Abstract
| Original language | English |
|---|---|
| Publication status | Published - 5 Jun 2014 |
| Event | Netsci 2014 - San Francisco, United States Duration: 2 Jun 2014 → … |
Scientific committee
| Scientific committee | Netsci 2014 |
|---|---|
| Country | United States |
| City | San Francisco |
| Period | 2/06/14 → … |
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Keywords
- criticality, Twitter, self-organization, statistical signal processing
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Fluctuations drive viral memes in online social media: "Integrating criticality into network science". / Sanli Cakir, Céyda; Lambiotte, Renaud.
2014. Poster session presented at Netsci 2014, San Francisco, United States.Research output: Contribution to conference › Poster
TY - CONF
T1 - Fluctuations drive viral memes in online social media: "Integrating criticality into network science"
AU - Sanli Cakir, Céyda
AU - Lambiotte, Renaud
PY - 2014/6/5
Y1 - 2014/6/5
N2 - Online social media allow users to publish materials and make them freely available for everyone. Research on Twitter has shown that the activity of different users are not independent. Moreover, if certain memes and hashtags are heavily propagated through retweets and mentions, a majority of them attracts no attention. This heterogenous virality could be explained by the fairly small fraction of “active” Twitter users. In analogy with disordered dense systems, e.g. jammed cars in traffic or glassy state of colloids, when the number of elements in a system increases beyond a critical value, a competition emerges for a restricted amount of sources. In this poster, we will present recent work where we analyse Twitter data available with statistical techniques developed for granular flows and argue that nature of fluctuations leading to criticality have a similar behavior.
AB - Online social media allow users to publish materials and make them freely available for everyone. Research on Twitter has shown that the activity of different users are not independent. Moreover, if certain memes and hashtags are heavily propagated through retweets and mentions, a majority of them attracts no attention. This heterogenous virality could be explained by the fairly small fraction of “active” Twitter users. In analogy with disordered dense systems, e.g. jammed cars in traffic or glassy state of colloids, when the number of elements in a system increases beyond a critical value, a competition emerges for a restricted amount of sources. In this poster, we will present recent work where we analyse Twitter data available with statistical techniques developed for granular flows and argue that nature of fluctuations leading to criticality have a similar behavior.
KW - criticality, Twitter, self-organization, statistical signal processing
M3 - Poster
ER -