Towards the prediction problems of bursting hashtags on T witter

Hundreds of thousands of hashtags are generated every day on T witter. Only a few will burst and become trending topics. In this article, we provide the definition of a bursting hashtag and conduct a systematic study of a series of challenging prediction problems that span the entire life cycles of...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Journal of the Association for Information Science and Technology 2015-12, Vol.66 (12), p.2566-2579
Hauptverfasser: Kong, Shoubin, Ye, Fei, Feng, Ling, Zhao, Zhe
Format: Artikel
Sprache:eng
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Hundreds of thousands of hashtags are generated every day on T witter. Only a few will burst and become trending topics. In this article, we provide the definition of a bursting hashtag and conduct a systematic study of a series of challenging prediction problems that span the entire life cycles of bursting hashtags. Around the problem of “how to build a system to predict bursting hashtags,” we explore different types of features and present machine learning solutions. On real data sets from Twitter, experiments are conducted to evaluate the effectiveness of the proposed solutions and the contributions of features.
ISSN:2330-1635
2330-1643
DOI:10.1002/asi.23342