Event grounding from multimodal social network fusion

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)


This paper studies the problem of extracting realworld event information from social media streams. Although existing work focuses on event signals of bursty mentions extracted from a single-source of textual streams, these signals are likely to be noisy due to ambiguous occurrences of individual mentions. To extract accurate event signals, we propose a framework capable of "grounding" mentions to unique event using multiple social networks with complementary strength. We show that our framework jointly using multiple sources outperforms state-ofthe-Arts using publicly available datasets.

Original languageEnglish
Title of host publicationProceedings - 16th IEEE International Conference on Data Mining, ICDM 2016
EditorsFrancesco Bonchi, Xindong Wu, Ricardo Baeza-Yates, Josep Domingo-Ferrer, Zhi-Hua Zhou
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages6
ISBN (Electronic)9781509054725
Publication statusPublished - 2017 Jan 31
Event16th IEEE International Conference on Data Mining, ICDM 2016 - Barcelona, Catalonia, Spain
Duration: 2016 Dec 122016 Dec 15

Publication series

NameProceedings - IEEE International Conference on Data Mining, ICDM
ISSN (Print)1550-4786


Other16th IEEE International Conference on Data Mining, ICDM 2016
CityBarcelona, Catalonia

Bibliographical note

Funding Information:
This work was partly supported by Institute for Information & communications Technology Promotion(IITP) grant funded by the Korea government(MSIP) (No.B0101-16-0307, Basic Software Research in Human-level Lifelong Machine Learning (Machine Learning Center)) and this research was supported by the MSIP(Ministry of Science, ICT and Future Planning), Korea, under the ITRC(Information Technology Research Center) support program (IITP-2016-R2720-16-0007) supervised by the IITP(Institute for Information & communications Technology Promotion)

Publisher Copyright:
© 2016 IEEE.

All Science Journal Classification (ASJC) codes

  • Engineering(all)


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