TY - GEN
T1 - COVID-19 in Bulgarian Social Media
T2 - International Conference on Recent Advances in Natural Language Processing: Deep Learning for Natural Language Processing Methods and Applications, RANLP 2021
AU - Nakov, Preslav
AU - Alam, Firoj
AU - Shaar, Shaden
AU - da San Martino, Giovanni
AU - Zhang, Yifan
N1 - Publisher Copyright:
© 2021 Incoma Ltd. All rights reserved.
PY - 2021
Y1 - 2021
N2 - With the emergence of the COVID-19 pandemic, the political and the medical aspects of disinformation merged as the problem got elevated to a whole new level to become the first global infodemic. Fighting this infodemic is currently ranked very high on the list of priorities of the World Health Organization, with dangers ranging from promoting fake cures, rumors, and conspiracy theories to spreading xenophobia and panic. With this in mind, we studied how COVID-19 is discussed in Bulgarian social media in terms of factuality, harmfulness, propaganda, and framing. We found that most Bulgarian tweets contain verifiable factual claims, are factually true, are of potential public interest, are not harmful, and are too trivial to fact-check; moreover, zooming into harmful tweets, we found that they spread not only rumors but also panic. We further analyzed articles shared in Bulgarian partisan pro/con-COVID-19 Facebook groups and found that propaganda is more prevalent in skeptical articles, which use doubt, flag waving, and slogans to convey their message; in contrast, concerned ones appeal to emotions, fear, and authority; moreover, skeptical articles frame the issue as one of quality of life, policy, legality, economy, and politics, while concerned articles focus on health & safety.
AB - With the emergence of the COVID-19 pandemic, the political and the medical aspects of disinformation merged as the problem got elevated to a whole new level to become the first global infodemic. Fighting this infodemic is currently ranked very high on the list of priorities of the World Health Organization, with dangers ranging from promoting fake cures, rumors, and conspiracy theories to spreading xenophobia and panic. With this in mind, we studied how COVID-19 is discussed in Bulgarian social media in terms of factuality, harmfulness, propaganda, and framing. We found that most Bulgarian tweets contain verifiable factual claims, are factually true, are of potential public interest, are not harmful, and are too trivial to fact-check; moreover, zooming into harmful tweets, we found that they spread not only rumors but also panic. We further analyzed articles shared in Bulgarian partisan pro/con-COVID-19 Facebook groups and found that propaganda is more prevalent in skeptical articles, which use doubt, flag waving, and slogans to convey their message; in contrast, concerned ones appeal to emotions, fear, and authority; moreover, skeptical articles frame the issue as one of quality of life, policy, legality, economy, and politics, while concerned articles focus on health & safety.
UR - https://www.scopus.com/pages/publications/85114467662
U2 - 10.26615/978-954-452-072-4_113
DO - 10.26615/978-954-452-072-4_113
M3 - Conference contribution
AN - SCOPUS:85114467662
T3 - International Conference Recent Advances in Natural Language Processing, RANLP
SP - 997
EP - 1009
BT - International Conference Recent Advances in Natural Language Processing, RANLP 2021
A2 - Angelova, Galia
A2 - Kunilovskaya, Maria
A2 - Mitkov, Ruslan
A2 - Nikolova-Koleva, Ivelina
PB - Incoma Ltd
Y2 - 1 September 2021 through 3 September 2021
ER -