@inproceedings{tagarev-etal-2021-tackling,
title = "Tackling Multilinguality and Internationality in Fake News",
author = "Tagarev, Andrey and
Bozhanova, Krasimira and
Nikolova-Koleva, Ivelina and
Ivanov, Ivan",
editor = "Mitkov, Ruslan and
Angelova, Galia",
booktitle = "Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2021)",
month = sep,
year = "2021",
address = "Held Online",
publisher = "INCOMA Ltd.",
url = "https://aclanthology.org/2021.ranlp-1.154",
pages = "1380--1386",
abstract = "The last several years have seen a massive increase in the quantity and influence of disinformation being spread online. Various approaches have been developed to target the process at different stages from identifying sources to tracking distribution in social media to providing follow up debunks to people who have encountered the disinformation. One common conclusion in each of these approaches is that disinformation is too nuanced and subjective a topic for fully automated solutions to work but the quantity of data to process and cross-reference is too high for humans to handle unassisted. Ultimately, the problem calls for a hybrid approach of human experts with technological assistance. In this paper we will demonstrate the application of certain state-of-the-art NLP techniques in assisting expert debunkers and fact checkers as well as the role of these NLP algorithms within a more holistic approach to analyzing and countering the spread of disinformation. We will present a multilingual corpus of disinformation and debunks which contains text, concept tags, images and videos as well as various methods for searching and leveraging the content.",
}
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%0 Conference Proceedings
%T Tackling Multilinguality and Internationality in Fake News
%A Tagarev, Andrey
%A Bozhanova, Krasimira
%A Nikolova-Koleva, Ivelina
%A Ivanov, Ivan
%Y Mitkov, Ruslan
%Y Angelova, Galia
%S Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2021)
%D 2021
%8 September
%I INCOMA Ltd.
%C Held Online
%F tagarev-etal-2021-tackling
%X The last several years have seen a massive increase in the quantity and influence of disinformation being spread online. Various approaches have been developed to target the process at different stages from identifying sources to tracking distribution in social media to providing follow up debunks to people who have encountered the disinformation. One common conclusion in each of these approaches is that disinformation is too nuanced and subjective a topic for fully automated solutions to work but the quantity of data to process and cross-reference is too high for humans to handle unassisted. Ultimately, the problem calls for a hybrid approach of human experts with technological assistance. In this paper we will demonstrate the application of certain state-of-the-art NLP techniques in assisting expert debunkers and fact checkers as well as the role of these NLP algorithms within a more holistic approach to analyzing and countering the spread of disinformation. We will present a multilingual corpus of disinformation and debunks which contains text, concept tags, images and videos as well as various methods for searching and leveraging the content.
%U https://aclanthology.org/2021.ranlp-1.154
%P 1380-1386
Markdown (Informal)
[Tackling Multilinguality and Internationality in Fake News](https://aclanthology.org/2021.ranlp-1.154) (Tagarev et al., RANLP 2021)
ACL
- Andrey Tagarev, Krasimira Bozhanova, Ivelina Nikolova-Koleva, and Ivan Ivanov. 2021. Tackling Multilinguality and Internationality in Fake News. In Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2021), pages 1380–1386, Held Online. INCOMA Ltd..