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ZENODO
Dataset . 2019
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2019
License: CC BY
Data sources: ZENODO
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2019
License: CC BY
Data sources: Datacite
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FIRE 2018 IRMiDis track dataset: Fact-checkable tweets posted during disasters

Research datakeyboard_double_arrow_right Dataset 01 Jan 2019Publisher:Zenodo
Authors: Basu, Moumita; Ghosh, Saptarshi; Ghosh, Kripabandhu;

doi: 10.5281/zenodo.3336477 , 10.5281/zenodo.3336476

FIRE 2018 IRMiDis track dataset: Fact-checkable tweets posted during disasters

Abstract

This is the dataset used for the FIRE 2018 track on Information Retrieval from Microblogs during Disasters (IRMiDis). The dataset contains ~50K tweets (microblogs) and ~6.8K news articles posted after the 2015 Nepal earthquake. The dataset can be used for tasks such as: (i) Identifying fact-checkable tweets from among tweets posted during a disaster -- the dataset includes a gold standard set of fact-checkable tweets, (2) Identifying news articles supporting / opposing a fact-checkable tweet, etc.

If you use this dataset, please cite the following paper: Moumita Basu, Saptarshi Ghosh, Kripabandhu Ghosh. Overview of the FIRE 2018 track: Information Retrieval from Microblogs during Disasters (IRMiDis). Proceedings of the Annual Meeting of the Forum for Information Retrieval Evaluation (FIRE), Gandhinagar, India, pp. 1-5, December 2018.

Keywords

Disaster, Twitter, Microblogs, Fact-checkable, News articles

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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
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