During a 2024 survey among marketers worldwide, approximately 83 percent selected increased exposure as a benefit of social media marketing. Increased traffic followed, mentioned by 73 percent of the respondents, while 65 percent cited generated leads.

              The multibillion-dollar social media ad industry

              Between 2019 – the last year before the pandemic – and 2024, global social media advertising spending skyrocketed by 140 percent, surpassing an estimated 230 billion U.S. dollars in the latter year. That figure was forecast to increase by nearly 50 percent by the end of the decade, exceeding 345 billion dollars in 2029. As of 2024, the social media networks with the most monthly active users were Facebook, with over three billion, and YouTube, with more than 2.5 billion.

              Pros and cons of GenAI for social media marketing

              According to another 2024 survey, generative artificial intelligence's (GenAI) leading benefits for social media marketing according to professionals worldwide included increased efficiency and easier idea generation. The third place was a tie between increased content production and enhanced creativity. All those advantages were cited by between 33 and 38 percent of the interviewees. As for GenAI's top challenges for global social media marketing,
              maintaining authenticity and the value of human creativity ranked first, mentioned by 43 and 40 percent of the respondents, respectively. Another 35 percent deemed ensuring the content resonates as an obstacle.

According to a study conducted in March 2020, ** percent of adults worldwide aged between 18 and 35 years old were getting most of their information about the coronavirus pandemic via social media, compared to ** percent of those aged 55 or above. Major news organizations were overall a more popular source of information about COVID-19, but younger consumers were more evenly split in terms of which platforms they were using the most to keep themselves updated about the virus, whereas older adults were far more likely to turn to major news outlets.

Methods of communications and the nature of messaging are critically important in influencing public behavior. The COVID-19 pandemic has resulted in major disruptions to all aspects of life globally and has triggered multiple approaches of health messaging to the general public to communicate COVID-19 preventative measures. This study aimed to identify: (1) differences between age groups in the main avenues used by people to obtain COVID-19 related information; and (2) whether age and information sources were associated with correct interpretation of government messaging relating to how people understand or interpret the terms “self-isolation” and “social distancing.” An online survey was conducted in 2020. Participants were aged over 18 years and grouped into age group decades. Differences in sources of COVID-19 information were compared visually between age groups. Logistic regression was used to determine whether age and each of the various methods of communication of COVID-19 information were independently associated with correct response to the self-isolation, or the social distancing statements. There were 3,300 survey respondents 85% female; age sub-groups: 18–29 (7.4%); 30–39 (10.6%); 40–49 (17.6%); 50–59 (22.9%); 60–69 (25.9%); 70–79 (13.9%); and 80+ (1.7%). People accessed public health messaging information from a wide variety of sources that changed as they aged (e.g., older people were more likely to be exposed to COVID-19 information via television news programs and less likely via social media platforms). Age was frequently associated with whether the message key terms were interpreted correctly or incorrectly, but in some cases, it promoted more correct responses whereas in others, fewer correct responses. There was no difference between being exposed to COVID-19 information via mainstream media, compared with social media, or compared with Government sources of information, in terms of whether COVID-19 messages were interpreted correctly. In order to improve future public health messaging, there is a need for multiple avenues of communication to meet the needs and preferences across and within age groups. Further investigation is warranted into the clarity of the content and method of delivery of public health messages, to ensure optimal understanding of public health messages by vulnerable populations and across the community.

During the COVID-19 pandemic, people have become increasingly fearful of the disease as death tolls rise, while governments attempt to combat it by installing restrictive measures. News media play a vital role as they are the main sources from which people gather information regarding the disease and the public health measures. The present longitudinal data reflect a bird’s eye view of people’s fears towards getting ill, their news media consumption, their attitudes regarding the (Belgian) government’s handling of the COVID-19 crisis, informal care burden, and changes in physical activities. Data were collected at five key moments in the pandemic among adults in Flanders, Belgium: in the middle of March 2020 (W1; when the first restrictive measures went into effect; N = 1,000), early April 2020 (W2; as hospital admissions and death toll peaked; N = 870), at the end of May and beginning of June 2020 (W3; as several measures were lifted or relaxed; N = 768), in late August 2020 (W4; as infection rates increased again; N = 505), and in the middle of March 2021, exactly one year after the first data collection (W5; N = 408). In W4 and W5, new respondents were added to the longitudinal sample to strengthen cross-sectional analyses. These data may be of interest to researchers who wish to explore dynamics of fear and attitudes towards public health measures during this particularly challenging time.

Social media is one of the go-to news sources in the United States – over one third of U.S. adults responding to a 2022 survey got their news from social media platforms every day, and a further 22 percent did so a few times or at least once per week. After the surge in social media news consumption in 2020 at the height of the COVID-19 pandemic, daily engagement fell in 2021, but the increase the following year suggests that daily news access on social networks could continue to grow in years to come.

The most popular social sites for news

An annual report surveying U.S. adults from 2019 to 2022 revealed that Facebook was the most popular social network used for news, followed by YouTube. Important to note here though is that TikTok was not included in the survey question for those years, a platform increasingly popular with younger generations. Whilst the share of adults regularly using TikTok for news aged 50 years or above was just five percent, among those aged between 18 and 29 years the figure was over five times higher.

Meanwhile, Twitter is journalists’ preferred social media site, with the share who use Twitter for their job at almost 70 percent. Since Elon Musk’s takeover of Twitter however, some journalists raised concerns about the future of free speech on the platform.

Gen Z and social media news consumption

A 2022 survey found that half of all Gen Z respondents used social media for news every day. Gen Z is driving growth in social media news usage, a trend which will continue if the younger consumers belonging to this generation increase their engagement with news as they age.

This dataset presents a large-scale collection of millions of Twitter posts related to the coronavirus pandemic in Spanish language. The collection was built by monitoring public posts written in Spanish containing a diverse set of hashtags related to the COVID-19, as well as tweets shared by the official Argentinian government offices, such as ministries and secretaries at different levels. Data was collected between March and June 2020 using the Twitter API, and will be periodically updated.

In addition to tweets IDs, the dataset includes information about mentions, retweets, media, URLs, hashtags, replies, users and content-based user relations, allowing the observation of the dynamics of the shared information. Data is presented in different tables that can be analysed separately or combined.

The dataset aims at serving as source for studying several coronavirus effects in people through social media, including the impact of public policies, the perception of risk and related disease consequences, the adoption of guidelines, the emergence, dynamics and propagation of disinformation and rumours, the formation of communities and other social phenomena, the evolution of health related indicators (such as fear, stress, sleep disorders, or children behaviour changes), among other possibilities. In this sense, the dataset can be useful for multi-disciplinary researchers related to the different fields of data science, social network analysis, social computing, medical informatics, social sciences, among others.

Access to accurate information during a crisis is essential. However, while the amount of information circulating during the COVID-19 pandemic has increased exponentially, finding trustworthy resources has been difficult for many, including those affected by international travel restrictions. In this study, we examined the information-seeking behaviors of individuals seeking to travel internationally during the COVID-19 pandemic. We also explored perceptions regarding the value of resources in supporting understanding of COVID-19 travel restriction-related information. Two online cross-sectional surveys targeting four groups were conducted. The groups targeted were: (1) citizens and permanent residents stranded abroad; (2) individuals separated from their partners; (3) individuals separated from immediate families; and (4) temporary visa holders unable to migrate or cross international borders. In total, we analyzed 2,417 completed responses, and a further 296 responses where at least 75% of questions were completed. Findings suggest that social media groups (78.4%, 1,924/2,453), specifically Facebook (86.6%, 2,115/2,422) were the most useful or most used information resource for these groups. Some significant information seeking behavior differences across age and gender were also found. Our study highlights the diversity in information needs of people impacted by COVID-19 travel restrictions and the range of preferred channels through which information is sought. Further, it highlights which challenges hold legitimacy in their target audiences' eyes and which do not. Policymakers may use these results to help formulate more nuanced, consumer-tailored—and hence likely more acceptable, trusted, and impactful—communication strategies as part of future public health emergencies.

Context

COVID-19 is an infectious disease caused by a newly discovered strain of coronavirus, a type of virus known to cause respiratory infections in humans. This new strain was unknown before December 2019, when an outbreak of pneumonia of unidentified cause emerged in Wuhan, China.

Ever since the Covid-19 pandemic there has been quite a buzz in social media platforms and news sites regarding the need for COVID-19 Vaccine. As the number of people getting affected by Covid-19 has been increasing drastically. This data set brings you the twitter tweets made with the hashtag #CovidVaccine

Content

The tweets have #CovidVaccine hashtag. The collection started on 1/8/2020, and will be updated on a daily basis.

Information regarding the data

The data totally consists of 1 lakh+ records with 13 columns. The description of the features is given below | No |Columns | Descriptions | | -- | -- | -- | | 1 | user_name | The name of the user, as they’ve defined it. | | 2 | user_location | The user-defined location for this account’s profile. | | 3 | user_description | The user-defined UTF-8 string describing their account. | | 4 | user_created | Time and date, when the account was created. | | 5 | user_followers | The number of followers a account currently has. | | 6 | user_friends | The number of friends a account currently has. | | 7 | user_favourites | The number of favorites a account currently has | | 8 | user_verified | When true, indicates that the user has a verified account | | 9 | date | UTC time and date when the Tweet was created | | 10 | text | The actual UTF-8 text of the Tweet | | 11 | hashtags | All the other hashtags posted in the tweet along with #CovidVaccine | | 12 | source | Utility used to post the Tweet, Tweets from the Twitter website have a source value - web | | 13 | is_retweet | Indicates whether this Tweet has been Retweeted by the authenticating user. |

Inspiration

You can use this data to dive into the subjects that use this hashtag, look to the geographical distribution, evaluate sentiments, looks to trends.

The peer-reviewed publication for this dataset has been presented in the 2022 Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), and can be accessed here: https://arxiv.org/abs/2205.02596. Please cite this when using the dataset.

This dataset contains a heterogeneous set of True and False COVID claims and online sources of information for each claim.

The claims have been obtained from online fact-checking sources, existing datasets and research challenges. It combines different data sources with different foci, thus enabling a comprehensive approach that combines different media (Twitter, Facebook, general websites, academia), information domains (health, scholar, media), information types (news, claims) and applications (information retrieval, veracity evaluation).

The processing of the claims included an extensive de-duplication process eliminating repeated or very similar claims. The dataset is presented in a LARGE and a SMALL version, accounting for different degrees of similarity between the remaining claims (excluding respectively claims with a 90% and 99% probability of being similar, as obtained through the MonoT5 model). The similarity of claims was analysed using BM25 (Robertson et al., 1995; Crestani et al., 1998; Robertson and Zaragoza, 2009) with MonoT5 re-ranking (Nogueira et al., 2020), and BERTScore (Zhang et al., 2019).

The processing of the content also involved removing claims making only a direct reference to existing content in other media (audio, video, photos); automatically obtained content not representing claims; and entries with claims or fact-checking sources in languages other than English.

The claims were analysed to identify types of claims that may be of particular interest, either for inclusion or exclusion depending on the type of analysis. The following types were identified: (1) Multimodal; (2) Social media references; (3) Claims including questions; (4) Claims including numerical content; (5) Named entities, including: PERSON − People, including fictional; ORGANIZATION − Companies, agencies, institutions, etc.; GPE − Countries, cities, states; FACILITY − Buildings, highways, etc. These entities have been detected using a RoBERTa base English model (Liu et al., 2019) trained on the OntoNotes Release 5.0 dataset (Weischedel et al., 2013) using Spacy.

The original labels for the claims have been reviewed and homogenised from the different criteria used by each original fact-checker into the final True and False labels.

The data sources used are:

• The CoronaVirusFacts/DatosCoronaVirus Alliance Database. https://www.poynter.org/ifcn-covid-19-misinformation/

• CoAID dataset (Cui and Lee, 2020) https://github.com/cuilimeng/CoAID

• MM-COVID (Li et al., 2020) https://github.com/bigheiniu/MM-COVID

• CovidLies (Hossain et al., 2020) https://github.com/ucinlp/covid19-data

• TREC Health Misinformation track https://trec-health-misinfo.github.io/

• TREC COVID challenge (Voorhees et al., 2021; Roberts et al., 2020) https://ir.nist.gov/covidSubmit/data.html

The LARGE dataset contains 5,143 claims (1,810 False and 3,333 True), and the SMALL version 1,709 claims (477 False and 1,232 True).

The entries in the dataset contain the following information:

• Claim. Text of the claim.

• Claim label. The labels are: False, and True.

• Claim source. The sources include mostly fact-checking websites, health information websites, health clinics, public institutions sites, and peer-reviewed scientific journals.

• Original information source. Information about which general information source was used to obtain the claim.

• Claim type. The different types, previously explained, are: Multimodal, Social Media, Questions, Numerical, and Named Entities.

Funding. This work was supported by the UK Engineering and Physical Sciences Research Council (grant no. EP/V048597/1, EP/T017112/1). ML and YH are supported by Turing AI Fellowships funded by the UK Research and Innovation (grant no. EP/V030302/1, EP/V020579/1).

References

• Arana-Catania M., Kochkina E., Zubiaga A., Liakata M., Procter R., He Y.. Natural Language Inference with Self-Attention for Veracity Assessment of Pandemic Claims. NAACL 2022 https://arxiv.org/abs/2205.02596

• Stephen E Robertson, Steve Walker, Susan Jones, Micheline M Hancock-Beaulieu, Mike Gatford, et al. 1995. Okapi at trec-3. Nist Special Publication Sp,109:109.

• Fabio Crestani, Mounia Lalmas, Cornelis J Van Rijsbergen, and Iain Campbell. 1998. “is this document relevant?. . . probably” a survey of probabilistic models in information retrieval. ACM Computing Surveys (CSUR), 30(4):528–552.

• Stephen Robertson and Hugo Zaragoza. 2009. The probabilistic relevance framework: BM25 and beyond. Now Publishers Inc.

• Rodrigo Nogueira, Zhiying Jiang, Ronak Pradeep, and Jimmy Lin. 2020. Document ranking with a pre-trained sequence-to-sequence model. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: Findings, pages 708–718.

• Tianyi Zhang, Varsha Kishore, Felix Wu, Kilian Q Weinberger, and Yoav Artzi. 2019. Bertscore: Evaluating text generation with bert. In International Conference on Learning Representations.

• Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov. 2019. Roberta: A robustly optimized bert pretraining approach. arXiv preprint arXiv:1907.11692.

• Ralph Weischedel, Martha Palmer, Mitchell Marcus, Eduard Hovy, Sameer Pradhan, Lance Ramshaw, Nianwen Xue, Ann Taylor, Jeff Kaufman, Michelle Franchini, et al. 2013. Ontonotes release 5.0 ldc2013t19. Linguistic Data Consortium, Philadelphia, PA, 23.

• Limeng Cui and Dongwon Lee. 2020. Coaid: Covid-19 healthcare misinformation dataset. arXiv preprint arXiv:2006.00885.

• Yichuan Li, Bohan Jiang, Kai Shu, and Huan Liu. 2020. Mm-covid: A multilingual and multimodal data repository for combating covid-19 disinformation.

• Tamanna Hossain, Robert L. Logan IV, Arjuna Ugarte, Yoshitomo Matsubara, Sean Young, and Sameer Singh. 2020. COVIDLies: Detecting COVID-19 misinformation on social media. In Proceedings of the 1st Workshop on NLP for COVID-19 (Part 2) at EMNLP 2020, Online. Association for Computational Linguistics.

• Ellen Voorhees, Tasmeer Alam, Steven Bedrick, Dina Demner-Fushman, William R Hersh, Kyle Lo, Kirk Roberts, Ian Soboroff, and Lucy Lu Wang. 2021. Trec-covid: constructing a pandemic information retrieval test collection. In ACM SIGIR Forum, volume 54, pages 1–12. ACM New York, NY, USA.

Introduction/background: The COVID-19 pandemic continues to have a significant global impact on the health and wellness of the population. Limited published literature exists on the information-seeking behaviour during the pandemic, of young adults, who were at start of the pandemic thought to be less susceptible to COVID-19. This study sought to bridge this gap by administering a survey among postsecondary students in Alberta. The study examined health-related information needs, preferred information sources, and behavioural efforts to prevent COVID-19 and maintain a healthy lifestyle during the pandemic. Methods: A cross-sectional study was conducted in Alberta among postsecondary students in March 2021. Using convenience sampling a link to a pre-validated questionnaire was posted on Alberta based post-secondary institutions online social media platforms (Facebook, LinkedIn). Results and analysis: A total 573 postsecondary students completed the survey. For COVID-19 related information students relied on instant messaging applications such as WhatsApp (52%) and print media (52%). Information on COVID-19 vaccine availability and safety and the changes in by-laws was reported to be vital by 70% of respondents. The preferred COVID-19 information source (60%) was the internet, namely official health websites (e.g., Alberta Health Services). Challenges to accessing COVID-19 information were too many conspiracy theories about COVID-19 (60%) and contradicting information from online sources (53%). Students reported an increase in consumption of fast food (38%); sitting and screen time (82%), time spent in searching for general health-related information (50%); use of natural health products (32%) and a decrease in the time dedicated to physical activities (49%). Over 23.7% of students reported being unsure or would not get the COVID-19 vaccine, while 35% of responded were either unsure or believed vaccines were unsafe. Conclusions and implications for policy, practice or additional research: As post-secondary institutions and public health professionals prepare for in-person classes, after a year of predominantly online learning these results provide baseline information that can be used to plan and communicate appropriate interventions (e.g., targeted vaccination campaigns) and support strategies that mitigate COVID-19 outbreaks and keep students informed and healthy.

The continuity hypothesis of dreams - a widely studied model of dreaming - suggests that the content of dreams is largely continuous with the waking experiences of the dreamer. Given the unprecedented nature of the experiences during the pandemic of COVID-19, we studied the continuity hypothesis in the context of such a pandemic. To that end, we implemented a state-of-the-art deep-learning algorithm that can accurately extract mentions of virtually any medical condition from text and applied it to two sets of data collected during the COVID-19 pandemic: 2,888 dream reports (dreaming life experiences), and 57M tweets mentioning the pandemic (waking life experiences). We found that the health expressions that were shared by both sets were common COVID-19 symptoms (e.g., coronavirus, anxiety, coughing, and stress), suggesting that dreams reflected people's real-world experiences. On the other hand, we found that the health expressions that distinguished the two sets reflected differences in thought processes: health expressions in waking life reflected a linear and logical thought process and, as such, described realistic symptoms or related disorders (e.g., body aches, nasal pain, SARS, H1N1); by contrast, those in dreaming life reflected a thought process likely based on the activation of the visual and emotional areas of the brain and, as such, described either conditions not necessarily associated with the pandemic's virus (e.g., maggots, deformities, snakebites), or conditions of surreal nature (e.g., teeth suddenly falling out, body crumbling into sand). Our results confirm that, in addition to the sources of health data being researched lately (e.g., psychological conditions inferred from social media posts, physiological readings from commercial wearables), dream reports, if interpreted correctly, represent an understudied yet valuable source of people's health experiences in the real world.

To estimate intention to receive newly introduced adult vaccines among community members and healthcare workers (HCWs) in Lusaka, Zambia in the context of previous COVID-19 vaccine uptake and perceived disease threat and, identify trusted sources of vaccine information. We conducted a cross-sectional survey among a random sample of community members and a convenience sample of HCWs from 13 November to 15 December 2023. We evaluated future vaccination intentions by self-reported COVID-19 vaccine uptake, community role, vaccine type (COVID-19 booster, HIV, tuberculosis, malaria, pneumonia, diarrheal disease), and source of information using adjusted, mixed effects Poisson regression and adjusted probability models. We enrolled 395 (79.2 %) community members and 104 (20.8 %) HCWs (N = 499). There was high intention to receive new vaccines among community members (mean score = 83.6 %) andHCWs (mean score = 86.0 %), though intentions varied by vaccine type. Prior COVID-19 vaccine uptake (0, 1, 2+ doses) impacted intentions to receive a novel COVID-19 vaccine among community members (43.3 %,62.8 %, and 79.7 %, respectively) but were not associated with any other vaccine types. Intention to receive a vaccine was strongly associated with perceived disease severity and susceptibility as well as age, sex, education, and household income. Social media as a vaccine information source was associated with lower overall vaccine intention among community members, while health system and community sources were associated with higher overall intention to receive new vaccines. The government was a highly trusted source of vaccine information among all participants. Prior COVID-19 vaccination uptake did not predict future non-COVID-19 vaccine intention in Zambia. Perceived threat and select socio-demographic factors were key predictors, suggesting the need for rapid research to design communication strategies and identify trusted sources per target population.

Methods Study design We conducted a cross-sectional survey in Lusaka, Zambia, recruiting community members from randomly selected households in four urban communities with relatively low COVID-19 vaccine uptake and healthcare workers (HCWs) at ten healthcare facilities chosen for diversity in size and geographic location. All participants were recruited from November to December 2023, long after the major COVID-19 waves in southern Africa, including the 2021 Omicron wave that was first reported in South Africa and Botswana. Participants and recruitment strategy Adults aged 18 years and above who resided in Lusaka Province and could provide consent were eligible to participate in the study. For HCWs, eligibility was restricted to those providing direct clinical services to patients or community-based health services. We purposively selected 10 healthcare facilities to recruit HCWs and four high-density, low-income areas (compounds) with low COVID-19 vaccination rates to recruit community members. This targeted selection aimed to improve the representation of unvaccinated individuals. By focusing on areas with lower uptake, we sought to identify early signals where pre-emptive engagement strategies may be needed and to understand acceptance in settings that might represent more challenging scenarios for vaccine introduction. Healthcare facilities included one University tertiary/specialist care teaching hospital, five first-level hospitals providing non-emergency in- and out-patient care, as well as three Urban Health Centres and one Rural Health Centres offering primary healthcare. Some of these health facilities served as COVID-19 referral treatment centres during the pandemic. We collected data from a convenience sample of HCWs drawn from five (5) distinct departments in 10 public health facilities including Antiretroviral Therapy and Treatment (ART), Mother and Child Health (MCH), TB, Adolescent, and Outpatient (OPD) Departments. Each of the four communities has 10 administrative units (zones), which are divided into 10 neighborhoods of approximately 100 households. Each neighborhood has a Neighborhood Health Committee (NHC) consisting of community members who liaise with the healthcare facility. Per community, we randomly selected one zone and sensitized the participating health facility and 10 NHCs to the study. We employed systematic random sampling to select households from which to draw individuals for data collection. Two study teams, each consisting of a field supervisor and four trained Research Assistants (RAs) accompanied by an NHC member and led by a study coordinator, collected data. Teams enrolled from 10 households per neighborhood and visited two neighborhoods each day. In each neighborhood, the team used the randomizing technique, "spin the bottle", to determine the initial direction and household and then approached every fifth household to the right. At each selected household, the RA and accompanying NHC member introduced the study to all household members, assessed interested household members for eligibility, and enrolled the first eligible member per household.

This is the fourth survey in the Canadian Perspectives Survey Series. It provides information about the source and quality of COVID-19 information that Canadians are accessing. Also covered are the ongoing impacts of COVID-19 on the physical and mental health of individuals, and on their social and employment circumstances.

Social media platforms have become integral tools in the conduct of foreign policy for many nations, including India. This dataset serves as a resource for analyzing ‘Social Media and India’s Foreign Policy: The Case Study of ‘X’ Diplomacy during the Covid-19 Pandemic.’ The data were collected through a web-based questionnaire distributed primarily to people aged 18 – 61 and above in India. A total of 171 valid data were collected from 17 states offering extensive geographic coverage and stored in Mendeley. The 15 contributor states are Goa, Maharashtra, Tamil Nadu, Gujarat, Delhi, Assam, Haryana, Jammu and Kashmir, Karnataka, Kerala, Punjab, Rajasthan, Tripura, Uttar Pradesh and West Bengal. It encompasses diverse question formats, including single-choice, multiple-choice, quizzes, and open-ended. The study underscores the opportunities and challenges of employing 'X' diplomacy in India's foreign policy. Thus, there were two hypotheses. First, India's effective use of 'X' diplomacy positively impacts public perception of India's foreign policy effectiveness. Second, India's adept use of 'X' diplomacy during the COVID-19 pandemic enhances its ability to manage and respond to the crisis effectively. This data shows public perception of the effective use of social media by the Government of India, particularly in the crisis situation. Data also highlight the significant change in India’s narrative through its ‘X’ diplomacy, effectively setting the narratives, public perceptions, and diplomatic strategies. This data can be fully utilized in the study of the significance of social media in India’s foreign policy, the role of social media like ‘X’ in the making of India’s foreign policy, how effective social media like ‘X’ was during the Covid-19 pandemic and how Indian government utilized social media like ‘X’ to delivered messages and to set the narrative in the international politics.

Collected Weibo user statistical information.

The study focuses on the role of journalists, public health officials, government communication officers, and political leaders in health crisis communication during the COVID-19 pandemic.

The qualitative data set consists of qualitative interviews with key individuals involved in health crisis communication during the COVID-19 pandemic in the four countries, conducted between May and October 2022. The interviewees were recruited from four main groups (a) journalists who covered the pandemic, (b) public health officials and other public health professionals who played important roles in communication processes, (c) communication officers in government and other institutions involved in health crisis communication, and (d) political leaders. The number of interviewees ranged from 20 (Brazil) to 14 (US, Poland and Serbia). In general, gaining access to journalists and public health officials was easier than gaining access to government officials and politicians.

All interviews were semi-structured and followed the same basic protocol, which was adapted for different countries and different types of interviewees, reflecting the role played by each of them in the health crisis communication process. Most interviews were conducted remotely, audio-recorded and then transcribed. A small number of interviewees declined to be recorded, and one interviewee responded to questions in writing. All recorded interviews were conducted in local languages, transcribed and translated into English (with the exception of those conducted in Serbian, which remain in original language). During transcription, the interviews were anonymized, and the interviewees were assigned a unique number, preceded by country abbreviation.

All interviews were carried out following the relevant research ethics guidelines and procedures for protection of human subjects at participating universities; interviewees were offered anonymity and gave informed consent. Participants in Serbia, Poland and Brazil provided consent in written form (in accordance with protocols set out by Loughborough University, UK), while in the US, oral consent was recorded (in accordance with the ethics requirements of the University of California San Diego).

The quantitative dataset is based on a cross-sectional survey with nationally representative samples, conducted in the four countries between November and December 2022. The questionnaire was designed to explore the patterns of public attitudes and information-seeking behaviour in relation to the pandemic, with questions about attitudes towards measures, trust in institutions, media use, as well as COVID-related misinformation and conspiracy theories. The data was collected by means of an online survey, carried out in all four countries between November and December 2022 by Lightspeed (Kantar). The survey included a total of 5,000 respondents (in Brazil, N= 1,500; in Poland, N= 1,000; in Serbia, N= 1,000; in the United States, N= 1,500), stratified by quotas according to sex, age, geographic regions, and income. Weights were not used as the data had a strong match with the census profiles.

Media serve as important sources of information about health, and their role increases during public health crises. The way media select and present information during a crisis can have a significant impact on public attitudes and behaviour; it can encourage social cohesion and compliance with public health measures, or alternatively saw division and distrust. The presence of populist leaders obstructs the capacity of media organisations to engage in effective health crisis communication. It fosters anti-elite sentiments, contributes to divisive media coverage, and thereby encourages polarized attitudes and distrust among citizens, making them more vulnerable to misinformation spreading through socio-digital networks. Given the growing appeal of populism globally, activities aimed at making our societies more resilient in the face of future pandemics need a better understanding of how populism affects health crisis communication. This project developed the first comprehensive, comparative study of health crisis communication in the context of populist politics, focusing on four countries that were led by populist leaders during the pandemic: Brazil, Poland, Serbia, and the USA . Research examined the impact of populism on four aspects of the pandemic communication circuit during COVID-19: government-led health crisis communication, media policy, media coverage, and public attitudes. A separate strand of research also considered how domestic public debate responded to China and Russia's pandemic geopolitics

I read a USA Today article from June 2020, where they discuss library usage during the pandemic. Some libraries set up wi-fi networks that extended outside the building, so that people would have access to the Internet even when the library was shutdown. This had me curious about how many people have convenient access to the Internet. There are some companies that rely on web pages instead of phone numbers for customer service. If someone wanted to determine the validity of claims and rumors spread by social media, they either need to have a trusted radio/television new source, or they need convenient access to the Internet to be able to investigate the information (by searching for original articles or unaltered video).

I found a pair of datasets that had information that would let me look at the situation. But while doing data cleaning, I found some problems that required significant effort to diagnose. I figured it would be useful to create a new dataset, and provide it on Kaggle in case others were interested.

I started with the dataset provided by the Institute of Museum and Library Services (IMLS), titled "IMLS Indicators Workbook: Economic Status and Broadband Availability and Adoption". The workbook contained statistics blended from three sources: the U.S. Census Bureau American Community Survey (ACS 5-year 2014-2018 estimates); broadbandnow.com (commercial aggregator of FCC data); and the Bureau of Labor Statistics (local area unemployment statistics).

On December 10, 2020, BroadbandNow.Com (bbn) provided a dataset hosted at GitHub as part of their Open Data Challenge. This had the features I wanted to cross check with the IMLS dataset.

I decided it would be worth it to do a partial clean-up of both sets, and then merge them to create a dataset with fewer problems. However, that still required some choices and compromises, so not problem-free. For example, I retained the 3 BBN features that were present in the original IMLS file, but I plan to use the information saved directly from the BBN file instead.

The aim of the special survey of the GESIS panel on the outbreak of the corona virus SARS-CoV-2 in Germany was to collect timely data on the effects of the corona crisis on people´s daily lives. The study focused on questions of risk perception, risk minimization measures, evaluation of political measures and their compliance, trust in politics and institutions, changed employment situation, childcare obligations, and media consumption. Due to the need for timely data collection, only the GESIS panel sub-sample of online respondents was invited (about three quarters of the sample). Since, due to time constraints, respondents could only participate in the online survey but not by mail, the results cannot be easily transferred to the overall population. Further longitudinal surveys on Covid-19 with the entire sample of the GESIS panel are planned for 2020.

Topics: Risk perception: Probability of events related to corona infection in the next two months (self, infection of a person from close social surrondings, hospital treatment, quarantine measures regardless of whether infected or not, infecting other people)

Risk minimization: risk minimization measures taken in the last seven days (avoided certain (busy) places, kept minimum distance to other people, adapted school or work situation, quarantine due to symptoms or without symptoms, washed hands more often, used disinfectant, stocks increased, reduced social interactions, worn face mask, other, none of these measures).

Evaluation of the effectiveness of various policy measures to combat the further spread of corona virus (closure of day-care centres, kindergartens and schools, closure of sports facilities, closure of bars, cafés and restaurants, closure of all shops except supermarkets and pharmacies, ban on visiting hospitals, nursing homes and old people´s homes, curfew for persons aged 70 and over or people with health problems or for anyone not working in the health sector or other critical professions (except for basic purchases and urgent medical care).

Curfew compliance or refusal: Willingness to obey a curfew vs. refusal; reasons for the compliance with curfew (social duty, fear of punishment, protection against infection, fear of infecting others (loved ones, infecting others in general, a risk group); reasons for refusal of curfew (restrictions too drastic or not justified, other obligations, does not stop the spread, not affected by the outbreak, boring at home, will not be punished).

Evaluation of the effectiveness of various government measures (medical care, restrictions on social life such as closure of public facilities and businesses, reduction of economic damage, communication with the population).

Trust in politics and institutions with regard to dealing with the coronavirus (physician, local health authority, local and municipal administration, Robert Koch Institute (RKI), Federal Government, German Chancellor, Ministry of Health, World Health Organization (WHO), scientists).

Changed employment situation: employment status at the beginning of March; change in occupational situation since the spread of coronavirus: dependent employees: number of hours reduced, number of hours increased, more home office, leave of absence with/ without continued wage payment , fired, no change; self-employed: working hours reduced, working hours increased, more home office, revenue decreased, revenue increased, company temporarily closed by the authorities, company temporarily voluntarily closed, financial hardship, company permanently closed or insolvent, no change.

Childcare: children under 12 in the household; organisation of childcare during the closure of day-care centres, kindergartens and schools (staying at home, partner stays at home, older siblings take care, grandparents are watching, etc.)

Media consumption on Corona: information sources used for Corona (e.g. nationwide public or private television or radio, local public or private television or radio, national newspapers or local newspapers, Facebook, other social media, personal conversations with friends and family, other, do not inform myself on the subject); frequency of Facebook usage; information about Corona obtained from regional Facebook page or regional Facebook group.

Demography: sex; age (categorized); education (categorized); intention to vote and choice of party (Sunday question); Left-right self-assessment; marital status; size of household.

Additionally coded: Respondent ID;...

Data from a survey held in August 2022 in the United States revealed that the most popular news source among millennials was social media, with 45 percent of respondents reporting daily news consumption on social networks. This was more than double the share who got their news via radio. When it comes to trust, though, social media does not fare well.

Social media and news consumption

As adults of all ages spend more and more time on social media, news consumption via this avenue is likely to increase, but something which could affect this trend is the lack of trust in the news consumers encounter on social platforms. Although now the preferred option for younger audiences, social networks are among the least trusted news sources in the United States, and concerns about fake news remain prevalent.

Young audiences and fake news

Inaccurate news is a major problem which worsened during the 2016 and 2020 presidential election campaigns and the COVID-19 pandemic. A global study found that most Gen Z and Millennial news consumers ignored fake coronavirus news on social media, but almost 20 percent interacted with such posts in the comments section, and over seven percent shared the content. Younger news consumers in the United States were also the most likely to report feeling overwhelmed by COVID-19 news. As younger audiences were the most likely to get their updates on the outbreak via social media, this also made them the most susceptible to fake news, and younger generations are also the most prone to ‘doomscrolling’, an addictive act where the reader pursues and digests multiple negative or upsetting news articles in one sitting.

The Illiberal Turn project aims to carry out the first-ever systematic, comparative study of news consumption and political polarization in Central and Eastern Europe, at a key point in time when the region is undergoing dramatic changes. The project employs comparative study of news consumption and political attitudes, using a novel multi-method analytical framework that combines survey data, media diaries, and qualitative interviews with audiences in four CEE countries: the Czech Republic, Hungary, Poland, and Serbia. The quantitative element of the project involved a longitudinal and a comparative study. The longitudinal study was conducted during the European Parliament election campaign in May 2019 in the Czech Republic, and is comprised of digital tracking of news consumption, as well as pre-and post-election population surveys, which collect data about peoples’ media consumption habits, perceptions of the EU, general political attitudes and political participation, including voting. The comparative study consists of a population survey conducted between November 2019 and January 2020 in four countries: the Czech Republic, Hungary, Poland, and Serbia. These questionnaires collect data about peoples’ a) sources of news and patterns of news consumption, as well as media bias perceptions; and b) political attitudes, support for populist and right-wing arguments, support for (liberal) democratic values, trust in democratic institutions, and political participation, including voting. The quantitative data uploaded here includes the two datasets (one for the longitudinal study and one for the comparative study), as well as their corresponding codebooks and questionnaires. The qualitative side of the project involved two rounds of qualitative semi-structured interviews, conducted between February and May 2020 (media diaries are not included herein). The first round of interviews, conducted in February and March 2020 in participants' native language, covered topics like every day routines, political engagement, the media environment, and news consumption routines and preferences; these interviews also made use of a 'card exercise', where participants ranked the personal importance of various media types and news sources (not included herein). In the second round of interviews participants were mainly asked to discuss their media diaries and the COVID-19 pandemic. The qualitative data uploaded here includes the Participant Information Sheets and Consent Forms (in English, Czech, Hungarian, Polish, Serbian), First Interview Protocol (all languages), Second Interview Protocol (all languages), and English transcriptions of all first and second round interviews.

Recent years have seen worrying political developments across both old and new democracies, ranging from the rise of populist leaders and dwindling support for democratic rule to the growing polarization of public opinion, evident in the stark divergence of political attitudes among both political elites and the general electorate. Many of these transformations have been linked to changes in information environments, and specifically to the growth of social media and digital platforms, which have given unprecedented visibility to populist rhetoric and hate speech, facilitated the spreading of misinformation, and allegedly encouraged the formation of ideological 'echo chambers'. According to many commentators, these developments contribute to the erosion of the public sphere, particularly in light of the gradual weakening of the role of professional, legacy news media organizations as primary providers of political information. With the proliferation of various "alternative", hyperpartisan online news sources whose content gets amplified via social media, unverified information, unchecked claims and fringe opinions spread virally and get exploited by populist actors and movements. While these tendencies currently pose challenges to democracies across the world, their impact is particularly detrimental in countries that have a shorter history of democratic development and where democratic institutions are more fragile. This is the case in Central and Eastern Europe (CEE), a region that has recently experienced an unprecedented decline in the quality of democracy, a resurgence of illiberal nationalism, and a shift towards authoritarian forms of government. These troublesome developments are arguably threatening to reverse the process of post-1989 transition following the fall of communism. This makes the research into the relationship between media use, political attitudes and behaviour, and popular support for democracy in CEE particularly topical - especially given the fact that systematic research into these issues has so far been limited largely to the U.S. and Western Europe. The ambition of this project is therefore to fill this gap, and to carry out the first-ever systematic, comparative study of news consumption and political polarization in Central and Eastern Europe, at a key point in time when the region is undergoing dramatic changes. This is achieved by means of a comparative study of news consumption an political attitudes, using a novel multi-method analytical framework that combines survey data, digital tracking of media consumption, as well as media diaries and qualitative interviews with audiences in four CEE countries. While empirically focused on CEE, the project also makes a key contribution to general debates on political polarization, populism, nationalism and related phenomena (a) by clarifying the role of the changing media environment in these phenomena, and (b) by pioneering a new multi-method comparative framework that can be adapted for similar research elsewhere in the world. Given the urgent nature of developments in CEE, the project also includes a significant impact component. We have collaborated with several CEE-based and pan-European organizations and associations representing media regulators and journalists, dedicated to the promotion of media literacy, media pluralism and freedom. Through designated activities with these partners we seek to influence both professional and public debate concerning the political impact of the changing news environment in CEE, and contribute to the development of regulatory frameworks, professional standards and civil society activities designed to counter the growth of media partisanship and the spreading of disinformation and "fake news" via online media channels.