Social Network Theory Public Health Definition
Social network theory focuses on the role of social relationships in transmitting information, channeling personal or media influence, and enabling attitudinal or behavioral change. Since the 1960s, social network theory has significantly expanded the horizon of media effects research, with increasing application of network analytic methods in various empirical contexts. The two-step flow of communication hypothesis, the theory of weak ties, and the theory of diffusion of innovations are three major theoretical approaches that integrate network concepts in understanding the flow of mediated information and its effects.
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Social Network Theory
WENLIN LIU, ANUPREET SIDHU, AMANDA M. BEACOM,
and THOMAS W. VALENTE
University of Southern California, USA
Research history and key concepts
A diverse array of research traditions has shaped the current state of social network
theory. As Scott (1991) summarizes, there are three lines of research that contributed
to the theory's early development: the sociometric analysis tradition, which relies on
graph theory methods from mathematics; the interpersonal relations tradition, which
focuses on the formation of cliques among a group of individuals; and an anthropol-
ogy tradition that explores the structure of community relations in less developed
societies.
ese research traditions did not evolve into a coherent theoretical framework until
the 1960s. A number of sociologists signicantly advanced the social network approach
by synthesizing previous theoretical traditions and extending them to understand both
formal and informal social relations. For example, the sociometric view of social net-
works was elaborated, emphasizing structural properties, such as the relative location
of individual nodes in the network. Researchers during this time also advanced social
networktechniquesbyproposingblock modeling and multidimensional scaling .Block
modeling considers the particular position of a node in a social network. is method
enables researchers to identify nodes that have similar network positions, or what is
called structurally equivalent nodes. e scaling technique, on the other hand, allows
researchers to convert social relationships into sociometric distance ,therebymapping
these relationships in a social space (Wasserman & Faust, 1994).
ree key network concepts that have organized research on network eects are
centrality, cohesion, and structural equivalence. Freeman (1979) proposed three dis-
tinct measures to indicate structural centrality: degree, closeness, and betweenness.
is seminal paper aorded a nuanced understanding of centrality, and it established
a process through which new network measures were developed to have a raw form,
a normalized form, and a network-level form. Freeman's (1979) paper also motivated
subsequent research to assess how dierent forms of network centrality interact with the
ow of information dierently. For example, Borgatti's simulation study (2005) identi-
ed a typology of ow processes, and he showed that the values of dierent central posi-
tions depend on the characteristics of the process (e.g., gossip diusion versus goods
delivery).
Network cohesion measures the degree of interconnections among a group of nodes.
is measure has long been useful to detect subgroups or cliques within the larger
e International Encyclopedia of Media Eects.
Patrick Rössler (Editor-in-Chief), Cynthia A. Honer, and Liesbet van Zoonen (Associate Editors).
© 2017 John Wiley & Sons, Inc. Published 2017 by John Wiley & Sons, Inc.
DOI: 10.1002/9781118783764.wbieme0092
2SOCIAL NETWORK THEORY
social network (Burt, 1987). In the context of media eects research, network cohesion
serves as an important structural feature that moderates the inuence of interpersonal
networks. Friedkin's (1993) longitudinal study, among others, found that personal inu-
ence grows stronger within more cohesive social networks than less cohesive ones.
Finally, structural equivalence indicates two or more network positions that share a
similar pattern of connections with the rest of the network. Actors that occupy struc-
turally equivalent positions oen have similar characteristics, such as social status or
other individual traits. Because equivalent nodes are connected to a similar set of actors,
they are more likely to receive similar information or social inuence. In understanding
the process of diusion, Burt's (1987) study found that innovations were more likely to
ow via structural equivalence than direct ties, suggesting equivalence inuence may
be a stronger predictor of behavioral adoption than cohesive inuence. Burt (1999)
further elaborated on these mechanisms to explain the role of opinion leaders in the
media eects context. He argued that there were two dierent network mechanisms at
play: a two-step ow process that consisted of opinion leaders spreading information to
the group, and a contagion process via structural equivalence that generated adoption
behaviors within the group.
e years since the 1990s have witnessed extensive applications of key network
concepts in diverse research contexts, and the eld has also constantly been updated
with more rened network measures and analytic tools. In the arena of media
eects research, the fundamental question is: How do social networks, including the
quality and quantity of relational ties, the structural position of individual actors in
anetwork,andtheoverallnetworkproperties(e.g.,itsdensity,centralization,and
modularity) impact the ow of media messages and their eects on the audience?
ese eects include public opinion formation, marketing, uses and gratications of
media consumption, and behavior change due to prosocial campaigns.
Although communication research did not substantially shape the initial develop-
ment of social network theory, there is an emerging trend of cross-pollination between
social network theory and media eects research. In large part, this cross-pollination
stems from the emergence of computer-mediated communication, which aords
explicit social networks as well as the modes of communication that bind them. e
following sections review three theoretical approaches that best represent the inuence
of social network theory.
Two-step flow of communication hypothesis
e two-step ow of communication hypothesis was rst proposed by Lazarsfeld,
Berelson and Gaudet in the book e People's Choice (1944). In their study of voting
decisions, they found personal inuence, which was largely derived from people's
social contacts and friendship networks, signicantly aected voting decisions. And
this eect was even more pronounced among people who were less committed to their
existing beliefs or who changed their minds during the course of a campaign. e
hypothesis is called two-step because the mass media initially inuence opinion leaders,
individuals who are perceived as inuential, who in turn inuence their social contacts.
SOCIAL NETWORK THEORY 3
Building on its initial formulation, Katz (1957) reviewed a number of corroborating
studies on this hypothesis and further elaborated on three important aspects of it.
First, the magnitude of personal inuence could be greater than that of mass media,
as rst identied in the 1940s voting study. Similar ndings also emerged from
subsequent cases, such as the Decatur Study, which examined individuals' fashion
decision making (Katz & Lazarsfeld, 1955). Second, in terms of the ow of personal
inuence, opinion leaders are not always concentrated at certain social strata, nor
does personal inuence always ow from a higher social stratum to a lower one. On
the contrary, studies have observed many cases of local leadership or issue-specic
leadership. at is, leaders dier for dierent groups of people and leaders lead in
some domains but not others. Finally, personal inuence does not necessarily work in
isolation from mass media. e voting study revealed that opinion leaders tended to
be those who were more exposed to the mass media. And, depending on the specic
context, personal inuence can either reinforce or attenuate the eect of traditional
mass media.
Central to the two-step ow of communication process is the concept of opinion
leaders, a group of individuals inuential in specic domains. Numerous studies have
attempted to identify the key characteristics associated with being inuential along
three lines (Katz, 1957): who one is , the individual characteristics of the opinion leaders,
such as personality traits, charisma, or demographic and socioeconomic backgrounds;
what one knows, the characteristics pertaining to individuals' competence, such as
their knowledge, expertise, or ability to provide information or guidance on particular
issues; and whom one knows , the characteristics related to an individual's structural
position in a network. In other words, individuals may become opinion leaders
not only because they possess certain attributes but also because they occupy the
right network positions that enable them to eectively spread information and exert
personal inuence. Centrality measures have been particularly useful for identifying
leaders based on their network position.
As discussed, social network theory has proposed three types of network centrality
measures to identify the advantageous position that opinion leaders usually occupy:
degree, betweenness, and closeness (Freeman, 1979). Degree centrality measures the
number of links to and from an individual in a network. Individuals with high degree
centrality are more likely to become opinion leaders because more social ties can mean
greater opportunities to receive as well as disseminate information (see Figure 1, black
node). Betweenness centrality measures the frequency at which an individual node
lies on the shortest path connecting other nodes in the network. Individuals high in
betweenness centrality are more likely to serve as a bridge in the network—dened as a
node that connects otherwise unconnected network clusters. Just like gatekeepers in a
network, if individuals high in betweenness centrality oppose the dissemination of an
idea, this piece of information may not be able to ow to other areas of the network. In
Figure 1, the light gray node occupies this critical position. Finally, closeness central-
ity measures the average distance between an individual node and all other nodes in
the network. Individuals with higher closeness centrality need relatively fewer steps to
reach all other individuals in the network and thus can potentially move information
faster. e ability to eectively reach other contacts in one's network makes individuals
4SOCIAL NETWORK THEORY
Opinion leaders with high
degree centrality
Opinion leaders with high
closeness centrality
Opinion leaders with high
betweenness centrality
Figure 1 Network illustration of opinion leaders with high degree centrality, closeness central-
ity, and betweenness centrality. Source: Adapted from Everett's kite, in Brandes and Hildenbrand,
2014.
with high closeness centrality inuential. In Figure 1, the dark gray nodes have high
closeness centrality.
As one of the most applied theories in media eects research, the two-step ow of
communication hypothesis has been rigorously tested in various empirical settings.
e research on public opinion formation and agenda-setting, for instance, has
studied how inuential individuals, such as early recognizers of social issues, may
mediate the public and the media agendas by identifying emerging issues in the
media, diusing them among public audiences, and ultimately aecting the media
agenda (Brosius & Weimann, 1996). Research on health interventions has examined
thedualinuencesofinterpersonalnetworksandmassmedia.InValenteandSaba's
(1998) study of a reproductive health communication campaign, they found both
the mass media campaign and personal networks were associated with individuals'
contraceptive adoption, but the impact of mass media was stronger for low threshold
individuals, those whose personal networks were composed of few contraceptive
users, than high threshold individuals, those whose networks contained a majority
of users.
Although the two-step ow hypothesis has been validated in numerous studies,
scholarship since the 1980s has pointed out that media inuence may take multiple,
recursive steps, and the overall process is more complex thana singular, one-directional
ow. With the rapid change in today's media and communication environment, some
scholars also argue that the role of opinion leaders is becoming less pivotal. Bennett
and Manheim (2006), among others, have proposed that the traditional two-step ow
of media messages has gradually transformed into a one-step ow process, where
SOCIAL NETWORK THEORY 5
mass media are becoming more fragmented and niche media increasingly engage
in narrowcasting . Under this changed landscape, media messages may directly reach
their audience and opinion leaders thus would play a less signicant role than was
previously theorized.
Thetheoryofweakties
e theory of weak ties, articulated in Granovetter's (1973) seminal piece "e Strength
of Weak Ties," concerns the role of weak social ties in diusing ideas and informa-
tion. In his labor-market study, Granovetter observed that people more oen found jobs
through their weak social ties, as opposed to relying on their family or close friends. He
measured tie strength through the frequency of contact, asking respondents how oen
theysaweachcontactaroundthetimetheyacquiredthepieceofjobinformation.
In addition to contact frequency, studies have proposed a combination of factors to
indicate the strength of social ties, such as the duration of interaction, the amount of
eort individuals invest in a relationship, the extent to which the social ties provide
reciprocal utility (e.g., social support), and the level of intimacy exchanged in a relation-
ship. Based on these criteria, weak ties are generally dened as social relations requiring
little investment, and they are composed mostly of acquaintances or other loosely con-
nected actors, as opposed to kin or close friends.
Why are weak ties more likely to channel novel information than strong ties? To
explain the underlying mechanism of Granovetter's ndings, it is necessary to return
to the network concept of bridging, mentioned previously in the denition of between-
ness centrality. Bridging ties are social connections that link two otherwise unconnected
network clusters. In other words, bridging ties provide the only path between two dis-
connected clusters, such as Cluster A and Cluster B in Figure 2. Granovetter found weak
ties were more likely to be bridging ties, because weak ties' peripheral position made
them better able to reach outside information than strong ties. In Figure 2, imagine each
network cluster represents a circle of close friends, as all the nodes in each cluster are
connected to each other. In such highly interconnected circles, each person is likely to
Cluster A
Bridging tie
Cluster B
Figure 2 Bridging ties.
6SOCIAL NETWORK THEORY
receive a similar set of information. e bridging tie (sitting between the two clusters),
on the other hand, becomes the only opportunity for any nodes in Cluster A to access
novel information from Cluster B.
Although strong ties oen emerge from the center of a network, which gives
them greater capacity to diuse information and exert social inuence, Granovetter's
thesis highlights the bridging function of weak ties and their ability to spread novel,
nonredundant information. e strength of weak ties, therefore, is not about the
numberofconnections.Rather,itliesinweakties'abilitytoreachabroader,and
potentially more heterogeneous, set of information sources. In the process of job
hunting, for example, the utility of strong ties diminishes, because they provide similar
and potentially redundant information to individuals.
Granovetter'sndingshaveledtoaseriesofreplicationstudies,suchasinthecon-
text of general information seeking, organizational knowledge sharing, the diusion
of innovations, community building, and many more. In the area of media eects,
studies have explored the role of weak discussion ties in promoting civic engagement.
For example, de Zúñiga and Valenzuela (2011) examined the association between
strong versus weak ties and individuals' online and oine civic engagement. Among
factors such as discussion frequency and discussion network size, they found the
frequency of weak-tie discussion was the strongest predictor of individuals' civic
behaviors.
e emergence of new media and social networking sites has created an increase in
online weak ties. Indeed, new media provide novel platforms through which individuals
can connect with geographically distant others, and functions such as "add friends,"
"follow the post," "mention," and "retweet" have been theorized as forms of weak social
ties. Some research has found evidence of online, mediated weak ties in maintaining
individuals' bridging social capital, such as Ellison, Steineld, and Lampe's (2007) study
on college students' Facebook friends networks, whereas other scholars have argued
that online connections may breed slacktivism , as they fail to nurture meaningful civic
participation. e rise of new media platforms thus urges scholars to reconsider the
denition, conceptual boundary, and new typologies of weak ties. It also encourages
new research to examine the role of mediated weak ties in diusing information and
exerting social inuence.
Diffusion of innovations
e diusion of innovations occurs between individuals or organizations in a social
system.econnectionpatternbetweentheactorswhoinitiate,relay,andadoptinno-
vations can be viewed as a social network, where network connections may take the
form of friendship, advice, communication, or social support. e diusion process is
essentiallyanetworkedprocess.Asinnovationstravelthroughaninterconnectedweb
of social connections, the structure and characteristics of this network can determine
how widely and how soon the innovations get adopted (Valente, 1995).
InseveraleditionsofthebookDiusion of Innovations , Rogers (2010) formally intro-
duced the model for diusion and dened it as "the process in which an innovation
SOCIAL NETWORK THEORY 7
is communicated through certain channels over time among the members of a social
system" (p. 5). Rice (2011) dened the process of diusion in the context of media eects
"as the process through which an innovation (an idea, product, technology, process, or
service) spreads (more or less rapidly, in more or less the same form) through mass
and digital media, and interpersonal and network communication, over time, through
a social system, with a wide variety of consequences (positive and negative)" (p. 1).
e groundbreaking study in the eld of diusion was conducted by Ryan and
Gross in 1943 while they were investigating the diusion of hybrid corn seeds among
farmers in Iowa (see Valente, 1995). e early network approach of diusion studies
looked at how opinion leader status, indicated by the number of times an individual
was nominated as a network partner, was correlated with the time of adoption. Later
there emerged a more structural approach, and this approach shied the focus to
examine how the overall network pattern inuenced the adoption of innovations,
such as network density, the presence of weak ties (Granovetter, 1973) or structurally
equivalent positions (Burt, 1987), and so forth. Valente (1995) proposed a social net-
work threshold model, and this model is particularly characterized by its system-level
emphasis.
A large body of diusion studies has focused on identifying the factors and forces
that lead to the adoption of innovations among members of a certain population. ese
studies also aim to understand why some individuals or organizations adopt the inno-
vation sooner while others take more time to accept the same idea or practice. Current
scholarship has identied four main elements of the diusion model (Rogers, 2010;
Valente, 1995): the rate of adoption, which can be inuenced by the perceived char-
acteristics of the innovation and can be measured by mathematical models (Valente,
1995); the rate of adoption over time, which yields a cumulative S-shaped pattern; the
various stages during the adoption process, which can be further classied as knowl-
edge, persuasion, decision, implementation, and conrmation; and the modication of
the innovation.
In general, the adoption process entails learning about a new product, getting more
information about it, making a decision to adopt it or not, experimenting with it, and
eventually conrming the use of the product. e pace of diusion can be determined
by certain characteristics of the innovation, which include its: relative advantage, com-
patibility, complexity, trialability, observability, cost, and radicalness. Less radical, less
complex, and less expensive innovations, and innovations perceived as more advanta-
geous, compatible, trialable, and observable, spread more rapidly.
e ve adoption stages—knowledge, persuasion, decision, implementation, and
conrmation—have long been useful for understanding media eects and behavioral
change. Additional theories have further developed the adoption stages to evaluate
media campaign eects. For example, the hierarchy of eects model proposed 12
steps leading to behavioral change, and it estimated that individuals usually proceed
from one step to the next at a rate of 80% (Valente, 1995). e transtheoretical model
proposed specic cognitive stages of change—precontemplation, contemplation,
preparation, action, and maintenance—for quitting a behavior such as smoking
(Prochaska, DiClemente, & Norcross, 1992). It should be noted that a homogenous
model usually cannot capture the varying diusion processes in dierent contexts.
8SOCIAL NETWORK THEORY
Networkmodelshavebeendevelopedtomodelsocialinuenceprocesseswith
network weight matrices, such as relational, positional, and centrality measures, and
the weights based on social distance.
Diusion research peaked in the early 1960s, and it has been rekindled with the
rapid emergence of newer and more advanced network models and technology. e
application of diusion theory spans a wide array of disciplines, such as marketing,
economics, mathematics, sociology, anthropology, and epidemiology, among many
others. In the area of media eects research, the main premise of the theory is that
innovations enter into communities from external sources such as mass media or tech-
nological advancements, and then they spread via social networks and interpersonal
communication.
Mass media play a critical role in initiating diusion among opinion leaders and low
threshold adopters, as these individuals are more likely to rely solely on media infor-
mation to adopt an innovation (Figure 3). For opinion leaders or early adopters, their
initial decision of adoption may be independent of their social network ties. rough
processes such as the two-step ow, opinion leaders then spread the innovation to their
adjacent social network partners. At this stage, the early majority and late majority
may seek additional validating information to reduce uncertainty regarding the inno-
vation, from both traditional mass media and online media platforms such as Facebook
and Google. Toole, Cha, and González (2012) studied the spatiotemporal adoption of
Twitter, a microblogging web application, while also considering the interplay between
media and word of mouth. Media inuences at later stages of adoption increased the
Twitter user base twofold to fourfold. A study on news diusion across various social
media platforms analyzed over 386 million Web documents over a 1-month period in
2011. It found that, depending on issue domains, dierent types of media had varying
Cluster A
Bridging tie
Mass media
Cluster B
1
3
3
3
3
3
4
4
4
1
2
2
2
2
2
2
2
2
Figure 3 Two-step ow. 1: early adopter; 2: early majority; 3: late majority; 4: laggards.
SOCIAL NETWORK THEORY 9
degreesofinuence.Specically,socialnetworkingsitesandblogsweremostinuential
in politics and culture, news media in the arts and economics, social media in controver-
sial topics such as protests, and single social platforms in entertainment (Kim, Newth, &
Christen, 2013). erefore, media can inuence one's perception of innovations as well
as one's adoption behaviors.
Key contributions and future directions
Social network theory and methods oer a distinct perspective on and set of tools
with which to understand media eects, enabling consideration of how micro- and
macrosocial structures mediate and moderate media eects. e theories of two-step
ow and diusion of innovations examine the paths by which mediated messages travel
through social networks, and the concepts of opinion leadership and tie strength oer
insights into critical variables that aect this ow. While each of the theories discussed
here was developed in the twentieth century during the golden age of mass media tech-
nologies, their theoretical contributions endure as scholars continue to test and rene
them in an era of social media and rapid evolution in media technologies. ree direc-
tions for current and future research are highlighted below.
First, new media technologies such as social networking sites, microblogging tools,
and online recommendation systems oer intriguing opportunities for further appli-
cation and extension of social network theory in the study of media eects. Current
research in this area falls into two broad categories. One category investigates whether
and how network-based media eects theories such as diusion and the strength of
weak ties operate dierently in dierent forms of social, as opposed to mass, media.
Forexample,researchsuggeststhatsomeofthetraditionalsocialnetworkmeasuresof
opinion leadership discussed above may not be the best indicators of social inuence
on Twitter (Gruzd & Wellman, 2014). A second category of research capitalizes on the
large amount of and novel types of data available through social media to rigorously
test network-based media eects theories in ways not previously possible. For example,
largecorpusesofdigitaltracedatathatavoidpotentialself-reportbiasesofsurveydata
can be used to create randomized controlled experiments of the diusion of consumer
and political behavior on Facebook.
Second, media eects researchers have begun to extend social network theory and
methods beyond classic social contagion processes to engage in what Ognyanova and
Monge (2013) describe as a "relational reinterpretation" of numerous mass communi-
cation phenomena. Hyperlink networks, for example, in which the nodes are websites
and the ties are the hyperlinks that connect them, may be analyzed to trace the dif-
fusion of content between mainstream media and blogs, or to determine the extent to
which prominent mainstream media versus bloggers wield inuence in media and pub-
lic agenda-setting. Semantic networks, in which the nodes are words and the ties are
cooccurrences of those words in various media, may be mapped to identify patterns
in how content is framed across dierent outlets over time. ese network approaches
oer promising new methods for research on core media eects theories.
10 SOCIAL NETWORK THEORY
ird, ongoing advances in the statistical approaches used in social network analy-
sis promise continued improvement in the sophistication with which researchers are
able to model how social structure shapes or is shaped by media eects. In particular,
the development of models that allow for multiplex (multiple types of ties), multimode
(multiple types of actors), and multilevel networks enables consideration of greater
complexity in the study of diusion and mediated social inuence. ese developments
are particularly relevant in a new media environment in which actors may be both pro-
ducers and consumers (potentially necessitating multiplex ties), and people may access
content from many dierent types of sources and using many dierent types of media
(requiring multiple modes and levels). In sum, communication research has never been
more promising or relevant, and the theories introduced here oer insights into how to
move communication research forward.
SEE ALSO: Agenda-Setting: Individual-Level Eects Versus Aggregate-Level Eects;
Diusion eories: Logic and Role of Media; Diusion eories: Media as Innovation;
Diusion eories: News Diusion; Multistep Flow of Communication: Evolution of
the Paradigm; Multistep Flow of Communication: Network Eects; Multistep Flow of
Communication: Online Media and Social Navigation; Multistep Flow of Communica-
tion: Opinion Leadership and Personality Strength; Network Society: Networks, Media,
and Eects; Social Networking
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Further reading
Burt, R. S. (2000). e network structure of social capital. Research in Organizational Behavior ,
22, 345–423. doi: 10.1016/s0191-3085(00)22009-1
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12 SOCIAL NETWORK THEORY
Wenlin Liu is a doctoral candidate at the Annenberg School for Communication,
University of Southern California, USA. Her research interests lie at the intersection
of interorganizational communication and social network theory and methodology.
Wenlin is a research member of the Center for Applied Network Analysis, led by
Dr. omas W. Valente.
Anupreet Sidhu is a doctoral student at the Department of Preventive Medicine, Uni-
versity of Southern California, USA. Her research interests lie in the area of health
campaign evaluation and social networks, specically in health promotion contexts.
Anupreet is a member of the Center for Applied Network Analysis, led by Dr. omas
W. V a l e n t e .
Amanda M. Beacom is a doctoral candidate at the Annenberg School for Communica-
tion, University of Southern California, USA. She conducts research on organizational
communication and social networks, particularly in health contexts.
omas W. Valente is professor in the Department of Preventive Medicine, Univer-
sity of Southern California, USA. He is the author of the books Social Networks and
Health: Models, Methods, and Applications (2010) and Network Models of the Diusion
of Innovation (1995).
... Granovetter's work [10] on Weak Tiestheory demonstrates that a person's weak contacts are more likely to bring novel information such as job opportunities to him compared with his close contacts. Liu et al. [25] discussed the increased online weak ties with the emergence of new media platforms and functions such as "follow the post", and "retweet". Mele [21] proposed a network formation model involving indirect connections, which is an extended version of weak tie. ...
... Following the proof of Theorem 1 and 2, we assume users in one community are independent copies of a single player and reduce the game to a two-player game. We define the two-player stochastic game resulting from Protocol 3 as follows: 1) A state of the game, C (t) , representing the acceptance probability at time t. 2) Actions of red player and blue player p 3) One-stage payoffs for red player and blue player which are the same as (25) and (26), except that the fixed C is substituted by the time-variant C (t) ...
... Combining (42,43) for the additional reward, and (23,24) for the expected utility of users in the game without ARM, we can derive the expected utility of users, i.e., the utility of red and blue player, in (25,26). ...
- Rui Luo
- Buddhika Nettasinghe
- Vikram Krishnamurthy
This paper studies controlling segregation in social networks via exogenous incentives. We construct an edge formation game on a directed graph. A user (node) chooses the probability with which it forms an inter- or intra- community edge based on a utility function that reflects the tradeoff between homophily (preference to connect with individuals that belong to the same group) and the preference to obtain an exogenous incentive. Decisions made by the users to connect with each other determine the evolution of the social network. We explore an algorithmic recommendation mechanism where the exogenous incentive in the utility function is based on weak ties which incentivizes users to connect across communities and mitigates the segregation. This setting leads to a submodular game with a unique Nash equilibrium. In numerical simulations, we explore how the proposed model can be useful in controlling segregation and echo chambers in social networks under various settings.
... These studies acknowledge the powerful influence of social contacts influencing outcomes. More specifically, research about network effects has applied the theory to better understand phenomena in social media such as social media metrics (Peters et al., 2013), mediated information flow (Liu et al., 2017) and personal influences (Katona et al., 2011). Peters et al. (2013) utilized network theory in part to develop guidelines for managing social media. ...
... Peters et al. (2013) utilized network theory in part to develop guidelines for managing social media. Liu et al. (2017) explain network effects based on the integration of three other theories including the two-step flow of communication hypothesis, the theory of weak ties and the theory of diffusion of innovations. ...
Purpose This research tests empirically the level of consumer engagement with a product via a nonbrand-controlled platform. The authors explore how social media influencers and traditional celebrities are using products within their own social media Instagram posts and how well their perceived endorsement of that product engages their network of followers. Design/methodology/approach A total of 226,881 posts on Instagram were analyzed using the Inception V3 convolutional neural network (CNN) pre-trained on the ImageNet dataset to identify product placement within the Instagram images of 75 of the world's most important social media influencers. The data were used to empirically test the relationships between influencers, product placement and network engagement and efficiency. Findings Influencers achieved higher network engagement efficiencies than celebrities; however, celebrity reach was important for engagement overall. Specialty influencers, known for their "subject" expertise, achieved better network engagement efficiency for related product categories. The highest level of engagement efficiency was achieved by beauty influencers advocating and promoting cosmetic and beauty products. Practical implications To maximize engagement and return on investment, manufacturers, retailers and brands must ensure a close fit between the product type and category of influencer promoting a product within their social media posts. Originality/value Most research to date has focused on brand-controlled social media accounts. This study focused on traditional celebrities and social media influencers and product placement within their own Instagram posts to extend understanding of the perception of endorsement and subsequent engagement with followers. The authors extend the theory of network effects to reflect the complexity inherent in the context of social media influencers.
... With the globalisation and the rapid technological growth, new technologies can be used to explore new opportunities for the social network theory, facilitating the contact between organisational members and families, for those who accept international assignments (Liu et al., 2017). The use of a social network is of high importance since its lack of support can lead to superior difficulties in adapting to a new culture (Harry, Dodd and Chinyamurindi, 2019). ...
... When forming those social networks, it is important to consider the members and their positions on the hierarchy. Network cohesion moderates the influence of interpersonal networks, but "personal influence grows stronger within more cohesive social networks" (Liu et al., 2017). ...
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![Adriana Gradim]()
The discussion about expatriation movements has great importance for academic researchers and managers of companies in context of globalization making decisions. The purpose of this work is to understand how the success of the expatriation process depends on a multiplicity of factors. The main aim is to develop a new theoretical framework and metrics to be implemented in different organizational and cultural contexts to enrich the literature on SIE's research field. With this model and its future implementation in various contextual settings, it allows the future development of comparative studies of how human resource management has been globally conducted, considering an internal marketing perspective. Moreover, this work provide better understanding of how global mobility is increasing, why and how to distinguish career paths, suggesting how to identify SIEs. In the final note of this work, strictly theoretical and based on the extensive literature review, the idea is that there is a multiplicity of factors that influence expatriates' decision making. Some of them may be identifiable and measurable, others totally unpredictable and random, suggesting a qualitative assessment before a meaningful and representative group of expatriates.
... Website quality theory (WebQual) is one method of measuring website quality developed by Barnes and Vidgen [30]. The size of web quality can be measured using: Accessibility, Currency, Accuracy and Credibility, can also be measured using information quality: Relevancy, Sufficiency, Understandability, Customer service efficiency: Careful, Continuous, Ease of navigation, Content layout, Ease of use [8], [31], [32]. ...
... External Environment Variables, measured by Government policies relating to entrepreneurship, socio-cultural conditions of society and the role of universities and other related institutions [6], [24], [16], [4] Entrepreneurial Orientation variables are measured based on attitude to innovate, proactive attitudes and risk attitudes [16], [34], [6]. Web Quality Variables are measured based on web accessibility, the accuracy of the information, services and Web security [8], [7], [35], [36], [31]. Variable Business Performance is measured based on market development conditions, development of production and the level of efficiency of respondents [5], [37], [38], [39], [40]. ...
... [30] The size of web quality can be measured using: Accessibility, Currency, Accuracy and Credibility, can also be measured using information quality: Relevancy, Sufficiency, Understandability, Customer service efficiency: Careful, Continuous, Ease of navigation, Content layout, Ease of use. [8], [31], [32]. ...
... External Environment Variables, measured by Government policies relating to entrepreneurship, socio-cultural conditions of society and the role of universities and other related institutions [6], [24], [16], [4] Entrepreneurial Orientation variables are measured based on attitude to innovate, proactive attitudes and risk attitudes [16], [34], [6]. Web Quality Variables are measured based on web accessibility, the accuracy of the information, services and Web security [8], [7], [35], [36], [31]. Variable Business Performance is measured based on market development conditions, development of production and the level of efficiency of respondents. ...
... The theory of social networks identifies the role of social relationships in transferring data, directing personal or media power, and supporting attitudinal or behavioral change [1]. Network studies have become highly important in recent years and now are even more predominate in the fight against the COVID-19 pandemic. ...
Social media has had a strong presence in many people's lives over the last decade. In addition, social media platforms have allowed people to share opinions, provide advice on numerous fac-tors, including where to visit, as well as to stay connected and maintain friendships. The hospital-ity and tourism industry, however, can make effective use of these powerful tools for marketing purposes, collaboration and information sharing, and service offerings. Reviewing social media followers' behaviors and interests offers a wealth of information and valuable data for a variety of tourism organizations. This case study focuses on an analysis of the social networks applied to the fortified town of Fredrikstad in Norway. The data used in this research study were collected from the Facebook site of the tourist authority. The results of this research project demonstrate the strengths of applying a social network analysis to a dataset, which can aid in the strategic direc-tion of a tourism destination. The conversations of the greatest interest can successfully be identi-fied as well as the growth of the online network. This paper adds knowledge to the literature through the application of a social network analysis regarding the success of a tourism destina-tion and its future potential.
... For example, social capital theory (Ellison et al., 2011), social network theory (W. Liu et al., 2017), social support theory (Erfani et al., 2016;Maier et al., 2015), persuasion theory (Westerman et al., 2014), social cognitive theory (DeAndrea et al., 2012) and communication theory (Youmans & York, 2012) have been used extensively to explore the positive potential of OSNs. However, our review revealed far less research on these theories and the negative effects of OSNs. ...
- Eila Erfani
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![Babak Abedin]()
Research on online social networks (OSNs) has focused overwhelmingly on their benefits and potential, with their negative effects overlooked. This study builds on the limited existing work on the so-called 'dark side' of using OSNs. The authors conducted a systematic review of selected databases and identified 46 negative effects of using OSNs from the users' perspective, which is a rich spectrum of users' negative experiences. This article then proposed nomenclature and taxonomy for the dark side of using OSNs by grouping these negative effects into six themes: cost of social exchange, cyberbullying, low performance, annoying content, privacy concerns, and security threats. This study then conducted structured interviews with experts to confirm the sense-making and validity of the proposed taxonomy. This study discusses the confirmed taxonomy and outlines directions for future research.
... Từ đây, các nhà nhân học, xã hội học và các nhà khoa học xã hội nổi tiếng khác như Barnes, Mitchell, George Simmel, Jacos Moreno tiếp tục đi sâu tìm hiểu về mạng lưới xã hội. Nhiều thập niên gần đây, các nhà khoa học thuộc nhiều lĩnh vực như kinh tế học, tâm lý học, khoa học hành vi, thậm chí là các lĩnh vực thiên về tự nhiên như thảm họa thiên nhiên, y tế, sinh thái động vật tiếp tục nghiên cứu chuyên sâu, phát triển, bổ sung hệ thống lý thuyết mạng lưới xã hội với các quan điểm đa chiều và liên ngành (Liu et al., 2017). Tuy nhiên, dù có điểm tương đồng hay khác biệt, song về cơ bản, các nhà nghiên cứu tương đối đồng thuận trong quan niệm về mạng lưới xã hội: ...
Sự kết nối trong lớp học là điều hay được nhắc tới trong các nghiên cứu nhưng rất khó tưởng tượng. Liệu tính kết nối có liên hệ gì với kết quả học tập của sinh viên hay là không. Bài báo này thông qua Phân tích Mạng lưới Xã hội đã mô hình hóa và đo lường tính kết nối giữa các thành viên trong lớp học và mối liên quan tới thành tích học tập của họ. Lớp được nghiên cứu ở đây là một lớp ở bậc đại học và kết quả cho thấy các thành viên có sự kết dính khá cao và không có sự phân tán đáng kể. Kết hợp với việc tính toán chỉ số Pearson (r) trong SPSS, nghiên cứu này đã có phát hiện tương đồng với nhiều nghiên cứu của quốc tế đó là độ kết nối, tính trung tâm của một sinh viên không có tương quan với kết quả học tập. Các kết quả từ bài viết không chỉ cung cấp các gợi ý cho công tác tổ chức lớp học và các hoạt động ngoại khóa mà còn gợi mở các hướng nghiên cứu mới trong lĩnh vực giáo dục ở Việt Nam bằng tư duy mạng lưới.
The COVID-19 pandemic has led to disruption of employee well-being; changing the work scenario across the globe. The psychological impact of this pandemic is an undeniable stressor greatly affecting employee well-being across cultures. Social media, in such a time of crisis, can provide the requisite support by filling the emotional, informational and instrumental voids. In order to explain how reactions to the COVID-19 pandemic influences an individual's employee well-being, this study first examines the relationships between pandemic reactions, social media engagement and employee well-being, and then develops a completely mediated model by fully integrating these links. The results, of structural equation modelling analyses conducted for 304 employees from Hospitality (129) and IT/ITeS sector (175) in India, offered strong support for the proposed model. We found that pandemic reactions were indirectly and positively associated with employee well-being; mediated by social media engagement. This study theoretically contributes to the employee well-being literature by revealing how social media engagement completely mediates the relationship between pandemic reactions and employee well-being. The study also offers practical implications by stressing the significant role played by social media engagement in influencing employee well-being in these testing times.
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![Maha Bashri]()
- Nazar Zaki
Alternative media has provided space for the disenfranchised, where counterhegemony and political practice can take place. Social media platforms have allowed for the formation of new communicative space that disrupts power structures and the established flow of information. This has allowed individuals, who share similar values and ideas, to come together in newly formed public spheres. Furthermore, it has allowed for the emergence of a new type of "social" journalist, who can rally and mobilize audiences around issues beyond the confines of the virtual world. The following study is based on a network analysis of Shaun King's mobilization of followers on Twitter (August 11–13, 2017) after the Unite the Right rally in Charlottesville, Virginia.
- Ronald S. Burt
Opinion leaders are more precisely opinion brokers who carry information across the social boundaries between groups. They are not people at the top of things so mulch as people at the edge of things, not leaders within groups so much as brokers between groups. The familiar two-step flow of communication is a compound of two very different network mechanisms: contagion by cohesion tl through opinion leaders gets information into a group, and contagion by equivalence generates adoptions within the group. Opinion leaders as brokers bear a striking resemblance to network entrepreneurs in social capital research. The complementary content of diffusion and social capital research makes the analogy productive. Diffusion research describes how opinion leaders play their role of brokering information between groups, and social capital. research describes the benefits that accrue to brokers.
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![Thomas Valente]()
Social Networks and Health provides a comprehensive introduction to how social networks influence health behaviors. Section one provides an introduction to major research themes and perspectives used to understand how networks form, evolve, and channel the spread of ideas and behaviors. An intellectual history of the field is provided as well as conjectures on why network science took so long to develop. Methodologies for studying networks and assessing personal network data are discussed. Section two covers algorithms and applications of the most common network metrics divided into four chapters: centrality, groups, positions, and network level. For each chapter, descriptions of how the metrics are calculated and how they influence health behavior are presented. Section three reviews applications of social network analysis to health behaviors. The actor-oriented stochastic evolution model is presented first which provides a way to statistically test network evolution properties. Diffusion of innovations models are presented next which describe how networks influence the spread of ideas and practices within and between communities. Network interventions are also presented and a typology describing network interventions and evidence from empirical studies presented. This book enables researchers to understand how network data are collected and processed; and how to calculate appropriate metrics and models used to understand network influences on health behavior. Simple examples and data are presented throughout so researchers can adopt this methodology and perspective in their own investigations. Examples of health behaviors include smoking, substance use, contraception, HIV/AIDS, obesity, and many others.
- Ulrik Brandes
- Jan Hildenbrand
An incredible number of centrality indices has been proposed to date (Todeschini & Consonni, 2009). Four of them, however, can be considered prototypical because they operationalize distinct concepts of centrality and together cover the bulk of analyses and empirical uses: degree, closeness, betweenness, and eigenvector centrality.
- Ronald S. Burt
This is a review of argument and evidence on the connection between social networks and social capital. My summary points are three: (1) Research and theory will better cumulate across studies if we focus on the network mechanisms responsible for social capital effects rather than trying to integrate across metaphors of social capital loosely tied to distant empirical indicators. (2) There is an impressive diversity of empirical evidence showing that social capital is more a function of brokerage across structural holes than closure within a network, but there are contingency factors. (3) The two leading network mechanisms can be brought together in a productive way within a more general model of social capital. Structural holes are the source of value added, but network closure can be essential to realizing the value buried in the holes.
This special issue presents leading-edge work into how the characteristics of social media affect the nature of influence in networks. Our central thesis is that social influence has become networked influence. Influence is networked in two ways: by occurring in social networks and by propagating through online communication networks. We want to understand online social influence in its diversity: who is exercising influence, how it is done, how to measure influence, what its consequences are, and how online and offline influences intertwine in different contexts.
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![Noah Friedkin]()
I examine the relationship between interpersonal power and influence during the resolution of an issue in an organization. Controlling for elementary bases of power (rewards, coercion, authority, identification, and expertise), I investigate three bases of power that arise from the structure of social networks (cohesion, similarity, and centrality). An analysis of longitudinal data on actors' bases of social power, frequency of interpersonal communications, and interpersonal influences indicates that cohesion, similarity, and centrality have significant effects on issue-related influence net of the elementary power bases. The effects of the structural bases are mediated by the frequency of issue-related communication. The primary structural determinant of the frequency of issue-related communication is network cohesion.
Social Network Theory Public Health Definition
Source: https://www.researchgate.net/publication/316250457_Social_Network_Theory#:~:text=Social%20network%20theory%20focuses%20on,enabling%20attitudinal%20or%20behavioral%20change.
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