A novel topical authority-based microblog ranking

Yanmei Zhai, Xin Li*, Jialiang Chen, Xiumei Fan, Kwok Wai CHEUNG

*Corresponding author for this work

Research output: Chapter in book/report/conference proceedingConference contributionpeer-review

7 Citations (Scopus)

Abstract

The high volume of microblogs produced daily together with their rich social structure makes microblogs' better query and filtering ever challenging. In the literature, most of the existing ranking methods are based on the overall popularity of the authors and the tweets without considering author's expertise. In this paper, we propose the topical authority-based ranking methods for social networks like Twitter and investigate how the underlying topical feature modeling can be optimized for performance boosting. In particular, we present a detailed study on the empirical distributions of the topical features. We propose the use of specific parametric forms for different features, which we believe to be crucial as the value of the cumulative distribution function is explicitly used for topical authority ranking. We applied the extended topical authority-based ranking method to a Twitter dataset for ranking keyword-matched microblogs. The experimental results show that our proposed approach outperforms a number of existing approaches by a large margin which verify the effectiveness of our proposed features and the importance of the topical authority for ranking microblogs.

Original languageEnglish
Title of host publicationWeb Technologies and Applications - 16th Asia-Pacific Web Conference, APWeb 2014, Proceedings
PublisherSpringer Verlag
Pages105-116
Number of pages12
ISBN (Print)9783319111155
DOIs
Publication statusPublished - 2014
Event16th Asia-Pacific Web Conference on Web Technologies and Applications, APWeb 2014 - Changsha, China
Duration: 5 Sep 20147 Sep 2014

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8709 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference16th Asia-Pacific Web Conference on Web Technologies and Applications, APWeb 2014
Country/TerritoryChina
CityChangsha
Period5/09/147/09/14

Scopus Subject Areas

  • Theoretical Computer Science
  • Computer Science(all)

User-Defined Keywords

  • Feature Distribution
  • Microblog Ranking
  • Topical Authority

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