A network framework for noisy label aggregation in social media

Xueying ZHAN, Yaowei WANG, Yanghui RAO, Haoran XIE, Qing LI, Fu Lee WANG, Tak Lam WONG

Research output: Book Chapters | Papers in Conference ProceedingsConference paper (refereed)

3 Citations (Scopus)

Abstract

This paper focuses on the task of noisy label aggregation in social media, where users with different social or culture backgrounds may annotate invalid or malicious tags for documents. To aggregate noisy labels at a small cost, a network framework is proposed by calculating the matching degree of a document’s topics and the annotators’ meta-data. Unlike using the back-propagation algorithm, a probabilistic inference approach is adopted to estimate network parameters. Finally, a new simulation method is designed for validating the effectiveness of the proposed framework in aggregating noisy labels.

Original languageEnglish
Title of host publicationProceedings of the 55th Annual Meeting of the Association for Computational Linguistics
Place of PublicationCanada
PublisherAssociation for Computational Linguistics (ACL)
Pages484-490
Number of pages7
Volume2
ISBN (Print)9781945626760
DOIs
Publication statusPublished - Jul 2017
Externally publishedYes
Event55th Annual Meeting of the Association for Computational Linguistics - Westin Bayshore Hotel, Vancouver, Canada
Duration: 30 Jul 20174 Aug 2017
http://acl2017.org

Publication series

NameACL 2017 - 55th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference (Long Papers)
Volume2

Conference

Conference55th Annual Meeting of the Association for Computational Linguistics
Abbreviated titleACL 2017
CountryCanada
CityVancouver
Period30/07/174/08/17
Internet address

Bibliographical note

The authors are thankful to the reviewers for their constructive comments and suggestions on this pa- per. The work described in this paper was support- ed by the National Natural Science Foundation of China (61502545), a grant from the Research Grants Council of the Hong Kong Special Admin- istrative Region, China (UGC/FDS11/E03/16), the Start-Up Research Grant (RG 37/2016-2017R), and the Internal Research Grant (RG 66/2016- 2017) of The Education University of Hong Kong.

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  • Cite this

    ZHAN, X., WANG, Y., RAO, Y., XIE, H., LI, Q., WANG, F. L., & WONG, T. L. (2017). A network framework for noisy label aggregation in social media. In Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Vol. 2, pp. 484-490). (ACL 2017 - 55th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference (Long Papers); Vol. 2). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/P17-2077