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

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

5 Citations (Scopus)
21 Downloads (Pure)

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 languageEnglish
Title of host publicationAlgorithms and Models for the Web Graph
Subtitle of host publication11th International Workshop, WAW 2014, Beijing, China, December 17-18, 2014, Proceedings
EditorsAnthony Bonata, Fan Chung Chung, Pawel Pralat
Place of PublicationCham, Switzerland
PublisherSpringer
Pages132-147
Number of pages16
ISBN (Electronic)978-3-319-13123-8
ISBN (Print)978-3-319-13123-8
DOIs
Publication statusPublished - 17 Dec 2014
Event11th International Workshop Algorithms and Models for the Web Graph, WAW 2014 - Beijing, China
Duration: 17 Dec 201418 Dec 2014
Conference number: 11

Publication series

NameLecture Notes in Computer Science
PublisherSpringer International Publishing
Volume8882
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Workshop

Workshop11th International Workshop Algorithms and Models for the Web Graph, WAW 2014
Abbreviated titleWAW
CountryChina
CityBeijing
Period17/12/1418/12/14

Keywords

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

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  • 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.), Algorithms and Models for the Web Graph: 11th International Workshop, WAW 2014, Beijing, China, December 17-18, 2014, Proceedings (pp. 132-147). (Lecture Notes in Computer Science; Vol. 8882). Cham, Switzerland: Springer. https://doi.org/10.1007/978-3-319-13123-8_11