1. Characterization of users of Online Social Networks Debesh Majumdar 2nd Year Student VGSOM, IIT Kharagpur April 29, 2011

3. Secondary sources of data

4. Primary data source

5. Observations

8. Built and directed by users themselves

9. Users populate the network with content and conversations

10. Direction of content is determined by anyone who takes part in the discussion

11. Unpredictability of direction makes it dynamic and exciting

12. Interactive

13. Presence of network based gaming applications alongside forums and chatrooms

14. These applications allow users to connect with other users and have fun

15. Community-driven

16. Users having common beliefs or interests create communities

18. Number of connections of users determine the user's distance from the centre of the network

19. Content published by a user proliferates exponentially as the number of contacts increases

20. Emotion over content

21. OSNs provide an easy way to reach out to a large number of friends

22. Certain sense of emotional security as friends are within easy reach

24. Degree-zero nodes who have joined the service but have never made a connection with another user

25. Do not actively participate in the network

26. Giant components

27. Represent the large group of people who are connected to one another through paths in the network

28. Typically connected directly or indirectly to a large fraction of the entire network

29. Contains most of the highly active and gregarious individuals

30. Middle region

31. Consists of various isolated communities

32. Small groups who interact with one another but not with the network at large

34. Almost all isolated communities are stars

35. A star is a single charismatic individual linked to a varying number of other users who have very few other connections

36. Evolution of stars characterized by two processes

37. Isolated communities grow one user at a time

38. Either merge into the giant component or cease to exist when the star loses focus

39. Merging stars represent the outer layer of a giant component

40. A group of tightly-connected active members form the core of a giant component

42. Users can be classified into three groups according to their posting behaviour - steadily posting, occasionally posting and inactively posting

43. 20% users contribute to 80% of the total content in the network

45. Extrovert individuals have a significantly higher number of connections than introvert individuals

46. Extrovert individuals demonstrate a lower use of personal information

47. Highly neurotic individuals prefer to post more photos

48. People with low and high levels of agreeableness are inclined to upload more pictures than people with a moderate level of agreeableness

49. Individuals having high degree of openness to experience use more features from the personal information section

51. Trust Altruism Subjectivity of question Expertise Belief that search engines would not work Properties of question Specific audience Nature of relationship Connect socially Connect socially Motivation for Q&A in OSN Questions Answers

53. People tend to form ties with other people who have similar characteristics

54. Stronger the ties, higher the similarities

55. Elements used to measure relationship strength

56. School and university attended

57. Companies worked for

59. Lengthen the tail

60. Fatten the tail

61. Drive demand down the tail

63. Default/standard

64. Sensitive

65. Potentially stigmatizing

66. Approximately 25% of all possible information that could potentially be disclosed by individuals are disclosed

67. Disclosure of personal information such as gender and age is related to disclosure of other sensitive and highly personal information

68. Younger people have more personal information on their profiles

70. Specification of legitimate reasons to access a specific piece of information

71. Visibility

72. Who is allowed to access provided data

73. Granularity

74. Degree of precision that is revealed in response to a query for a piece of data

75. Retention

76. The time period during which access to data should be allowed

77. Registration

78. Information required to identify data provider uniquely

79. Networking

80. Information solicited by the social network to be released to its other users

81. Content

82. Actual content with which the data provider participates in network

83. Activity

85. Purpose

86. Visibility

87. Granularity

89. Practically everything ...

90. Application Terms of Service

91. "Facebook may...provide developers access to...your name, your profile picture, your gender, your birthday, your hometown location...your current location...your political view, your activities, your interests...your relationship status, your dating interests, your relationship interests, your summer plans, your Facebook user network affiliations, your education history, your work history,...copies of photos in your Facebook Site photo albums...a list of user IDs mapped to your Facebook friends."

92. If you set your profile to private and one of your friends adds an application, most of your profile information that is visible to your friend is also available to the application developer -- even if you yourself have not installed the application

95. Facebook's Privacy Policy Statement Comparison with other OSNs

96. Current Facebook privacy settings

97. Friend comparison Allow users to declare best friends and compare friend traits Casual communication Allow users to exchange messages and write on each other's wall Rating/Recommendation Enables users to review, compare and recommend items Gestures Allows users to perform virtual gestures like poke and bite Self expression Enables users to express moods, political opinion etc Gifting Enables users to exchange gifts Categories of OSN applications Category Description

98. Average Age Distribution

99. Age Distribution per site

100. Average user per site

101. Average user per site

103. LinkedIn has an average user age of 44

104. The average Twitter user is 39 years old

105. The average Facebook user is 38 years old

107. Why are people playing?

108. Disclosures on OSNs

109. Who is spending the most time on OSN?

110. Profile of virtual world users

111. The Hypothesis H0 : Classification based on number of years in Facebook and the number of hours spent each week on Facebook are independent H1 : Classification based on number of years in Facebook and the number of hours spent each week on Facebook are not independent

112. The Hypothesis

113. The Tests Therefore we can say that number of years on FB and number of hours spent are not independent with a confidence level of 97.5%

115. Ravi Kumar, Jasmine Novak, Andrew Tomkins

116. "Social network use and personality"

117. YairAmichai-Hamburger, Gideon Vinitzky

118. "Modelling relationship strength in Online Social Networks"

119. Rongjing Xiang, Jennifer Neville, Monica Rogati

120. "All about me: Disclosure in Online Social Networking profile : The case of Facebook"

121. Amanda Nosko, Eileen Wood, SeijaMolema

122. "Analyzing patterns of user content generation in Online Social Networks"

123. Lei Guo, Enhua Tan, Songqing Chen, Xiaodong Zhang, Yihong Zhao

124. The long tail of social networking sites

125. Albrecht Enders, HaraldHungenberg, Hans-Peter Denker

126. What do people ask their social networks and why?