Using social network analysis to explain communicationcharacteristics of travel-related electronic word-of-mouth on social networking sites Qiuju Luoa,b,*, Dixi Zhonga,b,1 a School of To
Trang 1Using social network analysis to explain communication
characteristics of travel-related electronic word-of-mouth on social
networking sites
Qiuju Luoa,b,*, Dixi Zhonga,b,1
a School of Tourism Management, Sun Yat-sen University, Building 329, 135 Xingangxi Road, Guangzhou 510275, PR China
b Center for Tourism Planning and Research, Sun Yat-sen University, Building 329, 135 Xingangxi Road, Guangzhou 510275, PR China
h i g h l i g h t s
We viewed eWOM communication on SNSs as a network based on social relationships
We examined social ties and network structure with social network analysis
Travel-related eWOM communication relies on strong, middling, or weak social ties
The communication is structured, loose-knit, flat, and of high centrality
Travel-related eWOM on SNSs tends to be dominated by travel interests
a r t i c l e i n f o
Article history:
Received 26 February 2013
Accepted 7 July 2014
Available online 26 July 2014
Keywords:
Travel-related electronic word-of-mouth
Communication characteristics
Social networking sites
Social network analysis
Ego network
Whole network
a b s t r a c t Social networking sites (SNSs), which are platforms based on user interactions, currently play increas-ingly important roles in sharing electronic word-of-mouth (eWOM) among tourists Viewing eWOM communication on SNSs as a network based on the users' social relationships, this study applied social network analysis to examine the communication characteristics of travel-related eWOM on SNSs from the perspective of both ego and whole networks Results show that travel-related eWOM communication via SNSs relied on existing social relationships, ties of which can be categorized as strong, of middling strength, or weak Furthermore, the effect of transmitted information was stronger than that of influ-ential decision-making The communication network studied was found to be structured, loose-knit,flat, and of high centrality These results enrich current research on the effects of eWOM and provide a dy-namic perspective for understanding how eWOM disseminates and influences users through interactions
© 2014 Elsevier Ltd All rights reserved
1 Introduction
A significant symbol of Web 2.0, the boom in social networking
sites (SNSs) has also aroused a worldwide upsurge in tourism
destination marketing With SNSs, a great deal of tourists post and
share real-time feelings (Gretzel, 2006; Pan, MacLaurin,& Crotts,
2007), as well as travel reviews, opinions, and personal
experi-ences while traveling (Xiang & Gretzel, 2010) In particular,
individuals younger than 35 years old with at least a college degree chiefly participate in sharing travel experiences and photos on SNSs (Lo, McKercher, Lo, Cheung, & Law, 2011) Given the general popularity of sharing photos on SNSs, photos depicting travel have especially become a way of self-expression and self-image con-struction among younger generations (Lo et al., 2011) As mobile Internet capabilities progress, users more often share travel infor-mation whenever and wherever possible, which makes sharing via SNSs increasingly prevalent In fact, travel information provided by SNSs has quickly become commonplace in the day-to-day lives of SNS users
SNSs such as Facebook, Twitter, Myspace, and Microblog are platforms with dynamic, multimodal features by which users can post, share, and discuss interests with other interested users (Jansen, Zhang, Sobel,& Chowdury, 2009) These features of SNSs
* Corresponding author School of Tourism Management, Sun Yat-sen University,
Building 329, 135 Xingangxi Road, Guangzhou 510275, PR China Tel.: þ86 20
84112735/13450357112.
E-mail addresses: bettyluoqiuju@126.com (Q Luo), dreamy_cecilia@foxmail.com
(D Zhong).
1 Tel.: þ86 18011718710.
Contents lists available atScienceDirect Tourism Management
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0261-5177/© 2014 Elsevier Ltd All rights reserved.
Tourism Management 46 (2015) 274e282
Trang 2expand users' social circles as well as increase the frequency of
interpersonal contact Unlike traffic on other websites, users more
often form close-knit relationships with each other (Ding& Wang,
2010) Given the strength of these ties, SNSs have transformed
traditional information dissemination that relies on central mass
media (e.g., newspaper and television) With the popularity of SNSs
and general Internet use, a dual-core dumbbell structure of online
information dissemination has emerged that includes both
main-stream forums and microblogs as well as mainmain-stream portals,
which as the two core sources of influence have transformed how
peer-to-peer influence works (Li, 2011) In terms of consumption,
consumers are no longer passive recipients of information; instead,
they actively engage in peer-to-peer product recommendations and
electronic word-of-mouth (eWOM) (Chu& Kim, 2011) eWOM
of-fers a useful perspective from which to study information
dissemination and its influence on users and followers Since the
development of Web 2.0, traditional word-of-mouth (WOM) has
had to accommodate eWOM (Chatterjee, 2001; Hennig-Thurau,
Gwinner, Walsh,& Gremler, 2004), which by comparison is more
influential due to its speed, convenience, broadcast appeal, and lack
of the pressures of face-to-face interaction (Sun, Youn, Wu, &
Kuntaraporn, 2006) Another aspect of such influence is that any
communication and contact between communicators and receivers
might alter the recipient's attitude, especially regarding purchase
decisions (Cheung, Lee,& Thadani, 2009; Kiecker & Cowles, 2002;
Park& Kim, 2008; Park & Lee, 2008)
Likewise, travel-related eWOM on SNSs may significantly affect
the cognition and behavior of potential tourists Tourism is an
experiential good; consumers cannot perceive the quality of
tourism products in advance Therefore, interpersonal
communi-cations have become an important technique to reducing the risks
of travel (Murray, 1991).Litvin, Goldsmith, and Pan (2008)point out
that interpersonal influence and WOM were ranked the most
important sources of information for purchase decisions Partly as a
result,Chu and Kim (2011)suggest that product-focused eWOM on
SNSs is a unique phenomenon with important social implications
Therefore, the characteristics of communication via eWOM on SNSs
requires more sustained attention, particularly from the
perspec-tive of network structure and social relationships, which allows a
more thorough examination of how interpersonal influence can
spread among users and followers (Chu & Kim, 2011) From this
perspective, studying the communication characteristics of
travel-related eWOM on SNSs can expand the present understanding of
eWOM's influence, especially as it pertains to tourists and the
tourism industry
Currently, SNS regarding tourism has received scant scholarly
attention Most research exploring the function of SNSs for locating
tourism information, as well as users' motivations and behavior,
has neglected to investigate communication among users By
contrast, eWOM communication and how it affects consumers'
purchase decisions has gradually attracted the attention of
re-searchers (Jansen et al., 2009; Lee & Youn, 2009; Riegner, 2007)
Current research is conducted from three perspectivesdnamely,
those of the communicator, the receiver, and the communication
process Although studies on the communication process are well
outnumbered by those on communicators and receivers, recent
research has begun to study the social characteristics of eWOM
communication Nevertheless, most studies thus far have
consid-ered consumers to be independent individuals and have thus
emphasized the effects of eWOM on online purchase
decision-making, while research on eWOM via SNSs remains in its infancy
In the meantime, eWOM communication in those studies is static,
for few have conducted their research from a dynamic perspective
and considered communication as a dynamic dissemination
pro-cess Therefore, this study focuses on the communication of
travel-related eWOM on SNSs to underscore its practical and academic significance
To these ends, this study performed social network analysis (SNA) to examine the communication characteristics of travel-related eWOM on SNSs from the perspective of social ties and network structure Its results not only enrich the existing theoretical research, but also provide further inspiration for conducting effec-tive word-of-mouth marketing on SNSs in the tourism industry
2 Literature review 2.1 SNS research in tourism Most research on SNSs has been published since 2008 and pri-marily emphasized user motives and behaviors Among SNS research, the few travel-related studies can be grouped into two categories On the one hand, most studies have considered SNSs to
be one kind of social media in terms of their use for travel-related information searches Using Google as a search engine,Xiang and Gretzel (2010) investigated the role of social media in online searches for travel-related information The results showed that SNSs were not yet the main sources for users seeking travel-related information Meanwhile, other research has suggested that user trust of travel websites varies significantly; the three types considered most trustworthy were official websites of tourism bureaus, websites of travel agencies, and third-party websites (Burgess, Sellitto, Cox,& Buultjens, 2011; Yoo, Lee, & Gretzel, 2009) Though trust of SNSs was lower than expected and SNSs are far from the most popular way to gather travel-related information, the reasons for both conditions have gone unaddressed in these studies Furthermore, rapid changes that occur as mobile Internet become popularized may have altered the conditions in recent years
On the other hand, tourism studies have also focused on the use
of SNSs in terms of user characteristics and motivations for sharing Current studies in this category remain in the descriptive stage.Lo
et al (2011) found that most people sharing travel photos were young and well-educated, as well as had substantial incomes, rich travel experiences, and a willingness to involve themselves in the destination Huang, Basu, and Hsu (2010) identified three func-tional motives for sharing travel-related information via SNSsdnamely, obtaining travel information, disseminating infor-mation, and documenting personal experiencesdand that of these motives, obtaining travel information was the most important Both studies described nevertheless failed to present the characteristics
of the social networkdnamely, the effect of social features on tourists
In sum, research of SNSs in tourism remains in its infancy Though earlier studies explored the function of SNSs for locating travel information, most neglected to investigate the communica-tion process, for few conducted their research from a dynamic perspective If substantial characteristics of SNSs have been over-looked, such oversight precludes further understanding of the acquisition and impact of travel information At the same time, since few studies viewed online travel-related information as eWOM, we have viewed travel-related information as such and, moreover, sought to provide a dynamic perspective for under-standing how eWOM disseminates information and influences users
2.2 Communication research on eWOM Current research on eWOM is conducted from three perspecti-vesdnamely, those of the communicator, the receiver, and the communication process
Q Luo, D Zhong / Tourism Management 46 (2015) 274e282
Trang 3Research conducted from the perspective of the communicator
emphasizes the motives for eWOM communication In this strain of
the literature,Hennig-Thurau et al (2004)identified eight motives
for sharing product reviews, including social benefits and the need
for advice These results also suggest that social relationships
among users cannot be ignored in eWOM studies
The perspective of the receiver has drawn the most scholarly
attention In this strain, relevant research has primarily discussed
the effect of eWOM on the receiver in two aspects: the receiver's
attitude and the receiver's willingness to purchase
Regarding the effect of eWOM on the receiver's attitude, various
factors influence receivers' adoption of eWOM, including both the
features of eWOM and of receivers The features of eWOM include
quantity of eWOM (Doh & Hwang, 2009), source characteristics
(e.g., its reliability, objectivity, and expertise), information
charac-teristics (e.g., its general allure, completeness, accuracy, and
time-liness) (Chen & Zhang, 2008), relevance, and completeness
(Cheung, Lee, & Rabjohn, 2008) In particular, the usefulness of
information is a mediator that influences eWOM adoption (Cheung
et al., 2008) At the same time, the features of the receiver include
involvement and prior knowledge, both of which variously affect
the recipient's attitude (Doh& Hwang, 2009)
By comparison, studies on the effect of eWOM in purchase
de-cisions are more diverse, for scholars have conducted research on a
variety of influential factors.Park and Kim (2008)concluded that
benefit-centric eWOM has a greater influence on the willingness to
purchase for consumers who lack expertise, while attribute-centric
eWOM exerts a greater influence on consumers with professional
knowledge of the product.Poyry, Parvinen, Salo, and Blakaj (2012)
showed that, compared to utilitarian information searches, hedonic
information searches significantly improve the consumers'
perception of eWOM's usefulness and shortens the
decision-to-purchase time Though it is clear that SNSs prefer hedonic
infor-mation searches, whether there is any perceptible influence on
tourists' decision-making requires further exploration De Bruyn
and Lilien (2008) developed a multi-stage model to identify the
role of eWOM plays during each stage of recipients'
decision-making process
Compared to the perspectives of the communicator and
receiver, the perspective of the communication process has
received scant scholarly attention, though recent research has
begun to study the social characteristics of eWOM communication
On one hand, social relationships between consumers come into
notice Among studies of eWOM,Chu and Choi (2011)have
evalu-ated the effects of social relationships between consumers'
pur-chase decisions on SNSs Their results suggest that Chinese users
communicate most and most trustfully with users with whom they
have strong social relationships, thus the social capital of a
pre-existing social relationship plays a significant role in Chinese
users' eWOM communication By contrast, Americans interact
more with extended social circles or with other users with whom
they have no social relationship.Chu and Kim (2011)developed and
tested a conceptual framework that identifies tie strength,
homo-phily, trust, normative and informational interpersonal influence as
an important antecedent to eWOM behavior in SNSs, and tie
strength is positively associated with eWOM behavior As might be
expected, several researchers have suggested that WOM
commu-nication has relied on social relationships and that consumers were
inclined to trust acquaintances and people with whom they
maintained strong social ties (Brown & Reingen, 1987), family
members, and friends (Jansen et al., 2009) In the era of Web 2.0,
social interaction on SNSs determined by social relationships
con-tinues to merit in-depth investigation
On the other hand, some researchers studying the features of
eWOM communication networks have produced results indicating
that eWOM communication networks are structured instead of random Among these researchers, Vilpponen, Winter, and Sundqvist (2006) conducted a case study of communication on personal websites that used a downloadable banner to show resistance to a proposed copyright law in Finland Using SNA,
Vilpponen et al (2006)concluded that eWOM communication can
be characterized as a loose-knit network of high centralization and cliques In another study, by modeling an eWOM communication network on multi-agent simulation,Jiang (2009) found that the structure of any eWOM communication network influences both the scale and efficiency of communication
Altogether, current research on eWOM regarding the commu-nication process remains insufficient On the one hand, since re-searchers viewed users as independent individuals, most research failed to consider the relationships among users and the pathways
of communication most taken by users seeking to share and ex-change information On the other hand, few studies address eWOM communication on SNSs Certain features of SNSsdstrong inter-activity and timeliness, to name twodare likely to distinguish SNSs from general websites Our study has thus aimed to provide in-depth research on travel-related eWOM communication via SNSs from the aspect of user interaction
3 Research design
In all social communication processes, at least two individuals are needed to form an information-sharing relationship in order to share information symbols (Schramm& Porter, 2010) In this sense, the process of information exchange should not be viewed as a specific behavior (i.e., A acts upon B) but as information sharing that leads to a common understanding (Schramm& Porter, 2010) SNA views the social structure as an interpersonal network that emphasizes interpersonal relationships, the content of the re-lationships, and the interpretation of social phenomena within the structure of a social network (Luo, 2010) A social network is a collection of social actors and the relationships among them (Liu,
2009) Consequently, each node in the network represents one actor, which can be a social unit or entity, and each link represents the relationship between the actors SNA emphasizes three network levels: ego, partial, and whole During the past 30 years, SNA has been applied to many studies in sociology, organizational behavior, and social relationships More recently, SNA has been increasingly applied to social media-based communication research
This study applied SNA to answer research questions from the perspective of each single relationship and then extended that perspective to the whole network In short, this study concerns two aspects, one is the features of social ties of each communication pathway, and the other is the structural features of a travel-related eWOM communication network To do so, we applied ego-network analysis to examine social ties as well as whole-network analysis to measure the structure of travel-related eWOM communication network (Fig 1)
The interaction between users on SNSs can be silent (i.e., not directly observable) or visible (Pempek, Yermolayeva,& Calvert,
2009) Since silent contact is difficult to assess, the present anal-ysis was conducted based on visible contact Visible interactive behavior between users, including their comments and forwarding comments, represents the completion of information dissemination
3.1 Ego-network analysis From the perspective of social ties, ego-network analysis was used to analyze the strength of social ties between the
Q Luo, D Zhong / Tourism Management 46 (2015) 274e282
Trang 4communicator and the receiver in travel-related eWOM
commu-nication An ego network refers to any network consisting of an
individual and other users directly connected to him or her; it is
used to interpret the relationship features between the
commu-nicator and receiver in travel-related eWOM
In this study, data were collected by questionnaire A
nomina-tion method was used to identifyfive users who had made
travel-related eWOM communication with respondents during a period of
six months (October 2011eApril 2012) After the ego network was
constructed, a nomination interpretation method was used to
describe and measure each communication relationship The
questionnaire design was based on the standard ego-network
questionnaire exhibiting high reliability used in general social
surveys in the U.S formulated byBurt (1984), which uses three
constructs to interpret questionnaire data: contact duration,
con-tact frequency, and intimacy (Granovetter, 1973) The questionnaire
used in this study was revised based on local research conducted by
Luo and Xie (2008), added a construct (i.e.,“relationship between
close circles of friends”), and adjusted the range of years of each
item for the construct of contact duration, as well as the measures
and contents of the items in the construct of intimacy Additionally,
we added travel-related questions to explore respondents' tourism
preferences, common travel experiences, and reciprocal behaviors
in travel-related eWOM Five undergraduate students from
different universities were recruited to take the pilot test, after
which the questionnaire was adjusted accordingly
The questionnaire was distributed from April 1e8, 2012 to
high-frequency users of SNSs in Guangdong, China Users were mostly
office workers and college studentsdsome foreign exchange
stu-dentsdselected based on three considerations First, the sample
originated from the primary group of SNS users in China, which is
representative of China Second, the questionnaire design was new
and informative and thus required respondents with adept
comprehension skills and patience Third, active SNS users (i.e.,
those who log in more than two or three times per week) may have
various travel-related eWOM communication behaviors To ensure
a high reliability of questionnaire results, we distributed the
questionnaires to each participant one at a time
In this study, an ego network consisted of each respondent and
up tofive of his or her nominated contacts of travel-related eWOM
Each network was a sample set, in which the respondent served as
the core, while each communication relationship directly
con-nected to the respondent formed an independent sample In total,
64 questionnaires were collected; those of participants whose SNS
use frequency was less than two or three times per week or who
could not provide a complete dataset of at least one nominated
contact were excluded Altogether, 61 questionnaires (95.3%) were
deemed valid A total of 303 (97.7%) independent samples was
obtained, of which 289 were deemed valid; 14 samples with missing values were excluded
The profile of respondents is shown inTable 1 The sample sets generally represented the typical SNS user
3.2 Whole-network analysis Whole-network analysis examines the network structure of eWOM communication For this study, a representative microblog was selected as a sample This study only focused on the network characteristics of travel-related eWOM in a single circle of micro-blogging relationships instead of multiple circles With whole-network analysis, the study aimed to develop a directional adja-cency matrix to analyze travel-related eWOM communication The whole network refers to all relationships among all group members
Fig 1 Research framework.
Table 1 Profile of respondents (n ¼ 61).
Demographic characteristic n Percent Gender
Age
Highest level of education achieved Junior high school 0 0.0 High school or technical secondary school 4 6.6 University or college 55 90.2
Travel frequency within a year More than twice 47 77.0
Occupation Governmental agencies or institutions 4 6.6 Corporations or enterprises in the service industry 6 9.8 Individual industrialists and businessman 0 0.0 Researchers and teachers 0 0.0
SNS use frequency
Two or three times weekly 8 13.1
Q Luo, D Zhong / Tourism Management 46 (2015) 274e282
Trang 5(Liu, 2009) Network density, graph centralization, centrality, and
subgroup analysis were four important measurements used to
explore the network cohesion, integration, role and position, and
composition and structure of the travel-related eWOM
communi-cation network
The sample microblog originated on Sina Microblog, the most
popular microblogging platform in China Users on Sina Microblog
can be classified into two types: authenticated and ordinary users
An authenticated user must be a well-knownfigure in a particular
field with an authentication icon highlighted Since there are no
identity constraints on ordinary users, they form the major group
and account for a larger percentage of users To understand the
communication structure of ordinary users was therefore more
remarkable for destination marketing regarding SNSs In this study
ordinary bloggers were used as subjects for whole-network
anal-ysis; the microblog account of user Gaoli_Ivy provided data Factors
such as the quantity of travel-related microblogs and the degree of
interaction were considered during the sample selection to ensure
a sufficient amount of data The selected blogger loved traveling
and on average traveled threeefive times per year, including one or
two long-distance journeys After registering as a user in
September 2010, from September to December 2011 she posted a
total of 92 travel-related messages, each of which addressed topics
such as travel experiences, air travel, accommodation deals, and
recommendations for travel destinations The blogger followed a
total of 120 blogging friends and was followed by 227 users (March
26th, 2012)
Data from September to December 2011 were collected, which
consisted of all travel-related microblogging contacts followed by
the blogger and her followers The research dates included two
public holidays in Chinadnamely, the Mid-Autumn Festival and
National Daydto ensure data adequacy The blogger was asked to
review her use history in order to organize her travel microblogs
and microblog accounts she had commented on from September to
December 2011 During the same period, we read travel-related
microblogs in order to construct a travel-related eWOM
commu-nication pathway for other users
A case-by-case adjacency matrix was constructed for
whole-network analysis, for which each node represented an
indepen-dent microblog user The communication relationships between
the nodes indicating travel-related eWOM communication
behav-iors, which included forwarding or commenting on travel-related
microblogs, were represented by directional links The data were
screened, and inactive users with fewer than 50 followers were
excluded A 155 155 adjacency matrix was eventually constructed
for data analysis
UCINET 6 statistical analysis software was used for
whole-network analysis
4 Results
4.1 Ego networks
4.1.1 Results of tourist behavior
Regarding travel as a hobby, 75.6% of contacts enjoyed travel,
21.9% neither particularly enjoyed nor disliked travel, and 2.5% did
not enjoy travel In terms of common travel experience, 39.4% of
contacts had traveled with respondents in the previous year
Because the frequency of travel was less than the frequency of daily
entertainment activities, 39.4% can be considered a large
percent-age Finally, regarding the sharing of travel information, 53.0% of
contacts shared travel information with respondents Citing other
users or sending private messages were two ways they had shared
travel-related eWOM and can thus be viewed as
individual-to-individual eWOM communication Information sharing was a
form of reciprocal behavior between the respondents and contacts These results suggest that users who enjoyed travel or had common travel experience with communicators were more likely to have visible contact and more inclined to travel-related eWOM communication (Table 2)
4.1.2 Results of social ties Three constructsdnamely, contact duration, contact frequency, and intimacydwere used to measure the strength of travel-related eWOM communication ties on SNSs To distinguish communication relationships by strength of social ties, a k-means analysis was conducted for 289 pairs of contact relationships We conducted two-, three-, and four-category clustering analyses to better inter-pret and categorize the samples and finally selected a three-category analysis since it best explained the differences
Variance analysis of the cluster results showed that all indicators from the three clusters were significantly different, which was consistent with the required statistical significance Results of cluster analysis are shown inTable 3 The cluster characteristics of travel-related eWOM communication relationships included the following:
Category I: Strong social ties A total of 90 relationships (31.1%) fell into this category, the most significant characteristic of which was a high average of thefive indicators Average contact frequency in these relationships occurred more than two or three times weekly, while the average contact duration was threeeten years The topics and behaviors of communication were intimate and diverse, and on average, a small group of familiar and common friends was shared among the re-spondents and their contacts Of the contacts, 77.8% shared travel-related eWOM by citing other users and sending private messages to and from the respondents with strong reciprocity Category II: Social ties of middling strength Compared to Category
I, slightly fewer relationships (n¼ 78, 27.0%) were considered to have ties of middling strength Average contact frequency for this category was once or twice per week; contact duration was slightly shorter than that of the contacts with strong social ties; the topics and behaviors of communication were more general; and the degree of overlap between the circles of close friends among contacts was slightly lower than of that of contacts with strong social ties In this category, 51.3% of contacts were reciprocal subjects of travel-related eWOM from the re-spondents Based on the indicators, members of this category of communication relationship were determined to have social ties
of middling strength
Category III: Weak social ties Given their low scores for each item, most relationships (n¼ 121, 41.9%) belonged to the cate-gory encompassing contacts with weak social ties Contact fre-quency within the sample was as little as oneethree times monthly, while the average contact duration was from one to three years and the intimacy of topics and behaviors was extremely low Furthermore, the degree of overlap between
Table 2 Analytical results of travel behaviors of travel-related eWOM receivers.
Analysis of travel behavior n Percent Contact enjoys travel Yes 211 75.6
Neutral 61 21.9
Contact traveled with respondent
in the previous year
Yes 113 39.4
No 174 60.6 Would share online travel information
with respondent
Yes 151 53.0
No 134 47.0
Q Luo, D Zhong / Tourism Management 46 (2015) 274e282
Trang 6close circles of friends was low; most individuals in these
re-lationships did not have contacts in common Above all, since
social contact in this category was sporadic, these relationships
were determined to have weak social ties The social tie strength
was comparable to that of general colleagues and classmates,
neither of whom share much contact
In an empirical study,Marsden and Campbell (1984)showed
that the degree of intimacy is the best indicator to measure the
strength of social relationships In this study, the degree of intimacy
(i.e., the intimacy of topics and behavior indicators) was the
pri-mary index for distinguishing social tie strength More recently,
Petroczi, Nepusz, and Bazso (2010)categorized virtual social
re-lationships, which guided the definition of the strong social ties
category in this paper, which exhibited intimate friendship since
contacts were familiar with and supported each another (e.g., by
offering suggestions, sympathizing, and giving spiritual support)
By contrast, the categories of middling and weak social ties were
characterized the relationships of acquaintance, in which contacts
only knew one another in passing or were friends The contacts
with middling and weak social ties might share interests, hobbies,
and exchanged messages in private
4.2 The whole network
The 155 155 directional multi-value matrix constructed from
the data of 155 users was screened and coded From the subsequent
analysis we excluded 100 users who had no visible communication
of travel-related content with any other users in their social circles
from September to December 2011 in order to examine the
char-acteristics of travel-related eWOM communication without the
interference of the data of users who had not participated in
rele-vant communication A 55 55 matrix of travel-related eWOM
communication was constructed, in which each node was coded in
sequential order (AA, AB,…; BA, BB, …; CA, CB, …)
Fig 2 shows the general pathways and active members in a
travel-related eWOM communication process The contacts
be-tween users represented by the following nodes in the red circle
were more frequent and dense: AJ, BH, BM, CD, CF, CM, CO, CQ, CR,
CW, and DJ, as well as pairs AA and AI, DJ and BI, and CQ and CO
4.2.1 Network density
Network density is a measure of network cohesion (Webster&
Morrison, 2004) In this sense, density signifies the ratio of the
actual number of links versus the maximum number of links
possible in the network (0e1)
To measure network density, the multi-value matrix was
con-verted into a two-value matrix using UCINET 6 Nodes with
infor-mation dissemination behavior between them were assigned
values of one whether the information dissemination went both
ways or not By processing the 55 55 directional two-value matrix
in UCINET 6, sample network had a total of 105 ties of eWOM communication, which meant that network density was 0.0354 When density was measured among the groups with frequent contacts (represented by the red circle inFig 2), density increased
to 0.1703, which was nevertheless quite low
The results above show that in most instances, the travel-related eWOM contact network on an SNS was loose-knit instead of densely connected This result was significantly affected by the fact that not all contacts in eWOM communication had a connection with one another
4.2.2 Graph centralization Graph centralization measures the overall cohesion or integra-tion of a network and describes the extent to which such cohesion was organized around particular nodes (Scott, 2007) Regarding the degree of centrality of graph centralization, the outdegree centralization of the sample network was 73.73%, while the inde-gree was 20.92% The betweenness centrality of the graph centralization was low (24.41%)
A high degree of centrality of outward communication indicates that the level of information integration was high Any node with high centrality, which indicates that the person has more travel-related interaction with others, had a large effect in the network
By contrast, as the degree centrality of the eWOM-receiving network diminished, the receiving pathways became more diverse Low betweenness centrality of the graph centralization suggests a low level of distortion, which indicates fast and effective eWOM communication
4.2.3 Centrality analysis Centrality is an indicator of an individual's structural position that assesses the importance of the individual in the network (Luo,
Table 3
Clustering analysis results.
Category I: Strong social ties Category II: Social ties of middling strength Category III: Weak social ties
Contact frequency 4.01 1.13 3.38 1.30 2.63 1.34
Contact duration 3.98 0.80 3.86 0.80 3.11 1.02
Intimacy of communication 14.42 5.16 11.10 4.35 3.23 3.22
Intimacy of behavior 26.93 3.03 15.08 4.48 2.63 2.84
Relationship between close circles of friends 3.21 0.63 3.06 0.67 2.61 1.06
Note Score for indicators ranged from 1 to 5 points for contact frequency, 0 to 5 points for contact duration, 1 to 22 points for intimacy of communication, 1 to 31 points for intimacy of behavior, and 1 to 4 points for a close circle of friends; SD ¼ standard deviation.
Q Luo, D Zhong / Tourism Management 46 (2015) 274e282
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actors in the diagram by focusing on each node in the network
There are three centrality indexes: degree, closeness, and
betweenness (Scott, 2007) The higher the degree centrality index,
the more actors the user has contact within the network, thus the
more unofficial power and greater effect the individual exerts in the
network By contrast, users with high betweenness centrality
occupy the central position of contact between two members in the
network The more opportunities this user has to guide resources,
the more critical the position he or she occupies in theflow of
resources
Regarding outdegree centrality, AA was the main core in the
network, with a standard outdegree centrality of 75.93, followed by
AJ (24.07) and CQ (18.52) The standard outdegree centrality of
more than 33 actors was zero The results suggest that the sample
network had a structure dominated by one core surrounded by
several secondary cores Because the sample network was the
extended microblog network of AA, the attributes of AA did not
have a reference value Among the 10 individuals with the highest
outdegree centrality (excluding AA), AJ, CQ, DJ, BI, and CR were all
travel lovers,2whereas DL, DO, and DM were the official microblogs
of AirAsia, Asiago, and Qyer.com, respectively CP and BP traveled
frequently on business (i.e., approximately twice every six months)
Regarding indegree centrality, the standard indegree centrality
of three nodes was high; AA was the highest (24.07) The standard
indegree centrality of CQ, CF, and CO was 9.26 and then<8 for the
remaining nodes The receivers of eWOM were relatively evenly
distributed and not centralized, which suggests that travel-related
eWOM attracted attention from a relatively large number of users,
not only a few actors The sample network formed a network
structure of dispersed receiving (Table 4)
The betweenness centrality of only 12 nodes in the network was
greater than zero AA occupied the central position, with a standard
betweenness centrality of 24.60, followed by CQ and AJ AA
occu-pied the center of the network and had a great effect on the
thoughts of the other actors in the online social circles Except for
these three nodes, the betweenness centrality of the remaining
tourists was low, and many tourists were marginal (Table 5)
4.2.4 Subgroup analysis
Subgroup analysis examines the group characteristics of
cohe-sion in the network by analyzing the substructures of the whole
network Generally, a subgroup refers to a coalition of many
contacts who share a goal and have many stable contacts with each another From the perspective of social psychology, an individual is
an actor in the group and subjected to the concepts, influences, norms, and values of the group (Liu, 2009) Therefore, it was important to investigate whether there was a subgroup in the travel-related eWOM communication network in order to under-stand how eWOM further affects receivers
A component analysis was conducted on the 55 55 directional two-value matrix and revealed a strong component composed of 14 nodes (AA, AI, AJ, BI, CB, CM, CP, CQ, CR, CW, DJ, DL, DM, and DO) A strong component refers to a component in which the connection direction is considered
In the subgroup of 14 nodes, AI, AJ, BI, CM, CQ, CR, CW, and DJ were travel lovers, while DL, DM, and DO were the official micro-blogs of three travel websites The subgroup members shared an interest in travel and were therefore more likely to form a close-knit subgroup in the travel-related eWOM communication network
A k-core collapse sequence analysis was also conducted to analyze whether the sample network on SNSs was structured The index analyzes the similarities in relationships and structure be-tween the component and other nodes of the sample Results show that the core collapse sequence was 0, 0, 0.44, 0.71, and 0.89 The core collapse sequence is thus gradual as k increases from zero, which suggests that the communication and contact in the travel-related eWOM network was not random but structured (Table 6)
5 Discussion and conclusions
As an early empirical attempt to understand the characteristics
of travel-related eWOM communication on SNSs, this study examined the social ties and social network structure with SNA It thus offered a new perspective for better understanding how eWOM disseminates and influences within user interactions
In ego-network analysis, we examined the social relationship variables among users in travel-related eWOM communication on SNSs We specifically examined tie strength as a potential predictor
of interpersonal influence in eWOM communication In whole-network analysis, we also examined the whole-network structure of travel-related eWOM communication
Our resultsfirst show that travel-related eWOM communication via SNSs relied on existing social relationships, which can be categorized into three groups: having strong social ties, social ties
of middling strength, or weak social ties Only 0.7% relationships were newly established between respondents and contacts 1.7% relationships had been established for six monthseone year SNSs stood apart from other social media in encouraging their users with existing social relationship to interact online, which underscores its academic significance Relationships with weak social ties formed
Table 4
The output of the centrality.
N SOC SIC N SOC SIC N SOC SIC N SOC SIC
AA 75.93 24.07 CF 1.85 9.26 BX 0 3.70 CU 0 3.70
AJ 24.07 5.56 BK 1.85 0 AF 0 1.85 AV 0 1.85
CQ 18.52 9.26 CW 1.85 1.85 AE 0 5.56 BA 0 1.85
CP 12.96 1.85 CM 1.85 1.85 CD 0 7.41 DB 0 1.85
DJ 9.26 5.56 CV 1.85 3.70 BZ 0 1.85 DD 0 1.85
DL 7.41 1.85 AC 1.85 3.70 CG 0 3.70 CH 0 5.56
BI 5.56 5.56 DP 1.85 0 BM 0 3.70 DF 0 1.85
BP 5.56 1.85 AI 1.85 5.56 CK 0 1.85 DI 0 1.85
DO 5.56 1.85 BH 0 3.70 AL 0 1.85 BO 0 1.85
CR 3.70 1.85 AT 0 5.56 CN 0 1.85 CO 0 9.26
DM 3.70 1.85 BN 0 1.85 AG 0 5.56 BQ 0 1.85
DE 3.70 0 AN 0 1.85 AO 0 1.85 BV 0 3.70
CB 1.85 1.85 AH 0 1.85 AR 0 1.85 BW 0 3.70
AK 1.85 1.85 AB 0 3.70 AS 0 1.85
Note N ¼ nodes; SOC ¼ standard outdegree centrality; SIC ¼ standard indegree
centrality.
Table 5 The output of betweeness centrality.
N BC SBC N BC SBC N BC SBC N BC SBC
AA 704.17 24.60 DJ 38.00 1.33 BI 9.00 0.31 DO 1.50 0.05
CQ 125.83 4.40 BP 17.00 0.60 AC 8.33 0.29 CP 0.50 0.02
AJ 77.67 2.71 AI 16.50 0.58 CF 5 0.18 DM 0.50 0.02 Note N ¼ nodes; BC ¼ betweeness centrality; SBC ¼ standard betweeness centrality.
Table 6 The output of the k-core collapse sequence analysis.
k k-remainder k-remainder percentage
2 According to an interview with blogger AA Authors listed users who had
Q Luo, D Zhong / Tourism Management 46 (2015) 274e282
Trang 8the largest category, while the other two categories were similar in
size Contacts in relationships with strong, middling, or weak social
ties played different roles in communications with information
receivers (Granovetter, 1973); effects on the promotion and
opti-mization of social learning therefore also differed This conclusion
confirms the results of Chu and Choi (2011), who reported that
Chinese users were more likely to contact familiar users on SNSs
instead of expanding their existing social relationships In the
present study, we further segmented tie strength to better
under-stand the characteristics of eWOM communication and its effects
Secondly, concerning its effect of communication, results reveal
that eWOM can transmit information and influence
decision-making, though the effect of the former was stronger than that of
the latter Travel-related eWOM on SNSs could overcome
spatio-temporal limitations and spread to all corners of the social network
Furthermore, eWOM also affected the attitudes and
decision-making of contacts with strong social ties, since strong social ties
were conducive to influencing others and building trust, whereas
weak social ties were conducive to transferring knowledge and
information The fact that relationships with strong social ties
occupied the smallest category suggests that travel-related eWOM
plays a more important role in knowledge and information
dissemination Moreover, network density was low for
travel-related eWOM communication; the travel microblog did not
inspire frequent contact among tourists, which weakened eWOM's
influence Characteristics of social relationships have been indexed
to reflect how eWOM works among tourists In this study, the
ef-fects of eWOM were divided into two kinds: eWOM transmission
and influence Compared to studies of trust of eWOM on SNSs
(Burgess et al., 2011; Yoo et al., 2009), the present study offers a
new perspective for examining the extent of eWOM's influence,
though this perspective nevertheless requires further study
Thirdly, we found the communication of travel-related eWOM on
SNSs to be dominated by travel interests, while information and
influence were evenly disseminated among active travel-interested
users Individuals who loved to travel and had common travel
experience were more likely to follow travel-related content in
relationship circles on SNSs, make visible contact, be reciprocated,
and have subsequent contact concerning travel-related eWOM
According to centrality analysis, the effect of these individuals
cannot be ignored, given their significant centrality and impact In a
travel-related eWOM communication network, these people would
be more likely to take important positions and from there influence
other users in the network
Fourthly, we discovered that the communication network
struc-ture of travel-related eWOM on SNSs bears three characteristics One,
the communication of travel-related eWOM was not random but
structured The communication network of travel-related eWOM
could be divided into subgroups In the present study, the sample was
dominated by a single subgroup with a close-knit network The
structure of the overall network and components was consistent, and
there were no conditions in which dense areas were surrounded by
marginalized nodes Two, the communication of travel-related eWOM
on SNSs was loose-knit based on social relations The strength of most
social ties was middling or weak and its density low Three, the degree
of centrality was high, while the degree of betweenness centrality was
low in the sample network Network structure therefore exhibits high
centrality To communicate travel-related eWOM, actors in the
network would bypass redundant relationships, which implies that
eWOM at important nodes (i.e., hubs) would influence other nodes
and thereby flatten communication The above results thus also
essentially confirmed the conclusions ofJiang (2009)andVilpponen
et al (2006) Similar to information dissemination via personal
web-sites, travel-related eWOM communication on SNSs was loose-knit
and occurred among small groups The degree of connections
between nodes was not evenly distributed; a few nodes had many connections in the network, whereas the majority of nodes had only a few
Fifth and above all, this study'sfindings illuminate the process of travel-related eWOM communication on SNSs To begin, the network structure of travel-related eWOM outflows was domi-nated by a core and closed by several secondary cores Travel-related eWOM revealed a high degree of centrality and integra-tion It was disseminated from the nodes of high centrality to those
of low centrality with a high degree of information integration Users who loved to travel were more likely to take an important role in travel-related eWOM communication Moreover, the network structure of inflows was dispersed The degree centrality
of eWOM inflow was low; the pathways were diverse and exhibited
a dispersed reception network structure The receiving nodes of travel-related eWOM were relatively even with low centralization; travel-related eWOM could therefore attract the attention of many users, and accordingly, there were no instances in which travel-related eWOM was concentrated to a few actors
By comparison, Jiang (2009) and Vilpponen et al (2006)
investigated the communication network structure on a macro level, whileChu and Kim (2011)andLitvin et al (2008)both pro-vided conceptual frameworks of eWOM dissemination that judged interpersonal influence to be an important variable This empirical study examined the communication process from the perspective
of social network, from where it was viewed as a dynamic, inter-active process Ourfindings gave the inspirations on how eWOM disseminating its influence via social relationships on SNSs Perhaps above all, this study was based on social interaction, which
is the core feature of SNSs
Altogether, ourfindings emphasize the importance of social re-lationships and social networks upon eWOM communication on SNSs
by making the following contributions First, travel information on SNSs was considered eWOM, which provided a new angle for studying emergent media respecting tourism Second, this study focused on social interactions, whereas previous eWOM research primarily emphasized the perspective of individuals and viewed the commu-nicator and receiver as independent individuals with no connections However, any SNS is an interactive platform for users to establish contacts in social circles The features of communication, such as social ties and communication network structure, likely influence the effect
of eWOM significantly; therefore, neglecting to examine communi-cation contacts and relationships between communicators and re-ceivers will yield a distorted understanding of eWOM's effects Furthermore, since travel-related eWOM communication was viewed
as a network based on the user's social relationships, current eWOM studies have been enriched by this study's implication that eWOM dissemination and influence can be better understood given user in-teractions from a dynamic perspective Third, though bothChu and Kim (2011) and Litvin et al (2008) had proposed a conceptual framework of eWOM communication that considered interpersonal
influence, empirical studies remain insufficient Bycontrast, this study was conducted by using SNA, which constitutes an empirical study of travel-related eWOM on SNSs To a great extent, this study therefore provides a practical way to study eWOM communication: focusing on interpersonal influence
SNSs act as amplifiers of travel information Tourists intuitively comment on destinations and tourism experiences both while traveling and in retrospect By reaching a wide audience in social circles and by depending on the strength of social ties in their re-lationships, users' perceptions of destinations and tourism prod-ucts are greatly affected by eWOM on SNSs The advantages and disadvantages of destinations and the travel experiences as evident
in comments can be strengthened and amplified when provided by people close to the potential tourists These tourists' contributions
Q Luo, D Zhong / Tourism Management 46 (2015) 274e282
Trang 9constitute an important force given the communication's influence
bolstered by strong social ties and the communication's power with
weak social ties Since SNSs have become important marketing
tools in tourism, the phenomenon of travel-related eWOM on SNSs
promises to become a topic increasingly visited by scholars and
industry players alike For these reasons, eWOM on SNSs requires
further research, especially regarding its dynamic and interactive
communication processes
Acknowledgments
The research contained in the paper has beenfinancially
sup-ported by a grant from National Natural Science Foundation of
China (to Luo Qiuju) (No.40971041) The authors express their
gratitude to Miss Gao, all respondents and proofreading editors
who have offered help in this study
Appendix A Supplementary data
Supplementary data related to this article can be found athttp://
dx.doi:10.1016/j.tourman.2014.07.007
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Qiuju Luo (1968), Ph.D., female, professor, deputy dean of School of Tourism Management, Sun Yat-sen University ( G u a n g z h o u , G u a n g d o n g , C h i n a 510 27 5 ; e - m a i l :
bettyluoqiuju@126.com ) Prof Luo, researching in the area of exhibition, convention, mega event and event tourism, has published more than 40 academic articles in major journal home and abroad With a series of influential researches, she has earned a good reputation in event in-dustry and tourism inin-dustry in China As the populariza-tion of new media in tourism industry, Prof Luo devotes herself to conducting innovative research on social media and its influence in tourism domain.
Dixi Zhong (1989), female, master student of School of Tourism Management, Sun Yat-sen University (Guangzhou, Guangdong, China 510275; e-mail: dreamy_cecilia@ foxmail.com ) As mobile Internet popularizes, Dixi Zhong develops her interests in e-tourism as well as social media With an acute insight and rigorous academic attitude, she begins to conduct research on new tourism phenomena The electronic referrals on social networking sites are one
of the topics she's probing into.
Q Luo, D Zhong / Tourism Management 46 (2015) 274e282