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On Social Network Web Sites: Definition, Features, Architectures and Analysis Tools

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Journal of Computer Engineering
1 (2009) 3-11
41
On Social Network Web Sites: Definition, Features, Architectures and
Analysis Tools
Vala Ali Rohani
Department Of Software Engineering Faculty of Computer Science and Information Technology University Of Malaya Kuala Lumpur, Malaysia
V.Rohani@perdana.um.edu.my
Ow Siew Hock
Department Of Software Engineering Faculty of Computer Science and Information Technology University Of Malaya Kuala Lumpur, Malaysia Show@ um.edu.my
Abstract Development and usage of online social networking web sites are growing
rapidly. Millions members of these web sites publicly articulate mutual "friendship"
relations and share user-created contents, such as photos, videos, files, and blogs.
The advances in web designing technology and fast growing usage of online
resources prompted web designers to improve features and architectures of social
web sites. This paper, with the experience of the authors in developing the Iranian
Experts Social Network containing above 120,000 official members, describes the
features of Social Web Sites (SWSs) and proposes a taxonomy and comprehensive
definition in designing such social networking tools. We then present different SWS
architectures and also introduce some useful tools for social network analysis.
Keywords: Social network web site, Social media web site, e-society, Social Network
Analysis.
1. Introduction
Using IT Solutions and Web based applications in daily life of people cause the
generation of wide range of social networks. The study of social networks is an almost
natural approach to collaboration. In general, a network comprises of a set of nodes and
a set of ties representing some relationship between the nodes. The nodes in social
networks are most commonly individuals, organizations, or societies, and the ties often
represent collaboration as the particular type of relationship between the nodes [6].
MySpace and Facebook are some examples of these new technology approaches and
each claims more than 250 million registered users [1]. The growth of LinkedIn as a
social networking website, demonstrates the impact of profile information very well. Its
purpose is to help people build professional networks and find career development
opportunities. Using LinkedIn, employers can look into the profile information of users
to search for potential employees. Similarly, it helps employees look for potential
employers [5].
The necessity of a national social network to support information interchange of
Iranian experts motivated us to create the Iranian experts portal1 . This project, having
good infrastructure and skillful features, could attract more than 120,000 Iranian experts
1. http://www.IrExpert.ir
On Social Network Web Sites … V-A. Rohani, O.S. Hock
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to have their own official profile in it and also make their friends networks. Think tank
with more than 300 daily questions and 1200 answers is another valuable outcome of
this project.
There are hundreds of SNSs, with various technological affordances, supporting a
wide range of interests and practices. While their key technological features are fairly
consistent, the cultures that emerge around SNSs are varied. Most sites support the
maintenance of pre-existing social networks, but others help strangers connect based on
shared interests, political views, or activities. Some sites cater to diverse audiences,
while others attract people based on common language or shared racial, religious, or
nationality-based identities. Sites also vary in the extent to which they incorporate new
information and communication tools, such as mobile connectivity, blogging, and
photo/video-sharing [10].
In this paper, we organize the four aspects of social Web sites that we hope would
serve as a comprehensive framework for understanding the features and future of social
Web sites. The four aspects are definition of social Web sites, taxonomy of their
essential features, some famous types of their architectures and finally, some tools for
analyzing the content and relations in social web sites.
2. Social Network Sites: A Definition
In 1967, American psychologist Stanley Milgram [9] conducted the small world
experiment, in which he sent letters to sixty volunteers in Kansas and asked them to
forward the envelopes to a specific person in Massachusettsby hand and through
friends or friends of friends. The letters that reached the addressee were, on average,
relayed by five to seven people. This is seen as an empirical proof that arbitrary people
in our society are related to each other through friends and friends of friends.
The small world hypothesis based on Milgrams findings states that the number of
personal acquaintances needed to connect two random persons on the planet is small.
The hypothesis led to the expression the six degrees of separation, meaning that any
two random persons are associated with each other by a chain of about six individuals.
The six degrees of separation is one of the underlying concepts of social networks on
the Internet.
Social networking services offer friends a space where they can maintain their
relationships, chat with each other and share information. Moreover, they offer the
opportunity to build new relationships through existing friends. On the first use of the
system, users are required to submit a profile containing personal information such as
their name, date of birth, and a photo. The personal information is made available to
other users of the system, and is used to identify friends on the network and to add them
to a list of contacts. In most systems, users cannot only view their friends but also
second degree friends (friends of their friends). Some networks follow an invitation
only approach. Hence, every person in the system is automatically connected to at least
one other person.
Danah M. Boyd defines social network sites as web-based services that allow
individuals to (1) construct a public or semi-public profile within a bounded system, (2)
articulate a list of other users with whom they share a connection, and (3) view and
traverse their list of connections and those made by others within the system. The nature
and nomenclature of these connections may vary from site to site [10].
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Won Kim has proposed defined the social websites as those Websites that make it
possible for people to form online communities, and share user-created contents
(UCCs). The people may be the users of the open Internet or maybe restricted to those
who belong to a particular organization (e.g., corporation, university, professional
society, etc.).The community may be a network of offline friends (whose friendship is
extended to online), online acquaintances, or one or more interest groups (based on
school attended, hobby, interest, cause, profession, ethnicity, gender, age group, etc.).
The UCC maybe photos, videos, bookmarks of web pages, user profiles, users activity
updates, text (blog, micro blog, and comments), etc. The sharing of the UCC includes,
at the minimum, the posting, viewing, and commenting of the UCC, and may also
include voting on, saving, and retransmitting of the UCC. Roughly, He regards social
Web sites as a union of social networking sites and social media sites.
The terms ‘‘social networking sites’’ and ‘‘social media sites’’ have already been
loosely and widely used in press articles, blogs, press releases from the sites, etc., and
the features of such sites are rapidly evolving. As such, we do not feel that efforts to
define social Web sites (for that matter, social networking sites and social media sites as
well) more precisely than above are warranted.
Roughly, social networking sites are Web sites that allow people to stay connected
with other people in online communities (see [10, 11, 12] for attempts to define social
networking sites rather more precisely). Some of the most widely used social
networking sites in the world today include MySpace, Facebook, Windows Live
Spaces, Habbo, etc. Social media sites are Web sites that allow people to share UCCs.
Some of the most widely used social media sites include YouTube, Flickr, Digg,
Metacafe, etc. Users of many of the popular social Web sites are dominated by teens
and those in low twenties. The numbers of male and female users are roughly equal[13].
Historically, social networking sites started before social media sites.
Classmates.com (1995) and SixDegrees.com (1997) were the first social networking
sites. Friendster (2002), MySpace, Bebo, and Facebook (2004) were the next batch of
social networking sites. Social media sites Flickr (2004) and Youtube (2005) followed.
Refs. [10,11,14] provide a history of social networking sites, and Naone [15] gives a
history of microblogging sites, social networking sites that use microblogs for keeping
‘‘friends’’ updated and connected.
3. Social Network Sites Comparisons
Facebook now accounts for almost 60 percent of U.S. traffic to social networking
sites, having increased its share of audience by 194 percent in September 2009
compared with September 2008. During the same period, the once dominant MySpace
slumped to just 30 percent of overall visits, less than half of the 67 percent share it
enjoyed in 2008.
On Social Network Web Sites … V-A. Rohani, O.S. Hock
44
Table 1. Top social networking sites by share of U.S. visitors
Top Social Networking Sites by Share of U.S. Visitors,
September 2009
Rank
Name September
2009 (%) September
2008 (%) Year-
over-
year
change
(%)
1 Facebook 58.59 19.94 194
2 MySpace 30.26 66.84 -55
3 Tagged 2.38 1.62 47
4 Twitter 1.84 0.15 1170
5 myYearbook
1.05 1.76 -40
Additionally, Facebook saw its audience grow by around three percent month-on-
month from August to September 2009, while MySpace experienced a drop of around
three percent, suggesting its audience decline could continue. (Table 1)
Twitter's meteoric growth has resulted in its share of visits increasing by a whopping
1170 percent year-on-year, but it still accounts for just 1.8 percent of social networking
traffic, thereby dwarfed by both Facebook and MySpace. It's important to note,
however, that Hitwise only records traffic through the Twitter.com Web site, and does
not include access through popular third-party applications, such as TweetDeck, which
are likely to account for a large portion of Twitter's use [26].
Tagged received the third largest amount of visits during September 2009 with
around 2 percent, and myYearbook rounded out the top five with around 1 percent.
Also, Figure 1 shows the TopTenReviews results in social networks comparison[25].
Figure 1. 2010 social networking websites review comparisons
4. General Features of Social Networks
There are thousands of social Web sites, and the sites differ in details and layouts of
the features they provide. Further, they continue to add new features and make changes
to existing features. In this section, we will provide taxonomy of essential features that
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can be extracted from todays popular sites. To make the description of each feature
concrete, we provide brief descriptions of how a few representative sites manifest the
feature. We note that although all social Web sites support all these features, they
manifest these in different ways and in varying degrees of sophistication.
Personal Profile
Most social Web sites have members create and manage personal profiles, that is,
homepages. However, they differ in the types of information included. Further, some
sites have members specify privacy settings in order to control who (e.g., everyone,
friends only) may access what types of information on their personal profiles. Personal
profiles on social networking sites used to be more elaborate than those on social media
sites. However, this distinction is becoming blurred, as social media sites are making
the personal profile more elaborate [4].
Communicating With Online Connections
Massage passing system is one of the friendly features of each e-community. Using
this facility, the members of the same social network (also different ones) can send
messages to each other and be alarmed by notification emails.
Social Web sites provide various facilities for members to use to communicate with
their online connections, that is, friends and other members. These include email,
instant messaging, text messaging, and public and private bulletin boards, and even
Internet phone services. Such sites as MySpace and Facebook allow their members to
use the messaging and phone call facilities of Internet phone services, such as Skype.
Further, on behalf of the members, the sites send member updates and notices (e.g.,
friend request notice) using emails or text messages to members friends. They also
send updates and notices to members of groups (e.g., notices regarding a groups status
and activities). The sites also display friends updates to members public and private
boards. Some sites try to block spam by requiring the member to verify a Completely
Automated Public Turing Test to tell Computers and Humans Apart (CAPTCHA) code
before sending an email or text message.
For example, Twitter allows members to send messages to friends on what the
members are doing. A message, which is restricted to 140 characters, may be sent to
friends mobile devices and their Twitter accounts. A member may have one or more
‘‘followers,’’ and many members may be ‘‘following’’ a member. Facebook provides a
mini bulletin board (called a ‘‘wall’’) to post a members message for all friends to see
and respond to. LinkedIn provides an ‘‘answers’’ function to allow members to answer
questions posted by other members, and to refer the questions to their online
connections [4].
Personal Bill Board
Accessing the personal bill board through the profile control panel is one of the most
favorite abilities of each social network. Each member can submit his (or her) daily
events that want to announce in his (or her) profile.
On Social Network Web Sites … V-A. Rohani, O.S. Hock
46
For example, Twitter primarily allows the sharing of short text messages. The only
non-text UCCs it allows two photos of the member: one head and shoulder photo and
one background photo. The member may save in his/her folder the links to selected
(‘‘favorite’’) text messages. MySpace allows the sharing of blogs, photos, videos,
playlists of music contents, etc. YouTube supports the posting and viewing of videos,
including TV program clips, music videos, user-created video blogs, and short original
videos. Members may add titles and tags when posting videos. YouTube adds the titles
and tags to its search engine to support keyword-based search of the videos.
Thinking Room
Most social Web sites allow members to leave comments on the UCCs. Some sites
allow members to vote on them, too. The voting may take the form of ranking (e.g.,
checking 3 stars out of 5 stars), or marking the UCC as a ‘‘favorite,’’ or flagging it as
spam or inappropriate. Some sites present all comments as a flat list of comments, while
others organize comments as a 2-level hierarchy, that is, they allow comments on a
comment. Some sites display the comments in posting timestamp order, and some in
reverse timestamp order. Some sites give a few additional sorting options for displaying
the comments, such as the number of comments, the number of emails that sent the
UCC, the number of favorable votes received, etc.
e-Newsletter
Users tend to glance at websites when they need to accomplish something or to find
the answer to a specific question. In contrast, newsletters feel personal because they
arrive in users inboxes, and users have an ongoing relationship with them. Newsletters
also have a social aspect, as users often forward them to colleagues and friends.
The positive aspect of this emotional relationship is that newsletters can create much
more of a bond between users and a company than a website can. The negative aspect is
that newsletter usability problems have a much stronger impact on the customer
relationship than website usability problems [16].
As a best practice in irexpert project, we find this fact that customers do not check
their social network profile very regularly, but a majority of them check their mail box.
Hence, we can encourage them to browse) our social network by sending them a user
friendly newsletter.
This newsletter consists of the daily news that each member could submit in their
social networks after confirming the related administrator. A web-based agent can
gather daily news, generate pre-styled newsletter and then send it to the corresponding
receivers.
Friendship Network
Social Web sites provide various facilities for members to use to communicate with
their online connections, that is, friends and other members. These include email,
instant messaging, text messaging, and public and private bulletin boards, and even
Internet phone services.
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Each member also can invite others to make a friendship relation and develop his or
friends network. This ability motivates members to check their profiles periodically.
Forums
Many social Web sites support a small number of default groups and assign new
members to one or more of them. They also allow members to explicitly form new
groups, and/or join them. An explicit group is assigned a manager. Members and non-
members can both view all the UCCs in all the groups. However, only members may
post UCCs.
An Internet forum allows many people to chime in about their particular experiences,
information, tips, tricks, etc. There are many computer forums out there which, if you
have a problem with your computer, you can look up that problem and you might find 5
or 1 people who have been talking about that exact problem and how they are trying to
solve it and potential solutions. A forum is an online communication between multiple
users, generally through text-style communication occasionally through voice.
Internet forums really began as an off-shoot of the neighborhood bulletin board, where
you would go and post your want ads or what you needed or maybe, try and get some
business basic places where communities would come together and find information
about various topics. When the Internet came around, it made it much easier for people
to find specific forums, specific bulletin board sites. Some of the popular ones, like
Craigslist, enable you the ability to find anything you want, sell or buy things, hire
people, find a job yourself, find a roommate, etc. It's a place for Internet correspondence
and communication. It's a way for multiple users to give their tips, tricks, and
information about how they're using something or what they've found in their day-to-
day experiences. It's a way for information to be gathered and collected by every basic
user about specific topics [17].
Forums prefer a premise of open and free discussion and often adopt de facto
standards. Most common topics on forums include questions, comparisons and polls of
opinion as well as debates. Because of their volatile and random behavior, it is not
uncommon for nonsense or unsocial behavior to sprout as people lose temper. Poor
understanding of argumentation theory and differences in values of the participants is a
common problem of forums. Because replies to a topic are often wording aimed at
someone's point of view, discussion will usually go slightly off into several directions as
people question each others validity and sources.
5. Social Network Architecture
As huge social network site dramatically grew, the engineers had to solve three
architecture challenges: performance, scalability, and availability. To understand and
solve the bottlenecks on performance and scalability, the engineers have had to start
using system and network monitoring tools, and Web traffic and log file analysis tools.
The performance challenge is to provide real-time response to every user request. As the
traffic to a site increases, the number of members increases, and/or the amount of data
stored in the site increases, performance of the site is bound to degrade. The scalability
challenge is to maintain the performance at the same level even as the traffic, number of
members, and the amount of data stored increase. The availability challenge is to have
the site provide all services and access to all the data stored to all users at all times. Fig.
On Social Network Web Sites … V-A. Rohani, O.S. Hock
48
4 shows the prototypical architecture of huge social networks, such as YouTube,
MySpace, Facebook, Flickr, etc. Below, we describe the key components of the
architecture, and techniques used in meeting the three architecture challenges.
Figure 2. An architecture for huge social networks
5.1 Speeding up the Web Servers
Considering the important role of Web server, Site administrators need to ensure that
the Web server does not become overloaded. The sites manage incoming requests by
using various means, such as firewalls and HTTP traffic manager to block or redirect
unwanted or ill-formed traffic, and a traffic shaper to smooth out peaks in requests.
However, the engineers have determined that the key bottleneck for the Web servers is
the time it takes waiting for responses to remote procedure calls (RPC). For higher
performance, tremendous sites use Web server farms, consisting of multiple, more
powerful computers with more main memory and hard disk drive capacity. Gigantic
sites have also introduced a load balancer and/or reverse proxy servers in front of the
Web server farm. A reverse proxy server is installed to load balance the Web server
farm and to cache both static and dynamic content. It also provides an additional layer
of security.
5.2 Use of Main-memories as Cache
Major sites, use memcaches extensively. Memcache is an in- memory hash table that
is distributed across multiple servers. It has become an essential component of the
architecture to meet the performance and scalability challenges. It listens to the TCP
socket for requests. Hash tables are maintained in memcaches to rapidly respond to
metadata keyword searches, such as the member ID. The size of memcaches is often
over 16 Gigabytes. Further, some major sites, such as YouTube and MySpace, store
most frequently accessed contents and less frequently accessed contents on separate
server farms, serving most frequently accessed contents out of main memories of one
server farm. In particular, MySpace employs more than 1200 cache servers [18].
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5.3 Database Partitioning and Replication
Major sites have to deal with huge amounts of data of various types. The sites assign
different server farms to manage different types of data. Major sites, partition the
database based on services (e.g., member profiles, emails, news, videos, etc.). They use
a different application server farm for each service. This naturally distributes the load on
the application servers and database servers. Further, the sites keep multiple copies all
the databases. This is to address the performance, scalability, and availability
challenges.
Its popular in huge social networks to extend database partitioning and replication to
the level of relational tables. That is, they partition a huge relational into multiple
smaller tables comprising of some of the columns (i.e., ‘‘vertical decomposition’’)
and/or rows (i.e., ‘‘horizontal decomposition’’) of the original table. They also maintain
multiple copies of some of the table partitions. For example, such sites as YouTube,
Flickr, LinkedIn, and MySpace decompose the members table into separate partitions,
and replicate each partition [18,19]. MySpace keeps one million users in each partition;
and needs 300 partitions to store all 300 million registered members. Partitioning and
replication can each help meet the performance, scalability, and availability challenges.
5.4 Use of Server Farms
Gigantic social network sites use server farms for each of the three key components
of the site, rather than merely doubling it. For each server farm, there is a control server
that manages distribution of work, load balancing, and dynamic reconfiguration of the
server farm (i.e., adding a new server, taking out a server). The use of server farms
helps meet the performance, scalability, and availability challenges.
5.5 Redundant Servers and Database Backup
As a major site consists of thousands or tens of thousands of commodity hardware,
server failure occurs frequently. Major sites pair each server with a backup server. This
helps to meet the availability challenges. When a server crashes, its backup takes over
the processing load. All sites back up the database on a regular basis in order to recover
from crashes of hard disk drives and servers. They back up the database in its entirety or
selected parts once a day, a week, every two weeks, or a month.
6. Social Network Analysis
Social Network Analysis (SNA) is the study of social relations among a set of actors.
The key difference between network analysis and other approaches to social science is
the focus on relationships between actors rather than the attributes of individual actors.
Network analysis takes a global view on social structures based on the belief that types
and patterns of relationships emerge from individual connectivity and that the presence
(or absence) of such types and patterns have substantial effects on the network and its
constituents. In particular, the network structure provides opportunities and imposes
constraints on the individual actors by determining the transfer or flow of resources
(material or immaterial) across the network.
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50
SNA is thus a different approach to social phenomena and therefore requires a new
set of concepts and new methods for data collection and analysis. Network analysis
provides a vocabulary for describing social structures, provides formal models that
capture the common properties of all (social) networks and a set of methods applicable
to the analysis of networks in general. The concepts and methods of network analysis
are grounded in a formal description of networks as graphs. Methods of analysis
primarily originate from graph theory as these are applied to the graph representation of
social network data.
It is interesting to note that the formalization of network analysis has brought much
of the same advantages that the formalization of knowledge on the Web (the
SemanticWeb) is expected to bring to many application domains. Previously vaguely
defined concepts such as social role or social group could now be defined on a formal
model of networks, allowing to carry out more precise discussions in the literature and
to compare results across studies.
The methods of data collection in network analysis are aimed at collecting relational
data in a reliable manner. Data collection is typically carried out using standard
questionnaires and observation techniques that aim to ensure the correctness and
completeness of network data. Often records of social interaction (publication
databases, meeting notes, newspaper articles, documents and databases of different
sorts) are used to build a model of social networks [20].
This section reviews software for the statistical analysis of social networks. The
programs UCINET, Pajek, NetMiner II and STRUCTURE are investigated in
following. We start with three general packages, covering a wide range of analysis
methods. They are presented according to age: UCINET, Pajek and NetMiner [21].
6.1. Ucinet
UCINET is a social network analysis program developed by Steve Borgatti, Martin
Everett and Lin Freeman. The program is distributed by Analytic Technologies.
UCINET works in tandem with freeware program called NETDRAW for visualizing
networks. NETDRAW is installed automatically with UCINET.
Figure 3. UCINET software interface
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UCINET is a comprehensive package for the analysis of social network data as well
as other 1-mode and 2-mode data. It Can read and write a multitude of differently
formatted text files, as well as Excel files and is able to handle a maximum of 32,767
nodes (with some exceptions) although practically speaking many procedures get too
slow around 5,000 - 10,000 nodes. Its social network analysis methods include
centrality measures, subgroup identification, role analysis, elementary graph theory, and
permutation-based statistical analysis. In addition, the package has strong matrix
analysis routines, such as matrix algebra and multivariate statistics [22].
6.2 Pajek
Pajek is a windows-based program, for analysis and visualization of large networks
having some thousands or even millions of vertices. The main goals in the design of
Pajek are:
to support abstraction by (recursive) decomposition of a large network into several
smaller networks that can be treated further using more sophisticated methods.
to provide the user with some powerful visualization tools.
to implement a selection of efficient (subquadratic) algorithms for analysis of large
networks.
Figure 4. Pajek software interface
Pajek has some features to find clusters (components, neighborhoods of important
vertices, cores, etc.) in a network, extract vertices that belong to the same clusters and
show them separately, possibly with the parts of the context (detailed local view), shrink
vertices in clusters and show relations among clusters (global view).
Besides ordinary (directed, undirected, mixed) networks, Pajek supports also multi-
relational networks, 2-mode networks (bipartite (valued) graphs networks between
two disjoint sets of vertices), and temporal networks (dynamic graphs networks
changing over time) [23].
On Social Network Web Sites … V-A. Rohani, O.S. Hock
52
6.3 NetMiner
NetMiner is an innovative software tool for Exploratory Analysis and Visualization
of Network Data with some abilities to explore network data visually and interactively,
and also to detect underlying patterns and structures of the network.
The last version of this software is 3.4.0 wich released on 23 Sep. 2009. In this new
version, Layout and Drawing module that can be used for drawing large-scale 2D
network map by separating the visualization process into two steps(layout and drawing)
are now expanded to handle 3D network map. The coordinates of the 3D network map
can be generated by Layout 3D module and drawing 3D network map using the
generated coordinates can be accomplished by Drawing 3D module [24].
7. Future of Social Networks
Some reports predicts that growth in the number of people signing up to be a part of
the cultural phenomenon, which has put the likes of Facebook on the map, will plateau
by 2012. Growth in the membership of social-networking sites varies dramatically by
region, which predicts Asia Pacific will account for 35 percent of global social
networking users by the end of this year, followed by EMEA (28 percent), North
America (25 percent), and the Caribbean and Latin America (12 percent).
Figure 5. NetMiner software interface
Next generation Social Networking will present key insights not just in text, but a
visually appealing manner; from transactions to transformation; from raw data to visual
insights.
And finally, Enterprise Social Networking is being used to bring all the
functionalities inside a company to support the key goals and strategic objectives of the
organization.
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On Social Network Web Sites … V-A. Rohani, O.S. Hock
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... Les systèmes de recommandation font partie des systèmes qui permettentà leurs utilisateurs de s'entraider tout en garantissant la confiance et la fiabilité dans l'échange d'informations. Le chapitre 3 introduit un aperçu sur ces systèmes et souligne l'apport de peut accéderà tel ou tel type d'information sur leur profil personnel [RH09]. ...
Thesis
De nos jours, les réseaux sociaux constituent un élément essentiel de la vie des personnes du monde entier. Le World Wide Web est le principal outil utilisé pour partager des informations et interagir avec d'autres personnes via Internet. Pour s'adapter à l'évolution du Web, les techniques de recherche d'information ont dû intégrer des aspects sociaux et axés sur l'utilisateur et son comportement. Parmi ces techniques, on parle dans ce travail des systèmes de recommandation.En effet, la majorité de ces réseaux et systèmes n’offrent pas de réelles garanties sur le respect de la vie privée des utilisateurs (c’est-à-dire, ils collectent des données d’identités des consommateurs). Ce travail de thèse s’inscrit dans le cadre de la famille des réseaux dits « anonymes » où l’anonymat des utilisateurs est complètement respecté (non-collecte des informations liées à leurs identités). On peut donc se demander comment les utilisateurs peuvent se faire confiance et se fier aux informations fournies par ces systèmes tout en étant anonymes ? Il est donc essentiel d’instaurer un modèle confiance au sein du réseau social. Plusieurs travaux de recherche ont été menés pour développer des réseaux sociaux et des systèmes de recommandation à base de confiance. Ces systèmes utilisent des relations de confiance entre les utilisateurs pour prédire les évaluations de confiance en fonction des expériences et des commentaires.Bien que l'exploitation de ces relations d'interaction soit souvent efficace pour améliorer les résultats fournis par les systèmes de recommandation, on peut néanmoins noter quelques problèmes. Le premier concerne la nature statique de certains systèmes de recommandation et qui ne s’adaptent donc pas aux changements des comportements des utilisateurs. Le deuxième problème concerne la modélisation de la confiance. Ce concept est utilisé dans plusieurs domaines, cependant, une définition uniforme et consensuelle de ce concept n’existe pas. Le troisième problème a trait à la variation des modèles computationnels dans les systèmes à base de confiance. En fait, les interactions entre les utilisateurs génèrent des nouvelles données ce qui peut mener un utilisateur à changer son comportement et ses activités dans le système. Ce qui va créer des variations dans les profils utilisateurs. Certains utilisateurs ont des comportements corrects dans le système, d'autres peuvent faire des activités malveillantes. D'autres utilisateurs font confiance rapidement, d'autres sont méfiants à l’égard des inconnus, etc. Tous ces comportements doivent conduire à un (re)calcul de la valeur de la confiance selon différents modèles computationnels.Dans le cadre de cette thèse, dans un premier temps, un travail sur les systèmes de recommandation a été réalisé afin de trouver une solution pour la nature statique de ces systèmes. Cette solution utilise des techniques issues de l’apprentissage par renforcement. Dans un second temps, nous avons proposé un cadre unifié de gestion de la confiance tant au niveau sémantique qu’au niveau calculatoire. Une analyse approfondie pour comprendre l'intuition derrière chaque modèle computationnel a également été introduite. Enfin, la question de la sélection d’un modèle computationnel le plus approprié, selon la nature des besoins des utilisateurs, a aussi été abordée.
... Selain itu, layanan jejaring sosial mengizinkan seseorang untuk membagikan pengalaman, informasi, opini, preferensi, dan ulasan pada suatu produk (Lim, Heinrichs dan Lim, 2017). Layanan jejaring sosial juga menawarkan ruang untuk menjaga hubungan antar teman dan membuat relasi baru (Rohani, 2009 Twitter merupakan layanan jejaring sosial yang mengizinkan penggunanya untuk untuk membagikan informasi secara real-time melalui posting pengalaman dan pemikiran mereka (Mistry, 2011). Sebagai sistem micro-blogging, Twitter biasa digunakan untuk memperbarui status, memulai percakapan, mempromosikan produk, dan bahkan untuk mengirim spam (Benevenuto et al., 2010). ...
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Privasi adalah sesuatu yang penting di era ini. Namun, kasus kejahatan dunia maya yang mengancam privasi pengguna internet yang jumlahnya semakin banyak, termasuk pengguna layanan jejaring sosial seperti Twitter. Tujuan dari penelitian ini adalah untuk memahami hubungan information privacy concern dan perilaku perlindungan privasi serta hubungan antara komponen-komponen Protection Motivation Theory, yaitu perceived severity, perceived vulnerability, response efficacy, self-efficacy, rewards, dan response costs, dan information privacy concern pengguna Twitter di Indonesia. Dengan menggunakan simple random sampling, kuesioner dibagikan secara daring di Twitter pada tanggal 13 November 2020 sampai 15 November 2020. Dalam rentang waktu tersebut didapatkan 156 data. Data yang terkumpul lalu dianalisis dengan menggunakan Structural Equation Modeling. Hasil menunjukkan information privacy concern berpengaruh positif dan signifikan terhadap perilaku perlindungan privasi. Perceived seveerity, perceived vulnerability, response efficacy, dan self-efficacy memiliki pengaruh positif serta signifikan terhadap information privacy concern. Sedangkan rewards secara negatif dan signifikan mempengaruhi information privacy concern. Response costs tidak memiliki pengaruh yang signifikan terhadap information privacy concern.
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Digital technology such as AI has enabled private companies to collect and analyse people’s personal information, which may infer hidden private data about the individual, such as medical data or psychological state. The inferred private information can be sold to third parties or used to target advertisements without the individual’s knowledge and explicit consent. Private companies, therefore, pose a risk to internet users’ right to privacy in the digital world. As such, the legal system should have a comprehensive Data Privacy law that provides internet users with adequate legal protection for preserving their right to privacy against private companies. Still, Kuwait lacks comprehensive Data Privacy. The only two data privacy mechanisms are embodied in chapter 7 under the Electronic Transaction Act ( ETA ) No. 20 of 2014 and the Regulation of User Protection and Privacy issued by the Communication and Information Technology Regulatory Authority ( CITRA ). This paper finds that the fragmented Kuwaiti laws concerning the individual’s right to privacy inadequately protect internet users’ right to privacy against the risk posed by private companies, and therefore, legislative interventions are needed. This paper concludes with proposing essential recommendations for the Kuwaiti Legislative Authority to issue a comprehensive data privacy law, using European Union’s General Data Protection Regulation as a guidance framework ( GDPR ), to strengthen internet users’ right to privacy (as control over their personal information) against the risk private companies pose.
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This research aims to determine the factors affecting the users’ electronic word-of-mouth (eWOM) seeking and sharing intentions and to reveal the interactions among and within clusters using social network analysis (SNA). This study includes three hierarchical sub-studies conducted in two countries, Turkey and Poland. First, we develop a segmentation for social networking site (SNS) users based on the frequency of sharing product-related information on SNSs. Second, we investigate the impact of several factors that affect eWOM seeking and sharing intentions using regression analysis. In the second sub-study, we also include the identified segments developed in the first sub-study as another factor that may have differentiated eWOM intentions. Third, to understand the degree of interaction among SNS users, we apply an SNA using the forecasted eWOM intentions scores from the second sub-study, which gives us hypothetical social networks. The results of SNA present strong interactions inter- and intra-clusters in both countries. Some key findings include the identification of three SNS user segments, including “Middlers,” that may be of particular interest to brands. We also find that in terms of eWOM intentions, users in Turkey are more active than in Poland. Although some predictors of eWOM seeking and sharing intentions differ between the two countries, users intend to be more active in eWOM seeking than in eWOM sharing. The comparative study provides valuable insights for decision-makers to engage different market segments via SNSs with various proposed features using suggested information contents for selected product categories.
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İÇİNDEKİLER ÖNSÖZ i İÇİNDEKİLER iii I. BÖLÜM DESTİNASYON PAZARLAMASININ İNCELENMESİ GİRİŞ 1 1.1. Destinasyon Kavramı 2 1.2. Destinasyonların Yaşam Döngüsü 3 1.3. Destinasyon Unsurları 5 1.4. Destinasyon Pazarlaması 6 1.5. Destinasyon Pazarlama Karması 8 1.5.1. Destinasyon Pazarlamasında Ürün 8 1.5.2. Destinasyon Pazarlamasında Fiyat 10 1.5.3. Destinasyon Pazarlamasında Dağıtım 11 1.5.4. Destinasyon Pazarlamasında Tutundurma 12 1.6. Destinasyon Pazarlamasında Etkili Unsurlar 15 1.6.1. Destinasyon Markası 15 1.6.2. Destinasyon İmajı 15 1.6.3. Destinasyon Konumlandırma 16 1.7. Destinasyon Pazarlamasında Başarı İçin Kritik Unsurlar 17 KAYNAKÇA 20 II. BÖLÜM DESTİNASYON PAZARLAMASI VE DESTİNASYON REKABETÇİLİĞİ GİRİŞ 24 2.1. Rekabet Kavramı 25 2.2. Destinasyon Rekabetçiliği 26 2.3. Destinasyon Rekabetinin Önemi 27 2.4. Destinasyonların Rekabet Gücü Modelleri 28 2.4.1. Ritchie ve Crouch’un Kavramsal Rekabet Modeli 28 2.4.2. Porter’ın Rekabet Gücü Analizi Modeli 29 2.4.3. Kim’in Rekabet Modeli 30 2.4.4. Dwyer ve Kim’in Bütünleştirilmiş Rekabet Modeli 31 2.5. Destinasyon Rekabetini Etkileyen Faktörler 33 2.5.1. Sürdürülebilir Turizm ve Çevre 34 2.5.2. Hizmet Kalitesi ve Müşteri Memnuniyeti 35 2.5.3. Verimlilik ve Kaynakların Etkin Kullanımı 36 2.5.4. Turistik Ürün Çeşitlendirmesi 37 2.5.5. Destinasyon İmajı ve Yenilik 38 2.5.6. Turizm Pazarlama Stratejisi ve Pazar Payı 38 2.5.7. Devlet ve Turizm Politikaları 40 2.5.8. Destinasyon Pazarlaması ve Yönetimi 41 2.5.9. Kültürel Miras 42 2.5.10. Fiyat ve Değer 43 2.5.11. Güvenlik 44 2.5.12. Ulaşım ve Alt Yapı 45 2.5.13. Destinasyon Çekiciliği, Cazibe Yerleri, Çekim Merkezleri 46 2.5.14. Bölge Sakinlerinin Yaşam Kalitesi 47 2.5.15. E-Hazırlık 47 2.5.16. İklim Çekiciliği 48 2.5.17. Eğlence, Aktiviteler, Etkinlikler, Festivaller, Gece Hayatı 49 2.5.18. Gastronomi 50 2.5.19. Turistik Konaklama Olanakları 51 KAYNAKÇA 52 III. BÖLÜM DESTİNASYON YÖNETİMİ VE PAYDAŞ İLİŞKİSİ GİRİŞ 61 3.1. Destinasyon Yönetimi 62 3.2. Destinasyon Yönetimi Fonksiyonları 63 3.2.1. Destinasyonlarda Planlama 63 3.2.2. Destinasyonlarda Örgütleme 66 3.2.3. Destinasyonlarda Koordinasyon 68 3.2.4. Destinasyonlarda Yöneltme 69 3.2.5. Destinasyonlarda Kontrol 70 3.3. Destinasyon Yönetiminde Paydaşlar 71 3.3.1. Merkezi Yönetim 73 3.3.2. Yerel Yönetim 74 3.3.3. Sivil Toplum Kuruluşları 76 3.3.4. Özel Sektör 78 3.3.5. Turistler 79 3.3.6. Yerel Halk 80 KAYNAKÇA 82 IV. BÖLÜM OTANTİZM VE DESTİNASYON PAZARLAMA İLİŞKİSİ GİRİŞ 87 4.1. Otantizm Kavramı 88 4.2. Turizmde Otantizm ve Biçimleri 90 4.2.1. Nesneye Dayalı Otantizm 91 4.2.1.1. Nesnel (Objektivist) Otantizm 91 4.2.1.2. Yapısalcı (Constructivism) Otantizm 92 4.2.2. Aktiviteye Dayalı Otantizm 93 4.2.2.1. Varoluşçu (Existentialism) Otantizm 93 4.2.2.1.1. İçsel Otantizm 94 4.2.2.1.2. Kişilerarası Otantizm 95 4.3. Otantizmin Turizm Destinasyonlarına Etkisi 96 4.3.1. Otantizm ve Marka 96 4.3.2. Otantizm ve İmaj 97 4.3.3. Otantizm ve Gastronomi 98 4.3.4. Otantizm ve Kültürel Turizm 100 4.3.5. Otantizm ve Turist Deneyimi 101 4.3.6. Otantizm ve Pazarlama 102 KAYNAKÇA 105 V. BÖLÜM DESTİNASYON PAZARLAMASINDA AFETLER, KRİZLER VE KARANLIK TURİZM GİRİŞ 110 5.1. Kriz ve Kriz Yönetimi Kavramları 110 5.2. Krizlerin Özellikleri 113 5.3. Turizmde Kriz ve Kriz Yönetimi 114 5.3.1. Deprem ve Diğer Doğal Afetlerin Yarattığı Krizler 116 5.3.2. Terörizm ve Savaşın Yarattığı Krizler 118 5.3.3. Covid-19 Dönemi Turizm Destinasyonları ve Etkileri 120 5.3.4. Genel Ekonomik ve Finansal Krizlerin Yarattığı Krizler 122 5.4. Karanlık (Dark) Turizm 123 5.5. Karanlık Turizm Türleri ve Örnekleri 125 KAYNAKÇA 128 VI. BÖLÜM DESTİNASYON MARKASI VE HEDEF MARKA KİMLİĞİ GİRİŞ 133 6.1. Marka ve Markalaşma Kavramı 134 6.2. Destinasyon ve Markalaşma 136 6.2.1. Destinasyon Marka İmajı 140 6.2.2. Destinasyon Marka Kimliği 141 6.2.3. Destinasyon Marka Kişiliği 143 6.2.4. Destinasyon Marka Değeri 144 6.2.5. Destinasyon Marka Farkındalığı 146 6.2.6. Destinasyon Marka Sadakati 148 6.2.7. Destinasyon Marka Özgünlüğü 150 6.3. Destinasyon Marka Oluşturma Süreci 151 6.3.1. Slogan ve Logolar 151 6.3.2. İnternet ve Web Siteleri 153 6.3.3. Dizi ve Filmler 155 6.3.4. Fuar ve Festivaller 157 6.3.5. Yöre Halkının Tutum ve Davranışları 159 6.3.6. Ulaşım, Alt ve Üst Yapı Çalışmaları 161 6.3.7. Gastronomik Değerler 162 6.4. Destinasyon Markalaşmasının Faydaları 164 KAYNAKÇA 166 VII. BÖLÜM HATIRLANABİLİR TURİST DENEYİMİ VE DESTİNASYON İMAJI İLİŞKİSİ GİRİŞ 176 7.1. Deneyim Kavramı 177 7.2. Deneyimin Özellikleri 178 7.3. Turist Deneyimi ve Hatırlanabilir Turizm Deneyimleri 179 7.4. Turist Deneyimi Boyutları 181 7.4.1. Hazcılık 182 7.4.2. Yenilik 184 7.4.3. Yerel Kültür 186 7.4.4. Yenilenme 187 7.4.5. Anlamlılık 188 7.4.6. Katılım 189 7.4.7. Bilgi 190 7.5. İmaj Kavramı 191 7.6. Destinasyon İmajı ve Algılanan Destinasyon İmajı 192 7.6.1. Bilişsel Destinasyon İmajı 194 7.6.2. Duygusal Destinasyon İmajı 195 7.6.3. Davranışsal Destinasyon İmajı 196 7.7. Destinasyon Marka İmajı Oluşturma Süreci 196 7.7.1. Destinasyon Marka Stratejisi Geliştirme 196 7.7.2. Destinasyon Kimliği ve Bileşenleri 198 7.7.3. Destinasyon Kimliğini İmaja Dönüştürme 199 7.7.4. Konumlandırma 199 7.8. Destinasyon İmajının Faydaları 200 KAYNAKÇA 202 VIII. BÖLÜM DESTİNASYON MARKA KONUMLANDIRMASI GİRİŞ 209 8.1. Marka Konumlandırma 209 8.2. Marka Konumlandırma Süreci 212 8.3. Marka Konumlandırma Stratejileri 213 8.4. Marka Yeniden Konumlandırma 215 8.5. Konumlandırma Hataları 216 8.6. Destinasyon Marka Konumlandırma 217 8.7. Destinasyon Konumlandırma Stratejileri 219 8.7.1. Objektif Konumlandırma 219 8.7.2. Sübjektif Konumlandırma 220 KAYNAKÇA 222 IX. BÖLÜM DESTİNASYON PAZARLAMA İLETİŞİMİ GİRİŞ 226 9.1. İletişim Kavramı 226 9.2. Pazarlama İletişimi 228 9.3. Bütünleşik Pazarlama İletişimi ve Önemi 229 9.4. Bütünleşik Pazarlama İletişiminin Özellikleri 231 9.5. Destinasyonlarda Bütünleşik Pazarlama İletişimi 232 9.6. Destinasyonlarda Bütünleşik Pazarlama İletişimi Araçları 233 9.6.1. Halkla İlişkiler 233 9.6.2. Kişisel Satış 234 9.6.3. Reklam 235 9.6.4. Satış Geliştirme 235 9.6.5. Doğrudan Satış 236 9.6.6. İnternet ve Sosyal Medya 236 9.6.7. Fuarlar, Festivaller ve Etkinlikler 237 9.6.8. İlişkisel Pazarlama 238 9.6.9. Dizi, Film ve Ürün Yerleştirme 239 9.6.10. Sponsorluk 239 KAYNAKÇA 241 X. BÖLÜM DESTİNASYON PAZARLAMASINDA İNTERNET VE SOSYAL MEDYA GİRİŞ 245 10.1. İnternet ve Sosyal Medya Kavramları 245 10.2. Sosyal Medyanın Özellikleri 246 10.3. Sosyal Medya Pazarlaması 247 10.4. Sosyal Medya Pazarlamasının Avantajları 248 10.5. Destinasyon Pazarlamasında İnternet 249 10.6. Destinasyon Pazarlamasında Kurumsal Web Siteleri 251 10.7. Destinasyon Pazarlamasında Sosyal Medya 253 10.7.1. Facebook Yoluyla Pazarlama 256 10.7.2. Twitter Yoluyla Pazarlama 257 10.7.3. Youtube Yoluyla Pazarlama 258 10.7.4. Instagram Yoluyla Pazarlama 259 KAYNAKÇA 261 XI. BÖLÜM DESTİNASYONLAR VE SANAL GERÇEKLİK TEKNOLOJİSİ GİRİŞ 266 11.1. Sanal Gerçeklik 267 11.2. Sanal Gerçeklik Teknolojisinin Avantajları 269 11.3. Sanal Gerçeklik ve Pazarlama 270 11.4. Destinasyon Pazarlaması ve Sanal Gerçeklik 271 11.4.1. Bilgi Arama Sürecinde Sanal Gerçeklik 273 11.4.2. Karar Verme Sürecinde Sanal Gerçeklik 273 11.4.3. Sanal Turlar 274 KAYNAKÇA 277 XII. BÖLÜM YAVAŞ TURİZM DESTİNASYONLARI GİRİŞ 280 12.1. Yavaş Yaşam 280 12.2. Yavaş Turizm 282 12.3. Yavaş Turizm Bileşenleri 284 12.3.1. Yavaş Turist 284 12.3.2. Yavaş Seyahat (Slow Travel) 285 12.3.3. Yavaş Yemek (Slow Food) 286 12.3.4. Yavaş Şehir (Cittaslow) 287 12.4. Türkiye’de Yavaş Turizm Destinasyonları 290 KAYNAKÇA 294
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  • Nielsen Norman
  • Group Report
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