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8 results for “vaccine misinformation”
A Novel Dataset of Misinformation Tweets Regarding the CoronaVac Vaccine in Brazil
<p>This dataset was built to analyze the spread of misinformation about CoronaVac in Brazil by using data from Twitter for two specific events: the approval for emergency use in adults over 18 years old (January 17, 2021) and the approval for use in children aged 6 to 17 years (January 20, 2022).</p> <p>We choose to label the original tweets with at least one retweet in the analyzed period. The manual labeling of such tweets was initially performed by two annotators with high knowledge about the dataset and the considered context. In cases in which there was no agreement between the two annotators, a third annotator was considered to define the class of the tweet. </p> <p>The final dataset contains <strong>1,010 tweets from January 17, 2021</strong>, and <strong>816 tweets from January 20, 2022</strong>.</p> <p>This dataset was originally built for a conference paper accepted at BraSNAM 2022. If you make use of the dataset, please also cite the following paper:</p> <p><em>Gabriel P. Oliveira, Beatriz F. Paiva, Ana Paula Couto da Silva, and Mirella M. Moro. Characterizing the Diffusion of Misinformation Regarding the CoronaVac Vaccine in Brazil. In Proceedings of the XI Brazilian Workshop on Social Network Analysis and Mining </em><em>(BraSNAM 2022), 2022.</em></p> <pre><code>@inproceedings{brasnam/OliveiraPSM22, title = {Characterizing the Diffusion of Misinformation Regarding the CoronaVac Vaccine in Brazil}, author = {Gabriel P. Oliveira and Beatriz F. Paiva and Ana Paula Couto da Silva and Mirella M. Moro}, booktitle = {Proceedings of the XI Brazilian Workshop on Social Network Analysis and Mining (BraSNAM)} year = {2022} }</code></pre>
Twitter vaccine misinformation data
<p>Anti-vaccine content is rapidly propagated via social media, fostering vaccine hesitancy, while pro-vaccine content has not replicated the opponent's successes. Despite this disparity in the dissemination of anti- and pro-vaccine posts, linguistic features that facilitate or inhibit the propagation of vaccine-related content remain less known. Moreover, most prior machine-learning algorithms classified social-media posts into binary categories (e.g., misinformation or not) and have rarely tackled a higher-order classification task based on divergent perspectives about vaccines (e.g., anti-vaccine, pro-vaccine, and neutral). Our objectives are (1) to identify sets of linguistic features that facilitate and inhibit the propagation of vaccine-related content and (2) to compare whether anti-vaccine, pro-vaccine, and neutral tweets contain either set more frequently than the others. To achieve these goals, we collected a large set of social media posts (over 120 million tweets) between Nov. 15 and Dec. 15, 2021, coinciding with the Omicron variant surge. A two-stage framework was developed using a fine-tuned BERT classifier, demonstrating over 99 and 80 percent accuracy for binary and ternary classification. Finally, the Linguistic Inquiry Word Count text analysis tool was used to count linguistic features in each classified tweet. Our regression results show that anti-vaccine tweets are propagated (i.e., retweeted), while pro-vaccine tweets garner passive endorsements (i.e., favorited). Our results also yielded the two sets of linguistic features as facilitators and inhibitors of the propagation of vaccine-related tweets. Finally, our regression results show that anti-vaccine tweets tend to use the facilitators, while pro-vaccine counterparts employ the inhibitors. These findings and algorithms from this study will aid public health officials' efforts to counteract vaccine misinformation, thereby facilitating the delivery of preventive measures during pandemics and epidemics.</p>
Global misinformation spillovers in the online vaccination debate before and during COVID-19 - ex
<p>The dataset includes all the ids of the tweets analysed in the paper "Global misinformation spillovers in the online vaccination debate before and during COVID-19", divided by lang.</p> <p>They are all the tweets containing vaccines keywords in 18 different European languages, spanning the period October 2019 - March 2021 (excluded 2020 Jan - 2020 Jun).</p> <p>Note that a large fraction of the tweets can't be retrieved because of the suspension of the accounts and the removal of the posts by the users, so the study is only partially reproducible.</p> <p>The unzipped dataset has a dimension of 8,0G.</p> <p>The authors of the paper are: Lenti J, Mejova Y, Kalimeri K, Panisson A, Paolotti D, Tizzani M, Starnini M.</p>
Twitter vaccine misinformation data
Open the record for dataset details and reuse information.
Global misinformation spillovers in the online vaccination debate before and during COVID-19
<p>The dataset includes all the ids of the tweets analysed in the paper "Global misinformation spillovers in the online vaccination debate before and during COVID-19", divided by lang.</p> <p>They are all the tweets containing vaccines keywords in 18 different European languages, spanning the period October 2019 - March 2021 (excluded 2020 Jan - 2020 Jun).</p> <p>Note that a large fraction of the tweets can't be retrieved because of the suspension of the accounts and the removal of the posts by the users, so the study is only partially reproducible.</p> <p>The unzipped dataset has a dimension of 8,0G.</p> <p>The authors of the paper are: Lenti J, Mejova Y, Kalimeri K, Panisson A, Paolotti D, Tizzani M, Starnini M.</p>
Impact of a Mock-up Fact-checking Extension on HPV Vaccine Misinformation: A Survey Experiment
ClinicalTrials.gov study NCT06405048. IPD Sharing: YES. Countries: 1. Publications: 17.
Protecting Against HIV Vaccine Misinformation With Adolescent Girls and Young Women in South Africa
ClinicalTrials.gov study NCT06700447. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
Can Doctors Reduce COVID-19 Misinformation and Increase Vaccine Uptake in Ghana? A Cluster-randomised Controlled Trial
ClinicalTrials.gov study NCT06191211. IPD Sharing: YES. Countries: 1. Publications: 0.
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