A hybrid feature selection method for predicting user influence on Twitter

Yan Mei*, Zizhu Zhang, Weiliang Zhao, Jian Yang, Robertus Nugroho

*Corresponding author for this work

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

Abstract

This paper proposes a hybrid feature selection method for predicting user influence on Twitter. A set of candidate features from Twitter is identified based on the five attributes of influencers defined in sociology. Firstly, less relevant features are filtered out with a featureweighting algorithm. Then the Sequential Backward Floating Selection is utilized as the search strategy. A Back Propagation Neural Network is employed to evaluate the feature subset at each step of searching. Finally, an optimal feature set is obtained for predicting user influence with a high degree of accuracy. Experimental results are provided based on a real world Twitter dataset including seven million tweets associated with 200 popular users. The proposed method can provide a set of features that could be used as a solid foundation for studying complicated user influence evaluation and prediction.

Original languageEnglish
Title of host publicationWeb Information Systems Engineering – WISE 2015
Subtitle of host publication16th International Conference, Miami, FL, USA, November 1-3, 2015, Proceedings, Part 1
EditorsJianyong Wang, Wojciech Cellary, Dingding Wang, Hua Wang, Shu-Ching Chen, Tao Li, Yanchun Zhang
Place of PublicationCham
PublisherSpringer, Springer Nature
Pages478-492
Number of pages15
Volume9418
ISBN (Electronic)9783319261904
ISBN (Print)9783319261898
DOIs
Publication statusPublished - 2015
Event16th International Conference on Web Information Systems Engineering, WISE 2015 - Miami, United States
Duration: 1 Nov 20153 Nov 2015

Publication series

NameLecture Notes in Computer Science
PublisherSpringer International Publishing
Volume9418
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other16th International Conference on Web Information Systems Engineering, WISE 2015
CountryUnited States
CityMiami
Period1/11/153/11/15

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