Mining the Discussion of Monkeypox Misinformation on Twitter Using RoBERTa

Elroy, Or; Erokhin, Dmitry; Komendantova, Nadejda; Yosipof, Abraham

doi:10.1007/978-3-031-34111-3_36

Cited by 5 publications

(1 citation statement)

References 18 publications

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“…Furthermore, the rapid dissemination of this conspiracy theory led to people burning 5G towers in different regions in the United Kingdom [37]. Researchers from different disciplines have also investigated such patterns of web behavior related to the conspiracy theories associated with virus outbreaks of the past [38][39][40]. The recent outbreak of MVD followed by a warning signal (for testing purposes) sent by the United States Federal Emergency Management Agency (FEMA) to every TV, radio, and cellphone in the U.S. on 4 October 2023, led to an unusual conspiracy theory involving the MVD and zombies.…”

Section: Introductionmentioning

confidence: 99%

Marburg Virus Outbreak and a New Conspiracy Theory: Findings from a Comprehensive Analysis of Web Behavior

Thakur,

Cui,

Patel

et al. 2023

Preprint

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During virus outbreaks in the recent past web behavior mining, modeling, and analysis have served as means to examine, explore, interpret, assess, and forecast the worldwide perception, readiness, reactions, and response linked to these virus outbreaks. The recent outbreak of the Marburg Virus disease (MVD), the high fatality rate of MVD, and the conspiracy theory linking the FEMA alert signal in the United States on October 4, 2023, with MVD and a zombie outbreak, resulted in a diverse range of reactions in the general public which has transpired in a surge in web behavior in this context. This resulted in “Marburg Virus” featuring in the list of the top trending topics on Twitter on October 3, 2023, and “Emergency Alert System” and “Zombie” featuring in the list of top trending topics on Twitter on October 4, 2023. No prior work in this field has mined and analyzed the emerging trends in web behavior in this context. The work presented in this paper aims to address this research gap and makes multiple scientific contributions to this field. First, it presents the results of performing time series forecasting of the search interests related to MVD emerging from 216 different regions on a global scale using ARIMA, LSTM, and Autocorrelation. The results of this analysis present the optimal model for forecasting web behavior related to MVD in each of these regions. Second, the correlation between search interests related to MVD and search interests related to zombies (in the context of this conspiracy theory) was investigated. The findings show that there were several regions where there was a statistically significant correlation between MVD-related searches and zombie-related searches (in the context of this conspiracy theory) on Google on October 4, 2023. Finally, the correlation between zombie-related searches (in the context of this conspiracy theory) in the United States and other regions was investigated. This analysis helped to identify those regions where this correlation was statistically significant.

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Section: Introductionmentioning

confidence: 99%

Marburg Virus Outbreak and a New Conspiracy Theory: Findings from a Comprehensive Analysis of Web Behavior

Thakur,

Cui,

Patel

et al. 2023

Preprint

View full text Add to dashboard Cite

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Semi-Supervised Learning Classifier for Misinformation Related to Earthquakes Prediction on Social Media

Elroy,

Yosipof

2023

Lecture Notes in Computer Science

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Earthquake conspiracy discussion on Twitter

Erokhin,

Komendantova

2024

Humanit Soc Sci Commun

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Natural disasters like earthquakes, and global crises like pandemics have historically captured the public’s imagination and prompted people to seek explanations. However, in times of limited information, these explanations can take the form of conspiracy theories, particularly regarding the origins or causes of such events. With the advent of social media conspiracy theories can spread quickly and easily, leaving little room for critical thinking. The focus of this study is the analysis of the so-called High-Frequency Active Auroral Research Program (HAARP) conspiracy, which explains earthquakes through the employment of secret weather control weapons. This study aims to answer the research question of how the discourse on the HAARP conspiracy theory changes over time, and what are the potential catalysts for heightened attention to this conspiracy theory. This study uses the Twitter API to collect tweet frequencies about this conspiracy from January 2022 through March 2023. The empirical data include over one million tweets on HAARP. The sentiment analysis of the HAARP conspiracy theory is applied to the tweets before, during, and after the 6th of February 2023 earthquake in Syria and Turkey. In addition, this study investigates possible triggers of the development of the HAARP tweet frequency. This study finds that the frequency of HAARP discussion increases following a high-impact earthquake. There is also a positive correlation between average tweet sentiment and the number of tweets, which could indicate that the discussion of HAARP reinforces people’s beliefs. This study makes a significant contribution to the field of social psychology and communication by providing insights into the dynamics of belief reinforcement within online communities amidst heightened attention to conspiracy theories triggered by significant events. This knowledge has broader implications for understanding the impact of social media on public perception during crises.

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Mining the Discussion of Monkeypox Misinformation on Twitter Using RoBERTa

Cited by 5 publications

References 18 publications

Marburg Virus Outbreak and a New Conspiracy Theory: Findings from a Comprehensive Analysis of Web Behavior

Marburg Virus Outbreak and a New Conspiracy Theory: Findings from a Comprehensive Analysis of Web Behavior

Semi-Supervised Learning Classifier for Misinformation Related to Earthquakes Prediction on Social Media

Earthquake conspiracy discussion on Twitter

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