Information propagationin the FlickrFlickr social

network

Meeyoung Chamcha@mpi-sws.mpg.de

Max Planck Institute for Software SystemsWith Alan Mislove and Krishna Gummadi

TU Berlin Deutsche Telekom Lab

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Diffusion of innovations How, why, and at what rate new ideas and technology spread

through cultures? [Rogers 1950s]

time

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Milgram’s Experiment Through which social links information flow?

160 people in NebraskaPass letters to a colleague socially close to themTowards a particular stockbroker in Boston [1960s]

It took Six hops to deliver each letter

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YouTubeYouTube FlickrFlickr

DeliciousDelicious

FriendsterFriendster

FacebookFacebook

OrkutOrkut

MySpaceMySpace

LiveJournLiveJournalal

CyworldCyworld

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Online social networks bring unique opportunityfor understanding information spreading

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Online social networks (OSN)

OSN websites are popular Used for a variety of information propagation purposes

Viral marketing, political campaign, content sharing, launch of movie trailers, product promotions, etc.

In 2007, $12 billion spent on advertisements in OSNs

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Information flow mechanisms

Featuring (front page, hotlists) External links Search results Links between content Online social links or word-of-mouth

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Two key questions Word-of-mouth expected to spread content widely and quickly

throughout the network

1. How widely does information propagate in social network? Do popular content reach different parts of the network?

2. How quickly does information spread through the social network? How long does it take for people to find content?

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Key challenge: Gathering the data

Flickr: Founded in 2004, acquired by Yahoo! in 2005 The largest photo sharing site User activities

Make friends Upload and tag photos Comment on photos Mark photos as favorites

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How does information propagate in Flickr?How does information propagate in Flickr?

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Methodology

Crawled a substantial fraction of Flickr social network 2.5M users and 33M friend links

(in its largest weakly connected component) Repeated the crawls for 104 consecutive days

Gathered Flickr users’ favorite-marked pictures 34M bookmarks of 11M distinct photos

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Largest OSN data analyzed for information flow to date!Largest OSN data analyzed

for information flow to date!

Part1. Measurementmethodology

Part2. How widely do

pictures spread?

Part3. How quickly do

pictures spread?

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Topological distribution of popularity

Popularity measured as the number of fans or favorite-marks

Three questions 1. Are globally popular pictures also popular locally? 2. What is the distance from uploaders of photos to fans? 3. What does the network of fans look like?

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Test of local and global popularity

250 random users Find top-100 photos (hotlist) within a k-hop neighborhood Compare local hotlist with global hotlist Degree of overlap reflects topological correlation in popularity

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Hotlist from 2-hop neighborhood

Photos popular in a local neighborhood (2-hop) different from globally popular ones

Photos popular in a local neighborhood (2-hop) different from globally popular ones

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Hotlists from 3-4 hop neighborhood

Top-100 photos from 4-hop neighborhoodsoverlap largely with global top-100 photosTop-100 photos from 4-hop neighborhoodsoverlap largely with global top-100 photos

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Distance from uploaders to fans

Very popular pictures with more than 500 fans

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uploader

46% fans1-hop away

45% fans2-hop away

9% fans3-hop away

High content locality for even popular photosHigh content locality for even popular photos

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Network structure of fans

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72% of pictures (>100 fans) with fans connecting each other

indicating a strong topological correlation

72% of pictures (>100 fans) with fans connecting each other

indicating a strong topological correlation

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Summary of spatial spreading patterns

Strong correlation between topology and content popularity Difference in local and global hotlists Concentration of fans around uploaders Most fans forming a single connected component

→ Even popular photos do not spread widely in the network

Part1. Measurementmethodology

Part2. How widely do

pictures spread?

Part3. How quickly do

pictures spread?

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Temporal evolution of photo popularity

Goal is to understand how quickly pictures obtain fans over time- focus on long-term trends for popular photos

Case study on three popularity growth patterns Long-term trends in popularity growth

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Pattern 1: steady-growth

Gain new fans at a relatively constant rate

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London cycling by lomokev

Linear pattern cannot be explained by existing theoriesLinear pattern cannot be explained by existing theories

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Pattern 2: growth-spike

Sudden increase in fans over a short time period

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One would. by antimethod

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Pattern 3: dormant

Unknown to many users or stop gaining fans

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Velcro being pulled apart by Trazy

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Pattern across all popular photos

5,346 photos (>1 year & >100 fans)

23Characteristic growth in first few days and constant growthCharacteristic growth in first few days and constant growth

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Pattern across a 2-year period

798 photos (>2 years & >100 fans)

24Even popular photos spread slowly throughout the networkEven popular photos spread slowly throughout the network

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Photos become popular with very different patterns Key patterns: steady-growth, growth-spike, dormant

Contrary to popular expectations about viral marketing, even popular pictures gain fans very slowly

Summary of temporal growth patterns

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Conclusion Largest scale analysis to investigate the role of OSN in

information propagation using real traces Even popular pictures do not spread widely and quickly

Data analysis shows different patterns from the common expectations about viral marketing

Calls for the better design of social network features that enable full viral speed as suggested in theory

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http://socialnetworks.mpi-sws.org/