COVID-19 rumours in historical context
Lead Research Organisation:
University of London
Department Name: Inst of Historical Research
Abstract
The COVID-19 outbreak has been accompanied by a pandemic of rumour and disinformation in the UK. Rumours about the origins of the virus, shortages, fake cures and government conspiracies are being spread by well-meaning people who want to make sense of the outbreak, as well as by criminals and hostile foreign governments. These rumours have the potential to cost lives, not least by undermining public confidence in any forthcoming vaccine. Despite the apparent novelty of 'fake news' and its circulation online, there is little that is new about these rumours, all of which have historical precedents. Yet policy-makers know little about how and why similar rumours have spread in the past, how previous governments have responded to them, and how successful these efforts were.
At a point in history where rumours about COVID-19 present an unprecedented health challenge, this project will deploy a novel longitudinal study of relevant historical rumours and government efforts to address them in order to assist policy-makers. It will track rumours circulating in the UK relating to the COVID-19 pandemic and any vaccination programme as they develop and compare them to historical precedents. A report, published in collaboration with History & Policy, as well as two closed workshops with policy-makers and scholars drawn from other disciplines, will seek to inform UK government strategies for dealing with mis- and disinformation and influence the tone and content of public information campaigns in order to minimise the harmful impact of 'fake news' and maximise uptake of any future vaccine.
At a point in history where rumours about COVID-19 present an unprecedented health challenge, this project will deploy a novel longitudinal study of relevant historical rumours and government efforts to address them in order to assist policy-makers. It will track rumours circulating in the UK relating to the COVID-19 pandemic and any vaccination programme as they develop and compare them to historical precedents. A report, published in collaboration with History & Policy, as well as two closed workshops with policy-makers and scholars drawn from other disciplines, will seek to inform UK government strategies for dealing with mis- and disinformation and influence the tone and content of public information campaigns in order to minimise the harmful impact of 'fake news' and maximise uptake of any future vaccine.
| Description | The Covid-19 pandemic has been accompanied by a dramatic increase in misinformation, disinformation and conspiracy theories online. This misinformation correlates with vaccine hesitancy and non-compliance with public health measures, as well as a general atmosphere of distrust and disunity, generating the need for legislative action. The strong continuities between the rumours and conspiracies of the current pandemic and their historical counterparts, suggest that they are primarily the consequence of perennial rather than historically contingent features of society. This in turn points to the need for mitigative rather than preventive policy solutions, which include adjustments to the tone and the target of government communications. |
| Exploitation Route | We anticipate that the findings of this work will be used by policy-makers to inform public health communications and to understand approaches to controlling mis-and dis-information. We are making our data set and data dashboard available publicly for use in research (widely defined) and for the general public. |
| Sectors | Digital/Communication/Information Technologies (including Software),Government, Democracy and Justice |
| URL | https://historyandrumour.blogs.sas.ac.uk/ |
| Title | Covid Rumours in Historical Context - dashboard repository |
| Description | The complete corpus consists of three code and data repositories: covid-rumours, covid-rumours-data and covid-rumours-dashboard. In total the corpus contains almost 2 years of tweets harvested daily (576 jsonl.gz files). The total number of tweets in the corpus is 34,590,486, the number of unique users in the corpus is 7,542,484 and the number of unique hashtags in the corpus is 614,464. Anonymised derivative data has been produced and is available directly, including English n-gram word frequencies and colocation datasets in the prototype dashboard. Four Taxonomies of Rumour, produced from historical and data research, are included in collection. This is the dashboard repository - this holds the data visualization tool that was used as a means to investigate the dataset. The dashboard was used for exploring diachronic semantic fields in the data, including scripts, data and steps for recreating the dashboard. |
| Type Of Material | Data analysis technique |
| Year Produced | 2023 |
| Provided To Others? | Yes |
| Impact | Four Taxonomies of Rumour were produced from historical research and data analysis of the corpus, CONSPIRACY, CURES, ORIGINS and VACCINES, and include a set of subcategories and vocabularies. These were used to classify the English tweets for the project's linguistic analyses and used to explore the diachronic topical and categorical semantics within the social media data. A prototype tool to process and explore the linguistic semantic fields within the corpus was developed. The impact of developing/implementing these diachronic linguistic methods and tools allowed the fine-grained conceptual associations used by the online communities to be better observed, contrasted and compared, and subsequently understood in the context of relevant historical precedents. The taxonomies are included as structured YAML files and reusable by others. https://github.com/SAS-DHRH/covid-rumours-data - tweet ID's and anonymous corpus stats data https://github.com/SAS-DHRH/covid-rumours-dashboard - ngrams, word co-locates and dashboard code https://github.com/SAS-DHRH/covid-rumours - documentation, method and main data processing and classifiers code |
| URL | https://github.com/SAS-DHRH/covid-rumours-dashboard |
| Title | Covid Rumours in Historical Context main repository |
| Description | The complete corpus consists of three code and data repositories: covid-rumours, covid-rumours-data and covid-rumours-dashboard. In total the corpus contains almost 2 years of tweets harvested daily (576 jsonl.gz files). The total number of tweets in the corpus is 34,590,486, the number of unique users in the corpus is 7,542,484 and the number of unique hashtags in the corpus is 614,464. Anonymised derivative data has been produced and is available directly, including English n-gram word frequencies and colocation datasets in the prototype dashboard. Four Taxonomies of Rumour, produced from historical and data research, are included in collection. This data repository is the main data repository, which holds the linguistic and computation approach and methods applied to the dataset. |
| Type Of Material | Data analysis technique |
| Year Produced | 2023 |
| Provided To Others? | Yes |
| Impact | Four Taxonomies of Rumour were produced from historical research and data analysis of the corpus, CONSPIRACY, CURES, ORIGINS and VACCINES, and include a set of subcategories and vocabularies. These were used to classify the English tweets for the project's linguistic analyses and used to explore the diachronic topical and categorical semantics within the social media data. A prototype tool to process and explore the linguistic semantic fields within the corpus was developed. The impact of developing/implementing these diachronic linguistic methods and tools allowed the fine-grained conceptual associations used by the online communities to be better observed, contrasted and compared, and subsequently understood in the context of relevant historical precedents. The taxonomies are included as structured YAML files and reusable by others. https://github.com/SAS-DHRH/covid-rumours-data - tweet ID's and anonymous corpus stats data https://github.com/SAS-DHRH/covid-rumours-dashboard - ngrams, word co-locates and dashboard code https://github.com/SAS-DHRH/covid-rumours - documentation, method and main data processing and classifiers code |
| URL | https://github.com/SAS-DHRH/covid-rumours |
| Title | Covid Rumours in Historical Context tweet corpus |
| Description | The complete corpus consists of three code and data repositories: covid-rumours, covid-rumours-data and covid-rumours-dashboard. In total the corpus contains almost 2 years of tweets harvested daily (576 jsonl.gz files). The total number of tweets in the corpus is 34,590,486, the number of unique users in the corpus is 7,542,484 and the number of unique hashtags in the corpus is 614,464. Anonymised derivative data has been produced and is available directly, including English n-gram word frequencies and colocation datasets in the prototype dashboard. Four Taxonomies of Rumour, produced from historical and data research, are included in collection. |
| Type Of Material | Database/Collection of data |
| Year Produced | 2022 |
| Provided To Others? | Yes |
| Impact | Four Taxonomies of Rumour were produced from historical research and data analysis of the corpus, CONSPIRACY, CURES, ORIGINS and VACCINES, and include a set of subcategories and vocabularies. These were used to classify the English tweets for the project's linguistic analyses and used to explore the diachronic topical and categorical semantics within the social media data. A prototype tool to process and explore the linguistic semantic fields within the corpus was developed. The impact of developing/implementing these diachronic linguistic methods and tools allowed the fine-grained conceptual associations used by the online communities to be better observed, contrasted and compared, and subsequently understood in the context of relevant historical precedents. The taxonomies are included as structured YAML files and reusable by others. https://github.com/SAS-DHRH/covid-rumours-data - tweet ID's and anonymous corpus stats data https://github.com/SAS-DHRH/covid-rumours-dashboard - ngrams, word co-locates and dashboard code https://github.com/SAS-DHRH/covid-rumours - documentation, method and main data processing and classifiers code |
| URL | https://github.com/SAS-DHRH/covid-rumours-data |
| Description | History & Policy Unit |
| Organisation | History and Policy |
| Country | United Kingdom |
| Sector | Charity/Non Profit |
| PI Contribution | Worked together on public event. Worked collaboratively on the final report, published on the History& Policy website |
| Collaborator Contribution | Worked together on public event. Worked collaboratively on the final report, published on the History& Policy website |
| Impact | Policy paper Public event |
| Start Year | 2021 |
| Description | Disinformation and COVID-19 in Historical Context public event |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Public/other audiences |
| Results and Impact | The Covid-19 pandemic has been accompanied by the circulation of a significant volume of mis-and dis-information globally. Rumours and conspiracy theories about the virus itself and the vaccination campaign that followed spread widely, particularly online. This panel explored the trends in disinformation relating to the pandemic and asks how much is new, how concerned should we be about levels of disinformation, and whether historical research might suggest solutions. It brought together policy makers and researchers from different disciplinary backgrounds. It also connected two AHRC-funded projects Panel: Alex Aiken (Executive Director for Government Communication, Cabinet Office) Jo Fox (Principal Investigator, AHRC COVID-19 rumours in historical context project, Dean of the School of Advanced Study, London) Peter Knight (Principal Investigator, AHRC Infodemic: Combatting COVID-19 Conspiracy Theories project, Professor of American Studies, Manchester) Ed Pertwee (Media monitoring and analysis for the Vaccine Confidence Project, London School of Hygiene & Tropical Medicine) The aim was to bring the findings from research projects (together with a policy perspective) into the public domain, to allow the public to ask questions and debate the issues, and to cement connections between the policy profession and the academics on the panel. |
| Year(s) Of Engagement Activity | 2022 |
| URL | https://www.history.ac.uk/events/disinformation-and-covid-19-historical-context |