Modelling of trends in Twitter using retweet graph dynamics

Marijn Ten Thij, Tanneke Ouboter, Daniël Worm, Nelli Litvak, Hans Leo van den Berg, Sandjai Bhulai

  • 4 Citations

Abstract

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.
Original languageUndefined
Title of host publicationProceedings 11th International Workshop Algorithms and Models for the Web Graph, WAW 2014
EditorsAnthony Bonata, Fan Chung Chung, Pawel Pralat
Place of PublicationSwitzerland
PublisherSpringer International Publishing
Pages132-147
Number of pages16
ISBN (Print)978-3-319-13123-8
DOIs
StatePublished - 17 Dec 2014

Publication series

NameLecture Notes in Computer Science
PublisherSpringer International Publishing
Number8882
Volume2014

Fingerprint

Graph
Simulation
Mathematical model

Keywords

  • EWI-25535
  • Twitter
  • Random graph model
  • METIS-309800
  • Retweet graph
  • IR-93646
  • Graph dynamics

Cite this

Ten Thij, M., Ouboter, T., Worm, D., Litvak, N., van den Berg, H. L., & Bhulai, S. (2014). Modelling of trends in Twitter using retweet graph dynamics. In A. Bonata, F. C. Chung, & P. Pralat (Eds.), Proceedings 11th International Workshop Algorithms and Models for the Web Graph, WAW 2014 (pp. 132-147). (Lecture Notes in Computer Science; Vol. 2014, No. 8882). Switzerland: Springer International Publishing. DOI: 10.1007/978-3-319-13123-8_11

Ten Thij, Marijn; Ouboter, Tanneke; Worm, Daniël; Litvak, Nelli; van den Berg, Hans Leo; Bhulai, Sandjai / Modelling of trends in Twitter using retweet graph dynamics.

Proceedings 11th International Workshop Algorithms and Models for the Web Graph, WAW 2014. ed. / Anthony Bonata; Fan Chung Chung; Pawel Pralat. Switzerland : Springer International Publishing, 2014. p. 132-147 (Lecture Notes in Computer Science; Vol. 2014, No. 8882).

Research output: Scientific - peer-reviewConference contribution

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Ten Thij, M, Ouboter, T, Worm, D, Litvak, N, van den Berg, HL & Bhulai, S 2014, Modelling of trends in Twitter using retweet graph dynamics. in A Bonata, FC Chung & P Pralat (eds), Proceedings 11th International Workshop Algorithms and Models for the Web Graph, WAW 2014. Lecture Notes in Computer Science, no. 8882, vol. 2014, Springer International Publishing, Switzerland, pp. 132-147. DOI: 10.1007/978-3-319-13123-8_11

Modelling of trends in Twitter using retweet graph dynamics. / Ten Thij, Marijn; Ouboter, Tanneke; Worm, Daniël; Litvak, Nelli; van den Berg, Hans Leo; Bhulai, Sandjai.

Proceedings 11th International Workshop Algorithms and Models for the Web Graph, WAW 2014. ed. / Anthony Bonata; Fan Chung Chung; Pawel Pralat. Switzerland : Springer International Publishing, 2014. p. 132-147 (Lecture Notes in Computer Science; Vol. 2014, No. 8882).

Research output: Scientific - peer-reviewConference contribution

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Ten Thij M, Ouboter T, Worm D, Litvak N, van den Berg HL, Bhulai S. Modelling of trends in Twitter using retweet graph dynamics. In Bonata A, Chung FC, Pralat P, editors, Proceedings 11th International Workshop Algorithms and Models for the Web Graph, WAW 2014. Switzerland: Springer International Publishing. 2014. p. 132-147. (Lecture Notes in Computer Science; 8882). Available from, DOI: 10.1007/978-3-319-13123-8_11