skip to main content
10.1145/2615569.2615655acmconferencesArticle/Chapter ViewAbstractPublication PageswebsciConference Proceedingsconference-collections
poster

Analysing the duration of trending topics in Twitter using wikipedia

Published: 23 June 2014 Publication History

Abstract

The analysis of trending topics in Twitter is a goldmine for a variety of studies and applications. However, the contents of topics vary greatly from daily routines to major public events, enduring from a few hours to weeks or months. It is thus helpful to distinguish trending topics related to real-world events with those originated within virtual communities. In this paper, we analyse trending topics in Twitter using Wikipedia as reference for studying the provenance of trending topics. We show that among different factors, the duration of a trending topic characterizes exogenous Twitter trending topics better than endogenous ones.

References

[1]
C. Li, J. Weng, Q. He, Y. Yao, A. Datta, A. Sun, and B.-S. Lee. Twiner: named entity recognition in targeted twitter stream. In SIGIR, pages 721--730, 2012.
[2]
Z. Ma, A. Sun, and G. Cong. On predicting the popularity of newly emerging hashtags in Twitter. JASIST, 64(7):1399--1410, 2013.
[3]
O. Tsur and A. Rappoport. What's in a hashtag?: content based prediction of the spread of ideas in microblogging communities. In WSDM, pages 643--652, 2012.

Cited By

View all
  • (2021)Understanding topic duration in Twitter learning communities using data miningJournal of Computer Assisted Learning10.1111/jcal.1263338:2(513-525)Online publication date: 10-Dec-2021
  • (2017)Understanding dynamics of trending topics in Twitter2017 International Conference on Computing, Communication and Automation (ICCCA)10.1109/CCAA.2017.8229780(98-103)Online publication date: May-2017
  • (2015)Tracing Shifts in Emotions in Streaming Social Network DataFoundations of Intelligent Systems10.1007/978-3-319-25252-0_31(280-289)Online publication date: 30-Dec-2015

Index Terms

  1. Analysing the duration of trending topics in Twitter using wikipedia

    Recommendations

    Comments

    Information & Contributors

    Information

    Published In

    cover image ACM Conferences
    WebSci '14: Proceedings of the 2014 ACM conference on Web science
    June 2014
    318 pages
    ISBN:9781450326223
    DOI:10.1145/2615569
    Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

    Sponsors

    Publisher

    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 23 June 2014

    Check for updates

    Author Tags

    1. temporal analysis
    2. time series
    3. twitter
    4. wikipedia

    Qualifiers

    • Poster

    Funding Sources

    Conference

    WebSci '14
    Sponsor:
    WebSci '14: ACM Web Science Conference
    June 23 - 26, 2014
    Indiana, Bloomington, USA

    Acceptance Rates

    WebSci '14 Paper Acceptance Rate 29 of 144 submissions, 20%;
    Overall Acceptance Rate 245 of 933 submissions, 26%

    Contributors

    Other Metrics

    Bibliometrics & Citations

    Bibliometrics

    Article Metrics

    • Downloads (Last 12 months)0
    • Downloads (Last 6 weeks)0
    Reflects downloads up to 19 Feb 2025

    Other Metrics

    Citations

    Cited By

    View all
    • (2021)Understanding topic duration in Twitter learning communities using data miningJournal of Computer Assisted Learning10.1111/jcal.1263338:2(513-525)Online publication date: 10-Dec-2021
    • (2017)Understanding dynamics of trending topics in Twitter2017 International Conference on Computing, Communication and Automation (ICCCA)10.1109/CCAA.2017.8229780(98-103)Online publication date: May-2017
    • (2015)Tracing Shifts in Emotions in Streaming Social Network DataFoundations of Intelligent Systems10.1007/978-3-319-25252-0_31(280-289)Online publication date: 30-Dec-2015

    View Options

    Login options

    View options

    PDF

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader

    Figures

    Tables

    Media

    Share

    Share

    Share this Publication link

    Share on social media