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Competition among memes in a world with limited attention
Lilian Weng, Alessandro Flammini, Alessandro Vespignani and Filippo Menczer
*Center for Complex Networks and Systems Research School of Informatics and Computing Indiana University, Bloomington
*Department of Health Sciences, Department of Physics and College of Computer and Information Sciences, Northeastern University
Nature Scientific Report, 2012
Thursday, September 12, 13
#EpicTweets
#TheEpicTweet
Which hashtag is more popular?
Thursday, September 12, 13
#EpicTweets
#TheEpicTweet
66,376 RT
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10/1/2010 10/11/2010 10/21/2010 10/31/2010 11/10/2010 11/20/2010 11/30/2010 12/10/2010 12/20/2010 12/30/2010 1/9/2011 1/19/2011
mes
sage
s of
#th
eepi
ctw
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mes
sage
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#ep
ictw
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#epictweets
#theepictweets
14 RT
Thursday, September 12, 13
#BieberThing
#BieberFact
Which hashtag is more popular?
Thursday, September 12, 13
#BieberThing
#BieberFact
18 RT
97,523 RT
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10/1/2010 10/11/2010 10/21/2010 10/31/2010 11/10/2010 11/20/2010 11/30/2010 12/10/2010 12/20/2010 12/30/2010 1/9/2011 1/19/2011
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#bi
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sage
s of
#bi
eber
fact
#bieberfact
#bieberthing
Thursday, September 12, 13
They are similar, and they are competing!
Thursday, September 12, 13
Meme lifetime is the maximum number of
consecutive time units.
Competition is fierce.Only a few memes are long-lived; most are short-lived.
Thursday, September 12, 13
Competition is fierce.Only a few memes widely spread;most do not.
Meme popularity is the number of tweets
containing the meme.
Thursday, September 12, 13
How to represent the competition?
How to prove that the competition has an important role in shaping these two distributions?
Thursday, September 12, 13
Let’s design a model.
Thursday, September 12, 13
But what should it incorporate?
Thursday, September 12, 13
Users are more likely to retweet memes about which they posted in the past.
User has memory (attention)
Thursday, September 12, 13
Individual attention is independent from the system diversity.
User memory (attention) is bound
The breadth of attention of a user through Shannon entropy S = −Σi f(i) log f(i) where f(i) is the proportion of tweets generated by the user about meme i.
Thursday, September 12, 13
Here comes the Model
Each user has a memory and a screen, both with limited size. (a) Memes are propagated along follower links. (b) The memes received by a user appear on the screen. With probability pn, the user posts a new meme, which is stored in memory. (c) Otherwise, with probability 1 – pn, the user scans the screen. Each meme x in the screen catches the user's attention with probability pr. Then with probability pm a random meme from memory is triggered, or x is retweeted with probability 1 – pm. (d) All memes posted by the user are also stored in memory.
Thursday, September 12, 13
Features to reproduceThursday, September 12, 13
Features to reproduce
The number of tweets a user has produced.
The entropy of memes a user has tweeted
about.
Thursday, September 12, 13
Social network structure matters!Thursday, September 12, 13
Competition matters!Thursday, September 12, 13
Without assuming different intrinsic values among ideas, we can explain the heterogeneity of meme popularity, lifetime and user activity by a combination of (1) the social network structure and (2) the competition among memes for limited user attention.
Thursday, September 12, 13
Thank you!
Thursday, September 12, 13
