Modelling of trends in Twitter using retweet graph dynamics
| Autor: | Ten Thij, Marijn, Ouboter, Tanneke, Worm, Daniël, Litvak, Nelli, van den Berg, Hans Leo, Bhulai, Sandjai, Bonata, Anthony, Chung, Fan Chung, Pralat, Pawel |
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| Přispěvatelé: | Stochastic Operations Research |
| Jazyk: | angličtina |
| Rok vydání: | 2014 |
| Předmět: |
Connected component
Theoretical computer science EWI-25535 Computer science Graph dynamics IR-93646 02 engineering and technology Computer Science::Social and Information Networks Graph Computer Science::Computers and Society METIS-309800 020204 information systems Retweet graph 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Random graph model |
| Zdroj: | Lecture Notes in Computer Science ISBN: 9783319131221 WAW Algorithms and Models for the Web Graph: 11th International Workshop, WAW 2014, Beijing, China, December 17-18, 2014, Proceedings, 132-147 STARTPAGE=132;ENDPAGE=147;TITLE=Algorithms and Models for the Web Graph |
| ISSN: | 0302-9743 |
| DOI: | 10.1007/978-3-319-13123-8_11 |
| Popis: | In this paper we model user behaviour in Twitter to capture the emergence of trending topics. For this purpose, we first extensively analyse tweet datasets of several different events. In particular, for these datasets, we construct and investigate the retweet graphs. We find that the retweet graph for a trending topic has a relatively dense largest connected component (LCC). Next, based on the insights obtained from the analyses of the datasets, we design a mathematical model that describes the evolution of a retweet graph by three main parameters. We then quantify, analytically and by simulation, the influence of the model parameters on the basic characteristics of the retweet graph, such as the density of edges and the size and density of the LCC. Finally, we put the model in practice, estimate its parameters and compare the resulting behavior of the model to our datasets. |
| Databáze: | OpenAIRE |
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