, p. 58).
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The Strength of Weak Ties
Rapoport 1963). 6 This evidence is less comprehensive than one might hope.
In addition, however, certain inferences from the hypothesis have received
empirical support. Description of these inferences will suggest some of the
substantive implications of the above argument.
WEAK TIES IN DIFFUSION PROCESSES
To derive implications for large networks of relations, it is necessary to
frame the basic hypothesis more precisely. This can be done by investigating the possible triads consisting of strong, weak, or absent ties among
A, B, and any arbitrarily chosen friend of either or both (i.e., some member
of the set S, described above). A thorough mathematical model would do
this in some detail, suggesting probabilities for various types. This analysis
becomes rather involved, however, and it is sufficient for my purpose in this
paper to say that the triad which is most unlikely to occur, under the
hypothesis stated above, is that in which A and B are strongly linked, A
has a strong tie to some friend C, but the tie between C and B is absent.
This triad is shown in figure 1. To see the consequences of this assertion,
C
A
B
FIG. 1.-Forbidden triad
I will exaggerate it in what follows by supposing that the triad shown never
occurs-that is, that the B-C tie is always present (whether weak or
strong), given the other two strong ties. Whatever results are inferred
from this supposition should tend to occur in the degree that the triad in
question tends to be absent.
6 The models and experiments of Rapoport and his associates have been a major stimulus to this paper. In 1954 he commented on the “well-known fact that the likely
contacts of two individuals who are closely acquainted tend to be more overlapping
than those of two arbitrarily selected individuals” (p. 75). His and Horvath’s 1961
hypothesis is even closer to mine: “one would expect the friendship relations, and
therefore the overlap bias of the acquaintance circles, to become less tight with increasing numerical rank-order” (p. 290). (I.e., best friend, second-best friend, third-
best, etc.) Their development of this hypothesis, however, is quite different, substantively and mathematically, from mine (Rapoport 1953a, 1953b, 1954, 1963; Rapoport
and Horvath 1961).
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American Journal of Sociology
Some evidence exists for this absence. Analyzing 651 sociograms, Davis
(1970, p. 845) found that in 90% of them triads consisting of two mutual
choices and one nonchoice occurred less than the expected random number
of times. If we assume that mutual choice indicates a strong tie, this is
strong evidence in the direction of my argument.7 Newcomb (1961, pp. 160-
65) reports that in triads consisting of dyads expressing mutual “high
attraction,” the configuration of three strong ties became increasingly
frequent as people knew one another longer and better; the frequency of
the triad pictured in figure 1 is not analyzed, but it is implied that processes
of cognitive balance tended to eliminate it.
The significance of this triad’s absence can be shown by using the
concept of a “bridge”; this is a line in a network which provides the only
path between two points (Harary, Norman, and Cartwright 1965, p. 198).
Since, in general, each person has a great many contacts, a bridge between
A and B provides the only route along which information or influence can
flow from any contact of A to any contact of B, and, consequently, from
anyone connected indirectly to A to anyone connected indirectly to B. Thus,
in the study of diffusion, we can expect bridges to assume an important
role.
Now, if the stipulated triad is absent, it follows that, except under un-
likely conditions, no strong tie is a bridge. Consider the strong tie A-B: if A
has another strong tie to C, then forbidding the triad of figure 1 implies
that a tie exists between C and B, so that the path A-C-B exists between A
and B; hence, A-B is not a bridge. A strong tie can be a bridge, therefore,
only if neither party to it has any other strong ties, unlikely in a social
network of any size (though possible in a small group). Weak ties suffer no
such restriction, though they are certainly not automatically bridges. What
is important, rather, is that all bridges are weak ties.
In large networks it probably happens only rarely, in practice, that a
specific tie provides the only path between two points. The bridging func-
tion may nevertheless be served locally. In figure 2a, for example, the tie
A-B is not strictly a bridge, since one can construct the path A-E-I-B (and
others). Yet, A-B is the shortest route to B for F, D, and C. This function
is clearer in figure 2b. Here, A-B is, for C, D, and others, not only a local
bridge to B, but, in most real instances of diffusion, a much more likely
and efficient path. Harary et al. point out that “there may be a distance
[length of path] beyond which it is not feasible for u to communicate with
7 This assumption is suggested by one of Davis’s models (1970, p. 846) and made
explicitly by Mazur (1971). It is not obvious, however. In a free-choice sociometric
test or a fixed-choice one with a large number of choices, most strong ties would
probably result in mutual choice, but some weak ones might as well. With a small,
fixed number of choices, most mutual choices should be strong ties, but some strong
ties might show up as asymmetric. For a general discussion of the biases introduced
by sociometric procedures, see Holland and Leinhardt (1971b).
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The Strength of Weak Ties
E
c~~~~~~~~~~~~~~~~
D
C~
AH
A
B
G
X
D/
E
(b)
FIG. 2.-Local bridges. a, Degree 3; b, Degree 13. = strong tie;
weak tie.
v because of costs or distortions entailed in each act of transmission. If v
does not lie within this critical distance, then he will not receive messages
originating with u” (1965, p. 159). I will refer to a tie as a “local bridge
of degree n” if n represents the shortest path between its two points (other
than itself), and n > 2. In figure 2a, A-B is a local bridge of degree 3, in
2b, of degree 13. As with bridges in a highway system, a local bridge in a
social network will be more significant as a connection between two sectors
to the extent that it is the only alternative for many people-that is, as its
degree increases. A bridge in the absolute sense is a local one of infinite
degree. By the same logic used above, only weak ties may be local bridges.
Suppose, now, that we adopt Davis’s suggestion that “in interpersonal
flows of most any sort the probability that ‘whatever it is’ will flow from
person i to person j is (a) directly proportional to the number of all-positive
(friendship) paths connecting i and j; and (b) inversely proportional to
the length of such paths” (1969, p. 549).8 The significance of weak ties,
then, would be that those which are local bridges create more, and shorter,
paths. Any given tie may, hypothetically, be removed from a network; the
number of paths broken and the changes in average path length resulting
8 Though this assumption seems plausible, it is by no means self-evident. Surprisingly
little empirical evidence exists to support or refute it.
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American Journal of Sociology
between arbitrary pairs of points (with some limitation on length of path
considered) can then be computed. The contention here is that removal of
the average weak tie would do more “damage” to transmission probabilities
than would that of the average strong one.9
Intuitively speaking, this means that whatever is to be diffused can reach
a larger number of people, and traverse greater social distance (i.e., path
length),’0 when passed through weak ties rather than strong. If one tells
a rumor to all his close friends, and they do likewise, many will hear the
rumor a second and third time, since those linked by strong ties tend to
share friends. If the motivation to spread the rumor is dampened a bit on
each wave of retelling, then the rumor moving through strong ties is much
more likely to be limited to a few cliques than that going via weak ones;
bridges will not be crossed.11
Since sociologists and anthropologists have carried out many hundreds of
diffusion studies-Rogers’s 1962 review dealt with 506-one might suppose
that the above claims could easily be put to test. But this is not so, for
several reasons. To begin with, though most diffusion studies find that
personal contacts are crucial, many undertake no sociometric investigation.
(Rogers [1962] discusses this point.) When sociometric techniques are
used, they tend to discourage the naming of those weakly tied to the
respondent by sharply limiting the numbers of choices allowed. Hence, the
proposed importance of weak ties in diffusion is not measured. Even when
more sociometric information is collected there is almost never an attempt
to directly retrace the exact interpersonal paths traversed by an (idea,
rumor, or) innovation. More commonly, the time when each individual
adopted the innovation is recorded, as is the number of sociometric choices
he received from others in the study. Those receiving many choices are
characterized as “central,” those with few as “marginal”; this variable is
then correlated with time of adoption and inferences made about what paths
were probably followed by the innovation.
9 In a more comprehensive treatment it would be useful to consider to what extent a
set of weak ties may be considered to have bridging functions. This generalization
requires a long, complex discussion and is not attempted here (see Harary et al. 1965,
pp. 211-16).
10 We may define the “social distance” between two individuals in a network as the
number of lines in the shortest path from one to another. This is the same as the
definition of “distance” between points in graph theory (Harary et al. 1965, pp. 32-33,
138-41). The exact role of this quantity in diffusion and epidemic theory is discussed
by Solomonoff and Rapoport (1951).
11 If a damping effect is not specified, the whole population would hear the rumor
after a sufficiently large number of retellings, since few real networks include totally
self-contained cliques. The effective difference between using weak and strong ties,
then, is one of people reached per unit of (ordinal) time. This could be called
“velocity” of transmission. I am indebted to Scott Feld for this point.
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The Strength of Weak Ties
One point of controversy in diffusion studies can be related to my
argument. Some have indicated that early innovators are marginal, that
they “underconform to norms to such a degree that they are perceived
as highly deviant” (Rogers 1962, p. 197). Others (e.g., Coleman, Katz,
and Menzel [1966] on the adoption of a new drug by doctors) find that
those named more frequently adopt an innovation substantially earlier.
Becker (1970) tries to resolve the question of whether early innovators
are ”central” or “marginal” by referring to the “perceived risks of adoption
of a given innovation.” His study of public health innovations shows that
when a new program is thought relatively safe and uncontroversial (as with
the drug of Coleman et al.), central figures lead in its adoption; otherwise,
marginal ones do (p. 273). He explains the difference in terms of a greater
desire of “central” figures to protect their professional reputation.
Kerckhoff, Back, and Miller (1965) reach a similar conclusion in a
different type of study. A Southern textile plant had been swept by “hysterical contagion”: a few, then more and more workers, claiming bites
from a mysterious “insect,” became nauseous, numb, and weak, leading to
a plant shutdown. When the affected workers were asked to name their
three best friends, many named one another, but the very earliest to be
stricken were social isolates, receiving almost no choices. An explanation,
compatible with Becker’s, is offered: since the symptoms might be thought
odd, early “adopters” were likely to be found among the marginal, those
less subject to social pressures. Later, “it is increasingly likely that some
persons who are socially integrated will be affected. . . . The contagion
enters social networks and is disseminated with increasing rapidity” (p. 13).
This is consistent with Rogers’s comment that while the first adopters of
innovations are marginal, the next group, “early adopters,” “are a more
integrated part of the local social system than the innovators” (1962, p.
183).
“Central” and “marginal” individuals may well be motivated as claimed;
but if the marginal are genuinely so, it is difficult to see how they can ever
spread innovations successfully. We may surmise that since the resistance
to a risky or deviant activity is greater than to a safe or normal one, a larger
number of people will have to be exposed to it and adopt it, in the early
stages, before it will spread in a chain reaction. Individuals with many
weak ties are, by my arguments, best placed to diffuse such a difficult in-
novation, since some of those ties will be local bridges.12 An initially un12 These individuals are what is often called, in organizational analysis, “liaison persons,”
though their role here is different from the one usually discussed. (Cf. the concept in
graph theory of a “cut point”-one which, if removed from a graph, disconnects one
part from another [Harary 19651.) In general, a bridge has one liaison person on each
side, but the existence of a liason person does not imply that of a bridge. For local
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American Journal of Sociology
popular innovation spread by those with few weak ties is more likely to be
confined to a few cliques, thus being stillborn and never finding its way
into a diffusion study.
That the “marginal” innovators of diffusion studies might actually be
rich in weak ties is possible, given the usual sociometric technique, but in
most cases this is purely speculative. Kerckhoff and Back, however, in a
later more detailed analysis of the hysteria incident, indicate that besides
asking about one’s “three best friends,” they also asked with whom
workers ate, worked, shared car pools, etc. They report that five of the six
workers earliest affected “are social isolates when friendship choices are
used as the basis of analysis. Only 1 of the 6 is mentioned as a friend by
anyone in our sample. This is made even more striking when we note that
these 6 women are mentioned with considerable frequency when other bases
for choice are used. In fact, they are chosen more frequently on a ‘nonfriendship’ basis than are the women in any of the other categories” (1968,
p. 112).
This finding lends credence to the weak-tie argument, but is inconclusive.
A somewhat different kind of diffusion study offers more direct support:
the “small-world” investigations of Milgram and his associates. The name
of these studies stems from the typical comment of newly introduced indi-
viduals who discover some common acquaintance; this situation is generalized in an attempt to measure, for arbitrarily chosen pairs of individuals
in the United States, how long a path of personal contacts would be needed
to connect them. A booklet is given to randomly designated senders who
are asked to forward it toward some named target person, via someone the
sender knows personally who would be more likely than himself to know
the target. The new recipient then advances the booklet similarly; eventually it reaches the target or someone fails to send it on. The proportion of
such chains completed has ranged from 12%7o to 33%o in different studies,
and the number of links in completed chains has ranged from two to 10,
averaging between five and eight (Milgram 1967; Travers and Milgram
1969; Korte and Milgram 1970).
Each time someone forwards a booklet he also sends a postcard to the
researchers, indicating, among other things, the relationship between him-
self and the next receiver. Two of the categories which can be chosen are
“friend” and “acquaintance.” I will assume that this corresponds to
“strong” and “weak” ties. In one of the studies, white senders were asked
to forward the booklet to a target who was Negro. In such chains, a crucial
point was the first sending of the booklet from a white to a Negro. In 50%o
bridges, the concept of local liaisons could be developed. In a more microscopically
oriented discussion I would devote more time to the liaison role. For now, I only point
out that, under the present assumptions, one can be a liaison between two network
sectors only if all his ties into one or both are weak.
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The Strength of Weak Ties
of the instances where the white described this Negro as an “acquaintance,”
the chain was ultimately completed; completion rate fell to 26%, however,
when the white sent the booklet to a Negro “friend.” (My computation,
based on unpublished data kindly supplied by Charles Korte. See Korte
[1967] and Korte and Milgram [1970].) Thus, weaker interracial ties can
be seen to be more effective in bridging social distance.
Another relevant study, by Rapoport and Horvath (1961), is not exactly
one of diffusion but is closely related in that it traces out paths along
which diffusion could take place. They asked each individual in a Michigan
junior high school (N – 851) to list his eight best friends in order of preference. Then, taking a number of random samples from the group (sample
size, an arbitrary number, was nine), they traced out, for each sample, and
averaged over all the samples, the total number of people reached by fol-
lowing along the network of first and second choices. That is, the first and
second choices of each sample member were tabulated, then the first and
second choices of these people were added in, etc., counting, at each remove,
only names not previously chosen, and continuing until no new people were
reached. The same procedure was followed using second and third choices,
third and fourth, etc., up to seventh and eighth. (The theoretical connection of this tracing procedure to diffusion is discussed by Rapoport [1953a,
1953b, and especially 1954].)
The smallest total number of people were reached through the networks
generated by first and second choices-presumably the strongest ties-and
the largest number through seventh and eighth choices. This corresponds
to my assertion that more people can be reached through weak ties. A
parameter in their mathematical model of the sociogram, designed to measure, approximately, the overlap of acquaintance circles, declined monotonically with increasing rank order of friends.13
WEAK TIES IN EGOCENTRIC NETWORKS
In this section and the next, I want to discuss the general significance of
the above findings and arguments at two levels: first that of individuals,
then that of communities. These discussions make no pretense of being
comprehensive; they are meant only to illustrate possible applications.
In recent years, a great deal of literature has appeared analyzing the
impact on the behavior of individuals of the social networks in which they
are imbedded. Some of the studies have emphasized the ways in which
13 This parameter, 0, measures such overlap in the following sense: it is zero in a
random net-one in which individuals choose others at random-and is one in a net
made up entirely of cliques disconnected each from every other. Intermediate values of
0, however, do not have a good intuitive interpretation in terms of individuals, but
only with reference to the particular mathematical model defining the parameter; thus
it does not correspond precisely to my arguments about friendship overlap.
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American Journal of Sociology
behavior is shaped and constrained by one’s network (Bott 1957; Mayer
1961; Frankenberg 1965), others the ways in which individuals can
manipulate these networks to achieve specific goals (Mayer 1966; Bois-
sevain 1968; Kapferer 1969). Both facets are generally supposed to be
affected by the structure of one’s network. Bott argued that the crucial
variable is that of whether one’s friends tend to know one another (“closeknit” network) or not (“loose-knit” network). Barnes makes this dichotomy into a continuous variable by counting the number of ties observed
in the network formed by ego and his friends and dividing it by the ratio
of possible ones; this then corresponds to what is often called network
“density” (Barnes 1969; Tilly 1969).14
Epstein (1969) points out, however, that different parts of ego’s network
may have different density. He calls those with whom one “interacts most
intensely and most regularly, and who are therefore also likely to come to
know one another,” the “effective network”; the “remainder constitute
the extended network” (pp. 110-11). This is close to saying, in my terms,
that one’s strong ties form a dense network, one’s weak ties a less dense one.
I would add that one’s weak ties which are not local bridges might as well
be counted with the strong ties, to maximize separation of the dense from
the less dense network sectors.
One point on which there is no general agreement is whether ego’s network should be treated as composed only of those to whom he is tied
directly, or should include the contacts of his contacts, and/or others.
Analyses stressing encapsulation of an individual by his network tend to
take the former position, those stressing manipulation of networks, the
latter, since information or favors available through direct contacts may
depend on who their contacts are. I would argue that by dividing ego’s
network into that part made up of strong and nonbridging weak ties on
the one hand, and that of bridging weak ties on the other, both orientations
can be dealt with. Ties in the former part should tend to be to peo
