privacy and security implications of facebook groups

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S No Questions Asked | On a scale of 1-5, p1 p2 p3 p4 p5 1 Please specify how accessible or public you thought this information was. 5 5 5 4 5 2 How correctly/truly does the document reveal information/facts about you? 2 3 3 5 5 3 To what extent do you feel the attached document reveals information about your personal connections/friends? 2 3 2 3 4 4 How comfortable are you with people predicting your friend- circle/relationships based on the above? 1 2 3 4 5 5 How likely do you think it is that future employers will try and dig up this information about you? 3 2 4 4 5 6 If a future or current employer/company/college were to gain access to this information, do you feel it might hurt your career/professional growth? 2 4 3 4 3 7 Do you think this would be a problem were a parent or relative to see this information? 5 1 4 3 4 8 Does this highlight a privacy concern in your opinion? 3 4 4 4 2 9 Do you regret any of this public information that is already up on the social media platform? 2 3 3 2 1 10 Will you try and be more careful about your online profile hereon? 2 3 1 4 1 The IIITD Compliments Page | PSOSM | Aditya Gupta and Akanksha Singh 0 200 400 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 Activity by day of the week/by hour of day Monday Tuesday Wednesday Thursday Friday Saturday Sunday 0 5 10 15 20 25 Monday Tuesday Wednesday Thursday Friday Saturday Sunday Online FB Activity of IIITians by day of the Week 0 100 200 300 Feb Mar Apr May Jun Jul Aug Month-wise Activity (2012) 0 100 200 300 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 Time-Based Frequency of Posting 0 200 400 600 800 0 2 4 6 8 10 12 14 16 18 20 22 Time-Based Frequency of Comments 0 100 200 300 400 500 600 700 800 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 NUMBER OF COMMENTS NUMBER OF LIKES (EXACT) # of Likes per comment Posts on IIITD Comp: Total Comments: Total (1082 liked) Likes: Total (7400 on comments) People: Total (tagged 324 posts) 900+ 4081 14k 800 Above Graphs: Entire Network coloured on Eigenvector Importance - with IIITD Network on IIITD Compliments 0 20 40 60 80 100 120 20 Most Active (comments): [ Hidden for your Privacy ] # of Conversations Shared Average # of People shared with (of 800) 1 8.9325 2 2.01 3 0.795 4 0.41 5 0.2075 Hour of Day 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 Monday 1 3 8 8 4 8 2 2 7 3 24 48 26 33 87 34 46 25 7 1 0 0 0 0 Tuesday 1 1 1 1 3 8 8 4 3 1 9 8 12 12 6 7 28 28 21 5 8 4 3 Wednesday 1 1 3 1 1 3 2 0 2 17 2 3 7 2 7 7 53 72 86 138 47 15 0 3 Thursday 4 1 4 7 13 11 18 10 9 4 18 42 97 69 39 62 47 41 117 122 41 9 8 4 Friday 2 1 3 2 6 8 23 8 8 11 9 1 14 6 19 16 66 60 43 316 207 28 5 2 Saturday 1 1 1 7 15 15 37 23 25 22 38 41 36 30 54 47 30 51 62 29 7 5 2 6 Sunday 0 1 0 4 4 5 7 5 5 10 15 23 62 59 56 42 87 158 86 28 9 15 4 3 Scoring Metric: Directed +1 per like, Undirected +4(3) per comment conversation - with past work suggesting 4/1 marketing rate of comments/likes Below: In order, top likers, top liked, most “popular”, least “popular”, top relationships, and top one-sided relationships – with at least 10 likes in or out (unless specified) Person Likes Received Akshit Nanda 264 Prakhar Gupta 206 Lakshay Pandey 157 Sumit AggerWal 142 Arjun Ahuja 139 Person Likes committed Jahnavi Kalyani 153 Arjun Ahuja 146 Sakshi Saini 137 Tuhi Nanshu 136 Purujit Negi 136 Most Popular Score Maneet Singh 0.95 Sanchit Sharma 0.944444 Tushar Gupta 0.928571 Ankit Agarwal 0.928571 Prateek Gaur 0.923077 Akanksha Cullen 0.923077 Abhi. Gautam 0.921053 Sanchit Garg 0.916667 Score Threshold Relationships identified Density 1 6359 0.009948 3 3719 0.005818 5 1249 0.001954 7 875 0.001369 9 539 0.000843 Relationship Score Person1 Person2 79.5 PrEeti Singh Khushboo Mandal 62.5 Sakshi Saini Purujit Negi 59.5 PrEeti Singh Jyoti Gangwar 57.25 Purujit Negi Akshit Nanda 56.5 Utkarsha Bhardwaj Purujit Negi 55.25 Anish Kumar Akshit Nanda 52 Purujit Negi Apoorv Saini 49.25 Priyanshi Mittal Mannika Solanki 48.25 PrEeti Singh Kriti Pandey 47.5 Tuhi Nanshu Akshit Nanda 47 Utkarsha Bhardwaj Akshit Nanda 45.25 Surabhi Kabby Kabra Priyanshi Mittal 45 Sumit AggerWal Purujit Negi 44.5 Kshitiz Bakshi Kirti Lamba 42.5 Srishty Grover Priyanshi Mittal 41 Srishty Grover Akshit Nanda 41 Tanya Mishra Sakshi Saini Ratio of likes of liker/liked Total likes between (filtered for 7+) Liker Liked 1 14 Khushboo Mandal Kriti Pandey 1 11 Tanya Mishra Sakshi Saini 1 10 Inshu Kumar Chugh Prakhar Gupta 1 9 Tuhi Nanshu Lakshay Pandey 1 9 Jahnavi Kalyani Lakshay Pandey 1 8 Jahnavi Kalyani Prakhar Gupta 1 7 Tuhi Nanshu Anish Kumar 1 7 Sampoorna Biswas Akshit Nanda 1 7 Jahnavi Kalyani Sumit AggerWal 1 7 Divya Bansal Lakshay Pandey 1 7 Arjun Ahuja Sumit AggerWal 1 7 Apoorv Saini Sumit AggerWal 0.92 25 Tuhi Nanshu Akshit Nanda 0.866667 15 Purujit Negi Sumit AggerWal Person Eigenvector Centrality Purujit Negi 0.011791 Prakhar Gupta 0.010965 Nikhil Nagpal 0.010064 Arjun Ahuja 0.010064 Sakshi Saini 0.009914 Siddharth Gupta 0.008787 Srishty Grover 0.008487 Akshit Nanda 0.008487 Deepak Wali 0.008412 Utkarsh Bhardwaj 0.008412 Bijender Rai 0.008261 Amol Verma 0.008261 Shayan Lahiri 0.008036 1 2 4 8 16 32 64 128 256 1 20 400 Likes in/Likes Out Correlation Pearson’s Correlation: 0.65 Avg. of 4.10 likes per comment with likes Person Hub or Importance Purujit Negi 0.011791 Prakhar Gupta 0.010965 Nikhil Nagpal 0.010064 Arjun Ahuja 0.010064 Sakshi Saini 0.009914 Siddharth Gupta 0.008787 Srishty Grover 0.008487 Akshit Nanda 0.008487 Deepak Wali 0.008412 Utkarsha Bhardwaj 0.008412 Bijender Rai 0.008261 Amol Verma 0.008261 Shayan Lahiri 0.008036 Clustered Groups (7 clusters) “Importance” Highest In-Between-ness (Occurrence in shortest paths) Min-Hops to Farthest Self-Likers # of Likes Akshit Nanda 2 Aman Singhal 2 Anjali Ujjainia 4

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Company Proprietary and Confidential Copyright Info Goes Here Just Like This

S No Questions Asked | On a scale of 1-5, p1 p2 p3 p4 p5

1Please specify how accessible or public you thought this information was.

5 5 5 4 5

2How correctly/truly does the document reveal information/facts about you?

2 3 3 5 5

3To what extent do you feel the attached document reveals information about your personal connections/friends?

2 3 2 3 4

4How comfortable are you with people predicting your friend-circle/relationships based on the above?

1 2 3 4 5

5How likely do you think it is that future employers will try and dig up this information about you?

3 2 4 4 5

6If a future or current employer/company/college were to gain access to this information, do you feel it might hurt your career/professional growth?

2 4 3 4 3

7Do you think this would be a problem were a parent or relative to see this information?

5 1 4 3 4

8 Does this highlight a privacy concern in your opinion? 3 4 4 4 2

9Do you regret any of this public information that is already up on the social media platform?

2 3 3 2 1

10 Will you try and be more careful about your online profile hereon? 2 3 1 4 1

The IIITD Compliments Page | PSOSM | Aditya Gupta and Akanksha Singh

0

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0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

Activity by day of the week/by hour of day

Monday Tuesday Wednesday Thursday Friday Saturday Sunday

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25

Monday Tuesday Wednesday Thursday Friday Saturday Sunday

Online FB Activity of IIITians by day of the Week

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Feb Mar Apr May Jun Jul Aug

Month-wise Activity (2012)

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100

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300

7 8 9 10 11 12 13 14 15 16 17 18 19 20 21

Time-Based Frequency of Posting

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600

800

0 2 4 6 8 10 12 14 16 18 20 22

Time-Based Frequency of Comments

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400

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800

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25

NU

MB

ER O

F C

OM

MEN

TS

NUMBER OF LIKES (EXACT)

# of Likes per comment

Posts on IIITD Comp: TotalComments: Total (1082 liked)Likes: Total (7400 on comments)People: Total (tagged 324 posts)

900+

408114k800

Above Graphs:Entire Network coloured on Eigenvector Importance - with IIITD Network on IIITD Compliments

0

20

40

60

80

100

120

20 Most Active (comments):

[ Hidden for your Privacy ]

# of

Conversations

Shared

Average # of

People shared

with (of 800)1 8.9325

2 2.01

3 0.795

4 0.41

5 0.2075

Hour of Day 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23Monday 1 3 8 8 4 8 2 2 7 3 24 48 26 33 87 34 46 25 7 1 0 0 0 0Tuesday 1 1 1 1 3 8 8 4 3 1 9 8 12 12 6 7 28 28 21 5 8 4 3

Wednesday 1 1 3 1 1 3 2 0 2 17 2 3 7 2 7 7 53 72 86 138 47 15 0 3Thursday 4 1 4 7 13 11 18 10 9 4 18 42 97 69 39 62 47 41 117 122 41 9 8 4Friday 2 1 3 2 6 8 23 8 8 11 9 1 14 6 19 16 66 60 43 316 207 28 5 2Saturday 1 1 1 7 15 15 37 23 25 22 38 41 36 30 54 47 30 51 62 29 7 5 2 6Sunday 0 1 0 4 4 5 7 5 5 10 15 23 62 59 56 42 87 158 86 28 9 15 4 3

Scoring Metric:Directed +1 per like, Undirected +4(3) per comment conversation -with past work suggesting 4/1 marketing rate of comments/likes

Below:

In order, top likers, top liked, most “popular”, least “popular”, toprelationships, and top one-sided relationships – withat least 10 likes in or out (unless specified)

Person Likes Received

Akshit Nanda 264

Prakhar Gupta 206

Lakshay Pandey 157

Sumit AggerWal 142

Arjun Ahuja 139

Person Likes committed

Jahnavi Kalyani 153

Arjun Ahuja 146

Sakshi Saini 137

Tuhi Nanshu 136

Purujit Negi 136

Most Popular ScoreManeet Singh 0.95

Sanchit Sharma 0.944444

Tushar Gupta 0.928571

Ankit Agarwal 0.928571

Prateek Gaur 0.923077

Akanksha Cullen 0.923077

Abhi. Gautam 0.921053

Sanchit Garg 0.916667

Score Threshold

Relationships identified

Density

1 6359 0.009948

3 3719 0.005818

5 1249 0.001954

7 875 0.001369

9 539 0.000843

Relationship Score Person1 Person279.5 PrEeti Singh Khushboo Mandal62.5 Sakshi Saini Purujit Negi59.5 PrEeti Singh Jyoti Gangwar

57.25 Purujit Negi Akshit Nanda56.5 Utkarsha Bhardwaj Purujit Negi

55.25 Anish Kumar Akshit Nanda52 Purujit Negi Apoorv Saini

49.25 Priyanshi Mittal Mannika Solanki48.25 PrEeti Singh Kriti Pandey47.5 Tuhi Nanshu Akshit Nanda47 Utkarsha Bhardwaj Akshit Nanda

45.25 Surabhi Kabby Kabra Priyanshi Mittal45 Sumit AggerWal Purujit Negi

44.5 Kshitiz Bakshi Kirti Lamba42.5 Srishty Grover Priyanshi Mittal41 Srishty Grover Akshit Nanda41 Tanya Mishra Sakshi Saini

Ratio of

likes of

liker/liked

Total likes

between (filtered for 7+)

Liker Liked

1 14 Khushboo Mandal Kriti Pandey

1 11 Tanya Mishra Sakshi Saini

1 10 Inshu Kumar Chugh Prakhar Gupta

1 9 Tuhi Nanshu Lakshay Pandey

1 9 Jahnavi Kalyani Lakshay Pandey

1 8 Jahnavi Kalyani Prakhar Gupta

1 7 Tuhi Nanshu Anish Kumar

1 7 Sampoorna Biswas Akshit Nanda

1 7 Jahnavi Kalyani Sumit AggerWal

1 7 Divya Bansal Lakshay Pandey

1 7 Arjun Ahuja Sumit AggerWal

1 7 Apoorv Saini Sumit AggerWal

0.92 25 Tuhi Nanshu Akshit Nanda

0.866667 15 Purujit Negi Sumit AggerWal

PersonEigenvector

CentralityPurujit Negi 0.011791

Prakhar Gupta 0.010965

Nikhil Nagpal 0.010064

Arjun Ahuja 0.010064

Sakshi Saini 0.009914

Siddharth Gupta 0.008787

Srishty Grover 0.008487

Akshit Nanda 0.008487

Deepak Wali 0.008412

Utkarsh Bhardwaj 0.008412

Bijender Rai 0.008261

Amol Verma 0.008261

Shayan Lahiri 0.008036

1

2

4

8

16

32

64

128

256

1 20 400

Likes in/Likes Out Correlation

Pearson’s Correlation: 0.65

Avg. of 4.10 likes per comment with likes Person

Hub or

ImportancePurujit Negi 0.011791

Prakhar Gupta 0.010965

Nikhil Nagpal 0.010064

Arjun Ahuja 0.010064

Sakshi Saini 0.009914

Siddharth Gupta 0.008787

Srishty Grover 0.008487

Akshit Nanda 0.008487

Deepak Wali 0.008412

Utkarsha Bhardwaj 0.008412

Bijender Rai 0.008261

Amol Verma 0.008261

Shayan Lahiri 0.008036

Clustered Groups (7 clusters)

“Importance”

Highest In-Between-ness (Occurrence in shortest paths)

Min-Hops to Farthest

Self-Likers # of Likes

Akshit Nanda 2

Aman Singhal 2

Anjali Ujjainia 4