A Dashboard Approach to Monitoring Mpox-Related Discourse and Misinformation on Social Media
- URL: http://arxiv.org/abs/2505.20584v1
- Date: Mon, 26 May 2025 23:34:41 GMT
- Title: A Dashboard Approach to Monitoring Mpox-Related Discourse and Misinformation on Social Media
- Authors: Linfeng, Zhao, Rishul Bhuvanagiri, Blake Gonzales, Kellen Sharp, Dhiraj Murthy,
- Abstract summary: Mpox (formerly monkeypox) is a zoonotic disease caused by an orthopoxvirus.<n>During outbreaks, social media platforms like X (formerly Twitter) can both inform and misinform the public.<n>We developed a researcher-focused dashboard for use by public health stakeholders and the public.
- Score: 17.50820656964013
- License: http://creativecommons.org/licenses/by-nc-nd/4.0/
- Abstract: Mpox (formerly monkeypox) is a zoonotic disease caused by an orthopoxvirus closely related to variola and remains a significant global public health concern. During outbreaks, social media platforms like X (formerly Twitter) can both inform and misinform the public, complicating efforts to convey accurate health information. To support local response efforts, we developed a researcher-focused dashboard for use by public health stakeholders and the public that enables searching and visualizing mpox-related tweets through an interactive interface. Following the CDC's designation of mpox as an emerging virus in August 2024, our dashboard recorded a marked increase in tweet volume compared to 2023, illustrating the rapid spread of health discourse across digital platforms. These findings underscore the continued need for real-time social media monitoring tools to support public health communication and track evolving sentiment and misinformation trends at the local level.
Related papers
- Bridging the Gap: Leveraging Retrieval-Augmented Generation to Better Understand Public Concerns about Vaccines [0.5277756703318045]
Vaccine hesitancy threatens public health, leading to delayed or rejected vaccines.<n>Social media is a vital source for understanding public concerns, and traditional methods like topic modelling often struggle to capture nuanced opinions.<n>To address these limitations, we developed a tool (VaxPulse Query Corner) using the Retrieval Augmented Generation technique.<n>It addresses complex queries about public vaccine concerns on various online platforms, aiding public health administrators and stakeholders in understanding public concerns and implementing targeted interventions to boost vaccine confidence.
arXiv Detail & Related papers (2025-07-17T06:59:52Z) - Event Detection from Social Media for Epidemic Prediction [76.90779562626541]
We develop a framework to extract and analyze epidemic-related events from social media posts.
Experimentation reveals how ED models trained on COVID-based SPEED can effectively detect epidemic events for three unseen epidemics.
We show that reporting sharp increases in the extracted events by our framework can provide warnings 4-9 weeks earlier than the WHO epidemic declaration for Monkeypox.
arXiv Detail & Related papers (2024-04-02T06:31:17Z) - Visualizing Relation Between (De)Motivating Topics and Public Stance
toward COVID-19 Vaccine [0.0]
In this study, we proposed an interactive visualization tool to inspect and analyze the topics that resonated among Twitter-sphere during the COVID-19 pandemic.
This tool can easily be generalized for any scenario for visual analysis and to increase the transparency of social media data for researchers and the general population alike.
arXiv Detail & Related papers (2023-06-21T09:01:53Z) - Global misinformation spillovers in the online vaccination debate before
and during COVID-19 [5.1598868036106085]
Anti-vaccination views pervade online social media, fueling distrust in scientific expertise and increasing vaccine-hesitant individuals.
Here, we leverage 316 million vaccine-related Twitter messages in 18 languages to quantify misinformation flows between users exposed to anti-vaccination (no-vax) content.
We find that, during the pandemic, no-vax communities became more central in the country-specific debates and their cross-border connections strengthened, revealing a global Twitter anti-vaccination network.
arXiv Detail & Related papers (2022-11-21T14:32:37Z) - "COVID-19 was a FIFA conspiracy #curropt": An Investigation into the
Viral Spread of COVID-19 Misinformation [60.268682953952506]
We estimate the extent to which misinformation has influenced the course of the COVID-19 pandemic using natural language processing models.
We provide a strategy to combat social media posts that are likely to cause widespread harm.
arXiv Detail & Related papers (2022-06-12T19:41:01Z) - Parasocial diffusion: K-pop fandoms help drive COVID-19 public health
messaging on social media [11.772370636609677]
We analyze the online spread of the hashtag #WearAMask and vaccine-related tweets amid anti-mask sentiments and public health misinformation.
Analyses reveal the South Korean boyband BTS as one of the most significant driver of health discourse.
Mechanistically, strong-levels of parasocial engagement and connectedness allow sustained activism in the community.
arXiv Detail & Related papers (2021-10-07T17:55:27Z) - Know it to Defeat it: Exploring Health Rumor Characteristics and
Debunking Efforts on Chinese Social Media during COVID-19 Crisis [65.74516068984232]
We conduct a comprehensive analysis of four months of rumor-related online discussion during COVID-19 on Weibo, a Chinese microblogging site.
Results suggest that the dread (cause fear) type of health rumors provoked significantly more discussions and lasted longer than the wish (raise hope) type.
We show the efficacy of debunking in suppressing rumor discussions, which is time-sensitive and varies across rumor types and debunkers.
arXiv Detail & Related papers (2021-09-25T14:02:29Z) - COVID-19 and Big Data: Multi-faceted Analysis for Spatio-temporal
Understanding of the Pandemic with Social Media Conversations [4.07452542897703]
Social media platforms have served as a vehicle for the global conversation about COVID-19.
We present a framework for analysis, mining, and tracking the critical content and characteristics of social media conversations around the pandemic.
arXiv Detail & Related papers (2021-04-22T00:45:50Z) - Dark Web Marketplaces and COVID-19: before the vaccine [53.447910186085586]
We analyse 851,199 listings extracted from 30 dark web marketplaces between January 1, 2020 and November 16, 2020.
We identify 788 listings directly related to COVID-19 products and monitor the temporal evolution of product categories.
We reveal how the online shadow economy has evolved during the COVID-19 pandemic and highlight the importance of a continuous monitoring of DWMs.
arXiv Detail & Related papers (2020-08-04T14:27:41Z) - Digital Ariadne: Citizen Empowerment for Epidemic Control [55.41644538483948]
The COVID-19 crisis represents the most dangerous threat to public health since the H1N1 pandemic of 1918.
Technology-assisted location and contact tracing, if broadly adopted, may help limit the spread of infectious diseases.
We present a tool, called 'diAry' or 'digital Ariadne', based on voluntary location and Bluetooth tracking on personal devices.
arXiv Detail & Related papers (2020-04-16T15:53:42Z) - Falling into the Echo Chamber: the Italian Vaccination Debate on Twitter [65.7192861893042]
We examine the extent to which the vaccination debate on Twitter is conductive to potential outreach to the vaccination hesitant.
We discover that the vaccination skeptics, as well as the advocates, reside in their own distinct "echo chambers"
At the center of these echo chambers we find the ardent supporters, for which we build highly accurate network- and content-based classifiers.
arXiv Detail & Related papers (2020-03-26T13:55:50Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.