scholarly journals Infodemiology: Computational Methodologies for quantifying and visualizing key characteristics of the COVID-19 infodemic

2021 ◽  
Author(s):  
Dominic Ligot ◽  
Frances Claire Tayco ◽  
Mark Toledo ◽  
Carlos Nazareno ◽  
Denise Brennan-Rieder
Keyword(s):  
Social Media ◽  
Topic Modeling ◽  
Time Varying ◽  
Specific Topic ◽  
False Information ◽  
Conspiracy Theories ◽  
Heat Maps ◽  
Key Characteristics ◽  
Latent Topics ◽  
Taking Action

Objectives. Infodemics of false information on social media is a growing societal problem, aggravated by the occurrence of the COVID-19 pandemic. The development of infodemics has characteristic resemblances to epidemics of infectious diseases. This paper presents several methodologies which aim to measure the extent and development of infodemics through the lens of epidemiology.Methods. Time varying R was used as a measure for the infectiousness of the infodemic, topic modeling was used to create topic clouds and topic similarity heat maps, while network analysis was used to create directed and undirected graphs to identify super-spreader and multiple carrier communities on social media.Results. Forty-two (42) latent topics were discovered. Reproductive trends for a specific topic were observed to have significantly higher peaks (Rt 4-5) than general misinformation (Rt 1-3). From a sample of social media misinformation posts, a total of 385 groups and 804 connections were found within the network, with the largest group having 1,643 shares and 1,063,579 interactions over a 12 month period.Conclusions. These approaches enable the measurement of the infectiousness of an infodemic, comparative analysis of infodemic topics, and identification of likely super-spreaders and multiple carriers on social media. The results of these analyses can form the basis for taking action to stem an ongoing spread of misinformation on social media and mitigate against future infodemics. The methods are not confined to health misinformation and may be applied to other infodemics, such as conspiracy theories, political disinformation, and climate change denial.

scholarly journals False news around COVID-19 circulated less on Sina Weibo than on Twitter. How to overcome false information?

2020 ◽  
Author(s):  
Cristina Pulido Rodríguez ◽  
Beatriz Villarejo Carballido ◽  
Gisela Redondo-Sama ◽  
Mengna Guo ◽  
Mimar Ramis ◽  
...  
Keyword(s):  
Social Media ◽  
Evidence Based ◽  
World Economic Forum ◽  
Fake News ◽  
Best Interest ◽  
False Information ◽  
Conspiracy Theories ◽  
Sina Weibo ◽  
World Economic ◽  
False News

Since the Coronavirus health emergency was declared, many are the fake news that have circulated around this topic, including rumours, conspiracy theories and myths. According to the World Economic Forum, fake news is one of the threats in today's societies, since this type of information circulates fast and is often inaccurate and misleading. Moreover, fake-news are far more shared than evidence-based news among social media users and thus, this can potentially lead to decisions that do not consider the individual’s best interest. Drawing from this evidence, the present study aims at comparing the type of Tweets and Sina Weibo posts regarding COVID-19 that contain either false or scientific veracious information. To that end 1923 messages from each social media were retrieved, classified and compared. Results show that there is more false news published and shared on Twitter than in Sina Weibo, at the same time science-based evidence is more shared on Twitter than in Weibo but less than false news. This stresses the need to find effective practices to limit the circulation of false information.

scholarly journals STRATEGI PENGAWASAN TERHADAP UJARAN KEBENCIAN DI MEDIA SOSIAL PADA PEMILU

2020 ◽  
Vol 1 (2) ◽  
pp. 99-116
Author(s):  
Dewi Anggraeni ◽  
Adrinoviarini Adrinoviarini
Keyword(s):  
Social Media ◽  
Hate Speech ◽  
Group Discussion ◽  
The Political ◽  
False Information ◽  
Effective Strategies ◽  
Fertile Ground ◽  
Data Collection Technique ◽  
Gubernatorial Election ◽  
Taking Action

The political year is a fertile vehicle for disseminating news of hate speech, forms of intolerance, and false information (hoaxes) decorating the Indonesian social media universe. Election campaigns provide fertile ground for hate speech and incitement, especially on social media. This research aims to analyze and identify the prevalence of hate speech in the DKI Jakarta gubernatorial election by evaluating the regulations regarding hate speech on social media according to stakeholders and appropriate and effective strategies in preventing and taking action against hate speech violations in the Pilkada/Election. This type of research is descriptive qualitative, which portrays the phenomenon of the DKI Jakarta governor election in 2017, The data collection technique used was a focus group discussion by inviting several sources. The results of this study reveal that; Hate speech in 2017 on social media, especially Facebook, has increased in the momentum of the Pilkada. The ITE Law and SE / 06 / X / 2015 have been implemented by various stakeholders as an effort to prevent and prosecute hate speech offenders, although this has not been maximized due to the weak media literacy of Indonesian society itself. The case for the 2017 DKI Jakarta election as a prototype for the National Election. Therefore, election organizers need to pay special attention to monitoring social media during the election period.

scholarly journals MISINFORMATION AND DISINFORMATION DURING COVID-19: THE EFFECTS AND THE RELEVANT LAWS IN MALAYSIA

2020 ◽  
Vol 5 (21) ◽  
pp. 202-209
Author(s):  
Hanis Wahed
Keyword(s):  
Social Media ◽  
Social Situation ◽  
Fake News ◽  
False Information ◽  
Legal Research ◽  
Conspiracy Theories ◽  
The Public ◽  
The Social ◽  
The Future ◽  
Use Of Social Media

Misinformation and disinformation are increasing as fast as the spreading of Coronavirus disease 2019 or Covid-19. Both happen as a result of the use of social media and technologies. The act of spreading fake news, rumors, and conspiracy theories or giving false information is considered an offence under the laws of Malaysia. However, the number of cases that relate to this offence has been increasing especially during the current pandemic. Thus, this article discusses the effects of the offence and the efforts taken in preventing it from happening. The focus is on the laws that are applicable in the situation. The methodology used is socio-legal research that involves analysing the laws that are applicable in the social situation. The article suggests that further research should be carried out on the applicable laws and amendments should be made to the relevant laws in order to combat the commission of the offence in the future. It is hoped that the suggestion will assist the authority to add more measures in combatting the pandemic and for the public to be more cautious of committing misinformation and disinformation.

scholarly journals Medical documents classification using topic modeling

2020 ◽  
Vol 17 (3) ◽  
pp. 1524
Author(s):  
Maryam Nuser ◽  
Enas Al-Horani
Keyword(s):  
Blood Pressure ◽  
Classification Accuracy ◽  
Topic Modeling ◽  
Heart Diseases ◽  
Modeling Technique ◽  
Specific Topic ◽  
Text Documents ◽  
Medical Documents ◽  
Latent Topics

The number of digital medical documents is increasing continuously; several medical websites share a lot of unclassified articles. These articles have very long texts that should be read to determine the topic of each document. The classification of these documents is important so researchers can use these documents easily and the effort and time in reading and searching for a specific topic will be reduced. Therefore, an automatic way to extract latent topics from these text documents is needed. Topic modeling is one of the techniques used to deal with this problem. In this paper, a medical collection of documents is used; this collection contains documents from three types of widespread diseases (Heart Diseases, Blood Pressure and Cholesterol). LDA topic modeling technique is applied to classify these documents into the previous mentioned topics. An evaluation of the algorithm’s results is done and the LDA shows a good level of classification accuracy.

scholarly journals Characterizing the COVID-19 Infodemic on Chinese Social Media: Exploratory Study

10.2196/26090 ◽  
2021 ◽  
Vol 7 (2) ◽  
pp. e26090
Author(s):  
Shuai Zhang ◽  
Wenjing Pian ◽  
Feicheng Ma ◽  
Zhenni Ni ◽  
Yunmei Liu
Keyword(s):  
Social Media ◽  
Topic Modeling ◽  
Conspiracy Theories ◽  
Daily Number ◽  
Video Sharing ◽  
Government Response ◽  
Governance Systems ◽  
Social Media Platforms ◽  
News Sharing ◽  
Chinese Social Media

Background The COVID-19 infodemic has been disseminating rapidly on social media and posing a significant threat to people’s health and governance systems. Objective This study aimed to investigate and analyze posts related to COVID-19 misinformation on major Chinese social media platforms in order to characterize the COVID-19 infodemic. Methods We collected posts related to COVID-19 misinformation published on major Chinese social media platforms from January 20 to May 28, 2020, by using PythonToolkit. We used content analysis to identify the quantity and source of prevalent posts and topic modeling to cluster themes related to the COVID-19 infodemic. Furthermore, we explored the quantity, sources, and theme characteristics of the COVID-19 infodemic over time. Results The daily number of social media posts related to the COVID-19 infodemic was positively correlated with the daily number of newly confirmed (r=0.672, P<.01) and newly suspected (r=0.497, P<.01) COVID-19 cases. The COVID-19 infodemic showed a characteristic of gradual progress, which can be divided into 5 stages: incubation, outbreak, stalemate, control, and recovery. The sources of the COVID-19 infodemic can be divided into 5 types: chat platforms (1100/2745, 40.07%), video-sharing platforms (642/2745, 23.39%), news-sharing platforms (607/2745, 22.11%), health care platforms (239/2745, 8.71%), and Q&A platforms (157/2745, 5.72%), which slightly differed at each stage. The themes related to the COVID-19 infodemic were clustered into 8 categories: “conspiracy theories” (648/2745, 23.61%), “government response” (544/2745, 19.82%), “prevention action” (411/2745, 14.97%), “new cases” (365/2745, 13.30%), “transmission routes” (244/2745, 8.89%), “origin and nomenclature” (228/2745, 8.30%), “vaccines and medicines” (154/2745, 5.61%), and “symptoms and detection” (151/2745, 5.50%), which were prominently diverse at different stages. Additionally, the COVID-19 infodemic showed the characteristic of repeated fluctuations. Conclusions Our study found that the COVID-19 infodemic on Chinese social media was characterized by gradual progress, videoization, and repeated fluctuations. Furthermore, our findings suggest that the COVID-19 infodemic is paralleled to the propagation of the COVID-19 epidemic. We have tracked the COVID-19 infodemic across Chinese social media, providing critical new insights into the characteristics of the infodemic and pointing out opportunities for preventing and controlling the COVID-19 infodemic.

scholarly journals Exploring halal tourism tweets on social media

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Ali Feizollah ◽  
Mohamed M. Mostafa ◽  
Ainin Sulaiman ◽  
Zalina Zakaria ◽  
Ahmad Firdaus
Keyword(s):  
Social Media ◽  
Network Analysis ◽  
Topic Modeling ◽  
Semantic Network ◽  
Word List ◽  
Global Market ◽  
Semantic Network Analysis ◽  
Tourist Destinations ◽  
Muslim Countries ◽  
Emotion Lexicon

AbstractThis study explores tweets from Oct 2008 to Oct 2018 related to halal tourism. The tweets were extracted from twitter and underwent various cleaning processes. A total of 33,880 tweets were used for analysis. Analysis intended to (1) identify the topics users tweet about regarding halal tourism, and (2) analyze the emotion-based sentiment of the tweets. To identify and analyze the topics, the study used a word list, concordance graphs, semantic network analysis, and topic-modeling approaches. The NRC emotion lexicon was used to examine the sentiment of the tweets. The analysis illustrated that the word “halal” occurred in the highest number of tweets and was primarily associated with the words “food” and “hotel”. It was also observed that non-Muslim countries such as Japan and Thailand appear to be popular as halal tourist destinations. Sentiment analysis found that there were more positive than negative sentiments among the tweets. The findings have shown that halal tourism is a global market and not only restricted to Muslim countries. Thus, industry players should take the opportunity to use social media to their advantage to promote their halal tourism packages as it is an effective method of communication in this decade.

scholarly journals The COVID‐19 pandemic and the search for structure: Social media and conspiracy theories

2021 ◽  
Author(s):  
Benjamin J. Dow ◽  
Amber L. Johnson ◽  
Cynthia S. Wang ◽  
Jennifer Whitson ◽  
Tanya Menon
Keyword(s):  
Social Media ◽  
Conspiracy Theories

scholarly journals COVID-19 conspiracy theories

2021 ◽  
Vol 24 (2) ◽  
pp. 270-275 ◽  
Author(s):  
Karen M. Douglas
Keyword(s):  
Social Media ◽  
Public Opinion ◽  
Intergroup Relations ◽  
Group Processes ◽  
Negative Consequences ◽  
Conspiracy Theories ◽  
Open Questions ◽  
Potential Impact

Conspiracy theories started to appear on social media immediately after the first news about COVID-19. Is the virus a hoax? Is it a bioweapon designed in a Chinese laboratory? These conspiracy theories typically have an intergroup flavour, blaming one group for having some involvement in either manufacturing the virus or controlling public opinion about it. In this article, I will discuss why people are attracted to conspiracy theories in general, and why conspiracy theories seem to have flourished during the pandemic. I will discuss what the consequences of these conspiracy theories are for individuals, groups, and societies. I will then discuss some potential strategies for addressing the negative consequences of conspiracy theories. Finally, I will consider some open questions for research regarding COVID-19 conspiracy theories, in particular focusing on the potential impact of these conspiracy theories for group processes and intergroup relations.

scholarly journals Faster than warp speed: early attention to COVD-19 by anti-vaccine groups on Facebook

2021 ◽  
Author(s):  
Seth C Kalichman ◽  
Lisa A Eaton ◽  
Valerie A Earnshaw ◽  
Natalie Brousseau
Keyword(s):  
Social Media ◽  
Vaccine Development ◽  
Rapid Development ◽  
Development Program ◽  
Vaccine Safety ◽  
Vaccine Hesitancy ◽  
Conspiracy Theories ◽  
The Us ◽  
Us Government ◽  
Vaccine Information

Abstract Background The unprecedented rapid development of COVID-19 vaccines has faced SARS-CoV- (COVID-19) vaccine hesitancy, which is partially fueled by the misinformation and conspiracy theories propagated by anti-vaccine groups on social media. Research is needed to better understand the early COVID-19 anti-vaccine activities on social media. Methods This study chronicles the social media posts concerning COVID-19 and COVID-19 vaccines by leading anti-vaccine groups (Dr Tenpenny on Vaccines, the National Vaccine Information Center [NVIC] the Vaccination Information Network [VINE]) and Vaccine Machine in the early months of the COVID-19 pandemic (February–May 2020). Results Analysis of 2060 Facebook posts showed that anti-vaccine groups were discussing COVID-19 in the first week of February 2020 and were specifically discussing COVID-19 vaccines by mid-February 2020. COVID-19 posts by NVIC were more widely disseminated and showed greater influence than non-COVID-19 posts. Early COVID-19 posts concerned mistrust of vaccine safety and conspiracy theories. Conclusion Major anti-vaccine groups were sowing seeds of doubt on Facebook weeks before the US government launched its vaccine development program ‘Operation Warp Speed’. Early anti-vaccine misinformation campaigns outpaced public health messaging and hampered the rollout of COVID-19 vaccines.

Sign in / Sign up

Export Citation Format

Share Document