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TW

ITTER

What is Twitter,a Social Network or a News

Media?

Haewoon Kwak Changhyun Lee Hosung Park Sue Moon

Department of Computer Science, KAIST, Korea

19th International World Wide Web Conference (WWW2010)

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Twitter, a microblog service

write a short message

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Twitter, a microblog service

read neighbors’ tweets

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In most OSN

“We are friends.”

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In Twitter

“I follow you.”

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Following on Twitter

“Unlike most social networks, following on

Twitter is not mutual.  Someone who thinks you're interesting can follow you, and you don't have to approve, or follow back."

http://help.twitter.com/entries/14019-what-is-following6

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Following = subscribing tweets

recent tweets of followings

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The goal of this work

•We analyze how directed relations of following set Twitter apart from existing OSNs.

•Then, we see if Twitter has any characteristics of news media.

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me⋅di⋅a [mee-dee-uh]

1.a pl. of medium

2.the means of communication, as radio and television, newspapers, and magazines, that reach or influence people widely

http://dictionary.reference.com/

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The goal of this work

•We analyze how directed relations of following set Twitter apart from existing OSNs.

•Then, we see if Twitter has any characteristics of news media.

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Summary of our findings

1.Following is mostly not reciprocated (not so “social”)

2.Users talk about timely topics

3.A few users reach large audience directly

4.Most users can reach large audience by Word of Mouth (WOM) quickly

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Data collection (2009/06/01~09/24)

•41.7M user profiles (near-complete at that time)

•1.47B following relations

•4262 trending topics

•106M tweets mentioning trending topics

‣ Spam tweets removed by CleanTweets

*http://an.kaist.ac.kr/traces/WWW2010.html

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How we crawled

•Twitter’s well-defined 3rd party API

•With 20+ ‘whitelisted’ IPs

‣ Send total 20,000 requests per IP / hour

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Recent studies

•Ranking methodologies [WSDM’10]

•Predicting movie profits [HYPERTEXT’10]

•Recommending users [CHI’10 microblogging]

•Detecting real time events [WWW’10]

•The ‘entire’ Twittersphere unexplored

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Part I.

1.Following is mostly not reciprocated (not so “social”)

2.Users talk about timely topics

3.A few users reach large audience directly

4.Most users can reach large audience by WOM* quickly

2.

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Why do people follow others?

•Reflection of offline social relationships

•Subscription to others’ messages

otherwise,

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Sociologists’ answer

•“Reciprocal interactions pervade every relation of primitive life and in all social systems”

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Is following reciprocal?

•Only 22.1% of user pairs follow each other

•Much lower than

‣ 68% on Flickr

‣ 84% on Yahoo! 360

‣ 77% on Cyworld guestbook messages

2.

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Low reciprocity of following

•Following is not similarly used as friend in OSNs

‣ Not really reflection of offline social relationships

•Active subscription of tweets!

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Part II.

1.Following is mostly not reciprocated (not so “social”)

2.Users talk about timely topics

3.A few users reach large audience directly

4.Most users can reach large audience by WOM* quickly

1.

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Dynamically changing trends

1.

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User participation pattern can be a

signature of a topic

1.

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Majority of topics are headline

54.3%“headline news”

31.5%“ephemeral”

6.9%7.3%

“persistent news”

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Part III.

1.Following is mostly not reciprocated (not so “social”)

2.Users talk about timely topics

3.A few users reach large audience directly

4.Most users can reach large audience by WOM* quickly

3.

A F

EW

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BS

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How many followers a user has?

3.

A F

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P(x)dx

CCDF

•Complementary Cumulative Density Function

•CCDF(x=k) =

3.

A F

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BS

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Reading the graph

3.

A F

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Plenty of super-hubs

3.

A F

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More super-hubs than projected by power-law

•Where do they get all the followers? Possibly from...

‣ Search by ‘name’

‣ Recommendation by Twitter

•They reach millions in one hop

3.

A F

EW

HU

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Are those who have many followers active?

3.

A F

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How we plotted

3.

A F

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How we plotted

Avg. = 8×Med. = 9

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More followers, more tweets

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A F

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Many followers without activity

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A F

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Twitter user rankings by Followers, PageRank and

RT

3.

A F

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Twitter user rankings by Followers, PageRank and

RT

3.

A F

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Great discrepancy among rankings

Kan

dal’s

tau

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corr

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Top k ranking

# followers (RF), PageRank (RPR) # retweets (RRT )

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Part IV.

1.Following is mostly not reciprocated (not so “social”)

2.Users talk about timely topics

3.A few users reach large audience directly

4.Most users can reach large audience by WOM* quickly

5.*WOM: word-of-mouth

4.

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Which is more efficient for WOM?

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In Twitter

Following

Information

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Average path length: 4.1

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Retweet (RT)

•Relay tweets from a following to followers

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Retweet (RT)

•Relay tweets from a following to followers

Last day of WWW’10

node 0

4.

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Retweet (RT)

•Relay tweets from a following to followers

Last day of WWW’10

Last day of WWW’10

Last day of WWW’10

Last day of WWW’10

4.

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Retweet (RT)

•Relay tweets from a following to followers

RT @node0 Last day of WWW’10node 4

4.

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Retweet (RT)

•Relay tweets from a following to followersRT @node0 Last day of WWW’10

RT @node0 Last day of WWW’10

RT @node0 Last day of WWW’10

4.

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Retweet (RT)

•Relay tweets from a following to followers

writer

retweeter

wr

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Retweet (RT)

•Not only 1 hop neighbors

1 hop neighbors

wr

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Retweet (RT)

•More goes further

2 hop neighbors

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wr

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We construct RT tree

•A tree with writer and retweeter(s)

wr

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Height of RT trees

r

W

r

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r r

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rr

r

1 1 2

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Empirical RT trees

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96% of RT trees = Height 1

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Boosting audience by RT

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Additional readers

3 followers

2 additional readers by retweeter

wr

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A retweet brings a few hundred additional

readers

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Time lag between hops in RT tree

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Fast relaying tweets by RT:

35% of RT < 10 min.

4.

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Fast relaying tweets by RT:

55% of RT < 1hr.

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Summary

1.We study the entire Twittersphere

2.Low reciprocity distinguishes Twitter from OSNs

3.Twitter has characteristics of news media:

‣ Tweets mentioning timely topics

‣ Plenty of hubs reaching a large public directly

‣ Fast and wide spread of word-of-mouth

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