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Toward A Multilingual and Multimodal Data Repository for COVID-19 Disinformation
Proc. - IEEE Int. Conf. Big Data, Big Data ; : 4325-4330, 2020.
Article in English | Scopus | ID: covidwho-1186070
ABSTRACT
The COVID-19 epidemic is considered as the global health crisis of the whole society and the greatest challenge mankind faced since World War Two. Unfortunately, the fake news about COVID-19 is spreading as fast as the virus itself. The incorrect health measurements, anxiety, and hate speeches will have bad consequences on people's physical health, as well as their mental health in the whole world. To help better combat the COVID-19 fake news, we propose a new fake news detection dataset MM-COVID1 (Multilingual and Multidimensional COVID-19 Fake News Data Repository). This dataset provides the multilingual fake news and the relevant social context. We collect 3981 pieces of fake news content and 7192 trustworthy information from English, Spanish, Portuguese, Hindi, French and Italian, 6 different languages. We present a detailed and exploratory analysis of MM-COVID from different perspectives. © 2020 IEEE.

Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: Proc. - IEEE Int. Conf. Big Data, Big Data Year: 2020 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: Proc. - IEEE Int. Conf. Big Data, Big Data Year: 2020 Document Type: Article