Stumbl: Using Facebook to Collect Rich Datasets for Opportunistic Networking Research

Thrasyvoulos Spyropoulos

EURECOM, France

Stumbl: Using Facebook to Collect Rich Datasets for Opportunistic Networking

ResearchTheus Hossmann

ETH Zürich, Switzerland

Franck Legendre ETH Zürich, Switzerland

Motivation

• Opportunistic Networks• Natural disasters (floods, earthquakes, etc.) • Political censorship (Egypt, ...) • Rural regions• Offloading infrastructure

• Traditional random protocols (e.g., epidemic routing) are inefficient!

• Patterns in human behavior help to improve efficiency

2hossmann@tik.ee.ethz.ch

Need to understand different aspects of human behaviorNeed to understand different aspects of human behavior

Motivation

3hossmann@tik.ee.ethz.ch

Mobility

Communi-cation

Social

?

Who meets whom?☞ Forwarding opportunity

Who knows whom?☞ Trust, altruism Who communicates

with whom?☞ Forwarding necessity

How do mobility, social and communication relate to each other

How do mobility, social and communication relate to each other

Motivation

4hossmann@tik.ee.ethz.ch

Mobility

Communi-cation

Social

?

Why? Difficult and expensive to make mesaurements in large scale!

Why? Difficult and expensive to make mesaurements in large scale!

Existing studies do not capture all dimensions and/or are limited in size

Existing studies do not capture all dimensions and/or are limited in size

Mobility trace analyses

[Tuduce 2006]

[Chaintreau 2007]

[and many more]

Mobility + Social

[Mtibaa 2008]

[Eagle 2009]

[Scellato 2010] Mobility + Social +

Comm.

[Pietiläinen 2009]

• FB users report whom of their friends they meet• Initialization phase

• Users choose a subset of their FB friends• Max 20 FB friends as Stumbl friends• Classified as: friend, family, colleague, acquaintance

• Reporting phase• Users report their face-to-face meetings every day• number of meetings, aggregate meeting time,

contexts of the meetings (work, fun, home, meal, other)

• Collecting interaction• Wall posts (messages, photos, videos, links)• Comments on wall posts• Likes

Stumbl Facebook Application

5hossmann@tik.ee.ethz.ch

http://apps.facebook.com/_stumbl/

http://apps.facebook.com/_stumbl/

Stumbl Experiment

• 39 Participants personally invitation (colleagues + friends)

• 3 weeks (August – September 2010)

• Incentives: Raffle• One winner after every week• Drawn at random with probability depending on

• # of days participated• # of friends participating

6hossmann@tik.ee.ethz.ch

Dataset

• On avg. 22 (of 39) users reported data per day

• On avg. a user selected 14 Stumbl friends• 11 users selected the maximum allowed 20 friends• “most social” user reported meetings with 17 friends

• 498 Facebook pairs• 47 with mutual meeting reports

• Validation of user reports• 86% of days, the reports of having a meeting match

7hossmann@tik.ee.ethz.ch

Dataset

• Number of unique friends met• Percentage of days a pair meets• Number of meetings per context

8hossmann@tik.ee.ethz.ch

Mob.

Soc. Com.

?

Less than 10 Facebook friends met during the 3 weeks on average

Less than 10 Facebook friends met during the 3 weeks on average

~5% of pairs meet every day~5% of pairs meet every day

Most meetings happen at workMost meetings happen at work

Dataset

• Number of pairs per social tie type

• Facebook communication events

9hossmann@tik.ee.ethz.ch

Mob.

Soc. Com.

?

Most Facebook friends you meet are friends (>60%)Most Facebook friends you meet are friends (>60%)

Posts Comments Likes Total

199 341 103 643

Results

• How long and often pairs meet per day,depending on social tie type?

10hossmann@tik.ee.ethz.ch

Mob.

Soc. Com.

?

The social tie type has very strong impact on meeting characteristics in terms of context, duration and

frequency of meetings ☞ Tie type is valueable data for routing

The social tie type has very strong impact on meeting characteristics in terms of context, duration and

frequency of meetings ☞ Tie type is valueable data for routing

Results

• How do your social relationship types influence communications?

11hossmann@tik.ee.ethz.ch

Mob.

Soc. Com.

?

Friends and family are the most communicative☞ Tie types should be considered in traffic modeling

Friends and family are the most communicative☞ Tie types should be considered in traffic modeling

Results

• Are we more or less likely to communicate with Stumbl vs. FB friends?

12hossmann@tik.ee.ethz.ch

Mob.

Soc. Com.

?

A Facebook user communicates 10x more with Stumbl friends

☞ Communication ties are more local than social ties

A Facebook user communicates 10x more with Stumbl friends

☞ Communication ties are more local than social ties

Outlook

• Extended analysis• Multi-relational graph analysis• Structure (communities, clustering, path lengths, etc.)?• Nodes (centrality rankings, etc.)?

• Sharing the data• Anonymization

• Bigger experiments! Incentives??• Incentives must not motivate false reports• Game mechanism?

13hossmann@tik.ee.ethz.ch

Please

HelpPlease

Help

Take Home Messages

• Stumbl uses Facebook to collect data about• Communication• Social Ties• Mobility

• Potential scalable way to collect data from large numbers of users!

• Preliminary experiment and analysis shows that• The social tie type has very strong impact on meeting

characteristics in terms of context, duration and frequency of meetings

• The social tie type has strong impact on how communicative a pair is

• Communication ties are more local than social ties

14hossmann@tik.ee.ethz.ch

http://apps.facebook.com/_stumbl/http://apps.facebook.com/_stumbl/

Thank you!

15hossmann@tik.ee.ethz.ch