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Social Networking and On-Line Communities: Classification and Research Trends
Maria Ioannidou, Eugenia Raptotasiou, Ioannis Anagnostopoulos
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Evolution of the on-line social networks research field in WWW conf. series until 2005 the papers are
few (1 to 3 per year) increase of scientific
interest from 2006, when online social networks are recognized as an autonomous track
numbers keep rising: 28 in WWW2010
In WWW2011 out of 90 regular papers 12 contained the term “social” in their title
18 out of 89 posters were classified in “Social Systems and Graph Analysis”
Frequency of papers on social networks in WWW conferences in the period 2000-2010.
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Web Science Subject Categorization*
E. Web Society
E.2 Social Engagement and Social Science
E.2.1 Social networks
E.2.7 Virtual communities, groups and identity
E.6 Politics and Governance
E.6.2 Policy and Regulation
E.6.2.2 Privacy
E.6.2.3 Trust
E.6.2.4 Security
* http://webscience.org/2010/wssc.html
“The Web Science Subject Categorization (WSSC) system aims to facilitate communication and collaboration among scholars of the Web from various perspectives i.e. computational, mathematical, social, economic and legal”
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Our categorisation
Social Engagement and Social Science◦ Social networks
Web as a Complex System Systems, Social structures and processes Technologies used
◦ Virtual communities, groups and identity (Personalisation / Adaptation) Social interaction and behaviour Information propagation Social interest discovery, personalisation Community structure, evolution
Politics and Governance Policy and Regulation (Security, Privacy, Trust)
User anonymization Groups and mixed user profiles Collective privacy management User Reputation
How we worked… an example
In degree
Out degree
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Social Networks
See the Web as a Complex System:◦ Graphs
Systems, Social structures and processes◦ Network applications
Technologies used◦ Services, Games
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21
8797
1
110
4
2
5
7788104
115
126
89
6
78
7
7990
98105
111
8
80
91
99
106
112
9
81
12
10
13
82
92
100
107
113
116
118119
120
121
122
123
124
125
1483
15
84
93
101
16
85
94
102108
114
117
19
28
96
2086
95
103
109
22
23
24
2526
2729
30
31
32
3334
35
36
37
3839
4011
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
5758 59
60
61
62
63
64
65
6617
6768
69
70
71
72
73
74
75
76
18
Social Networks
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Virtual communities, groups and identity
Social interaction and behaviour- relation between a person’s social interactions and
personal behavior- Positive / Negative links
Information propagation- how quickly does information propagate- how widely does information propagate in the social
network- what is the role of word-of-mouth exchanges between
friends in the overall propagation of information in the network.
Social interest discovery, personalisationCommunity structure, evolution
- discovering and processing some of the community characteristics in order to predict their future evolution
Virtual communities, groups and identity
Profile / Group based
Behaviour basedCollaboration based
ImplicitExplicit
Hybrid
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Security, Privacy, Trust
User anonymizationhas to do with identifying security and privacy in on-line social networks and how this ensures, that the users are protected by malicious targeted attacks.Groups and mixed user profilesattacks that exploit the user groups with mixed profiles, in an effort to predict the users’ sensitive private attributes.Collective privacy managementdata that do not necessarily belong to the users that publish them.Privacy wizardSolutions and models that help users to describe their preferences and define their privacy settings automatically.
User Reputation
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Security, Privacy, Trust
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Relevancy between E.2.1/E.2.7 and E.6.2
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Graph Statistics
222 papers from which 104 and 31 concern categories E.2.1/E.2.7 and E.6.2
10% on the total papers are isolated nodeson average, each node is connected to two other
nodesgenerally, most nodes have low in/out degree there are links with papers from almost all other
tracks!high efficiency in information exchanging
(network’s efficiency value was 0.5)
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Generic Conclusions
Number of research efforts in social networks is still increasing
Existing problems become more intense and new arise as on-line users’ numbers increase
The topic of security and privacy seems to gain ground for now
Almost all other web topics are affected as well as other science fields
Semantic web research / semi-automatic information organisation can benefit from the study of social networks
Verify relations and weights between already established categorisations / semantic networks, or even exploit new ones (by graph clustering)
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Future workexplore in detail network’s structure and evolution
by including data from other sources / network graphs
examine the graph association of a specific topic with other topics (below an example from WWW conf. series)
Connections of E.6.2 with other topics:
black E.6.2grey other
Thank you …!!!
Questions ???
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Specific Conclusions
Social networking services fail to provide users the necessary protection and users tend to compromise their privacy neglecting necessary precautions
Community structure and activities within the communities have become more and more complicated but if studied can provide valuable information about human behavior and interaction
Similarity measurement among user profiles could be exploited in marketing methods and undergoing semantic web research