ABSTRACT
In 2020, when COVID-19 struck, social media gained even more influence in people's lives due to increased online activity. This event led to a surge of false information and cyberbullying, making content moderation harder than ever. Given this challenge, exploring opportunities to explore content moderation solutions to reduce hate speech and fake news on social media is vital. In this paper, we examine if existing content moderation systems are enough during global pandemics and, if not, where gaps may lie. Due to its intriguing Decentralized Content Management System (DCMS), we chose Reddit as the key social networking platform for our hypothesis testing. We used 1.8 million Reddit posts from COVID-19-related subreddits from January 2020 to April 2021. Our findings reveal several significant trends regarding the effect of a worldwide event on content moderation methods designed to lessen the prevalence of hazardous content and fake news. In light of these considerations, we provide the results of comprehensive research conducted with particular attention paid to the user-generated material and the DCMS of Reddit. © 2022 ACM.
ABSTRACT
The ongoing COVID-19 pandemic has profoundly impacted people's lives around the world, including how they interact with mobile technologies. In this paper, we seek to develop an understanding of how the dynamic trajectory of a pandemic shapes mobile phone users' experiences. Through the lens of app popularity, we approach this goal from a cross-country perspective. We compile a dataset consisting of six-month daily snapshots of the most popular apps in the iOS App Store in China and the US, where the pandemic has exhibited distinct trajectories. Using this longitudinal dataset, our analysis provides detailed patterns of app ranking during the pandemic at both category and individual app levels. We reveal that app categories' rankings are correlated with the pandemic, contingent upon country-specific development trajectories. Our work offers rich insights into how the COVID-19, a typical global public health crisis, has influence people's day-to-day interaction with the Internet and mobile technologies. © 2022 ACM.
ABSTRACT
The novel coronavirus (COVID-19) pandemic outbreak is drastically shaping and reshaping many aspects of our life, with a huge impact on our social life. In this era of lockdown policies in most of the major cities around the world, we see a huge increase in people and professionals' engagement in social media. Online Social Networks are playing an important role in news propagation as well as keeping people in contact. At the same time, social media is both a blessing and a curse as the coronavirus infodemic has become a major concern, and is already a topic that needs special attention and further research. In this study, we publish a multilingual coronavirus (COVID-19) Instagram dataset that we have continuously collected during the first wave of the pandemic from 5 January 2020 to 30 May 2020. The dataset contains 25.7K posts, 829K comments, and 3.2M likes in various subjects from different publishers such as 'public accounts', 'fake accounts (bots)', 'newsagencies', 'influencers', 'celebrities', 'business pages', etc. In addition to the dataset, this paper provides an analysis of the behaviour of the publishers. We study the behavioural aspects of the users in terms of their engagement, use of hashtags, activities, reactions as well as a full analysis of the published content related to the COVID-19. We believe this contribution helps the research community to better understand the dynamics behind this phenomenon in Instagram, as one of the major social media.
ABSTRACT
This is the artifact accompanying the paper "An Empirical Assessment of Global COVID-19 Contact Tracing Applications", accepted by ICSE 2021. The artifact presents the first automated security and privacy assessment tool that tests contact tracing apps for security weaknesses, malware, embedded trackers and private information leakage. COVIDGUARDIAN outperforms 4 state-of-the-practice industrial and open-source tools. Note that, Although the tool is tailored to focus on contact tracing apps, it can also be adapted to other types of apps with respect to the NLP PII learning context, e.g., by changing the source & sink list or updating the sensitive PII keywords.
ABSTRACT
The rapid spread of COVID-19 has made manual contact tracing difficult. Thus, various public health authorities have experimented with automatic contact tracing using mobile applications (or "apps"). These apps, however, have raised security and privacy concerns. In this paper, we propose an automated security and privacy assessment tool-COVIDGUARDIAN-which combines identification and analysis of Personal Identification Information (PII), static program analysis and data flow analysis, to determine security and privacy weaknesses. Furthermore, in light of our findings, we undertake a user study to investigate concerns regarding contact tracing apps. We hope that COVIDGUARDIAN, and the issues raised through responsible disdosure to vendors, can contribute to the safe deployment of mobile contact tracing. As part of this, we offer concrete guidelines, and highlight gaps between user requirements and app performance.
ABSTRACT
The worldwide spread of COVID-19 has prompted extensive online discussions, creating an 'infodemic' on social media platforms such as WhatsApp and Twitter. However, the information shared on these platforms is prone to be unreliable and/or misleading. In this paper, we present the first analysis of COVID-19 discourse on public WhatsApp groups from Pakistan. Building on a large scale annotation of thousands of messages containing text and images, we identify the main categories of discussion. We focus on COVID-19 messages and understand the different types of images/text messages being propagated. By exploring user behavior related to COVID messages, we inspect how misinformation is spread. Finally, by quantifying the flow of information across WhatsApp and Twitter, we show how information spreads across platforms and how WhatsApp acts as a source for much of the information shared on Twitter.
ABSTRACT
Wastewater monitoring (WM) of SARS-CoV-2 from sewers was applied throughout the world early in the COVID-19 pandemic. Sharing of protocols and experiences in WM of SARS-CoV-2 by national and international researchers and practitioners has been vital to ensuring the sensitivity and specificity of the methods. WM has been a valuable adjunct to human clinical testing, and when positive results occur in sewage, community testing has been increased. WM findings allow public health officials to track and respond to the impacts of loosening lockdown restrictions, demonstrating when return to normal social activities might occur without a resurgence of rapid community transmission, and they are particularly useful in areas with low human case numbers and/or low clinical testing rates. New research is required to address several practical knowledge gaps, for example, sampling protocols, prediction of case prevalence from viral numbers by modelling, and determination of detection limits. Communication to the Australian public of WM of SARS-CoV-2 has been via interactive, visual dashboards. Once SARS-CoV-2 vaccinations are introduced, WM could help track the underlying circulation of the virus in the population, the spread of known variants and its future evolution.
ABSTRACT
Wastewater monitoring (WM) of SARS-CoV-2 from sewers was applied throughout the world early in the COVID-19 pandemic. Sharing of protocols and experiences in WM of SARS-CoV-2 by national and international researchers and practitioners has been vital to ensuring the sensitivity and specificity of the methods. WM has been a valuable adjunct to human clinical testing, and when positive results occur in sewage, community testing has been increased. WM findings allow public health officials to track and respond to the impacts of loosening lockdown restrictions, demonstrating when return to normal social activities might occur without a resurgence of rapid community transmission, and they are particularly useful in areas with low human case numbers and/or low clinical testing rates. New research is required to address several practical knowledge gaps, for example, sampling protocols, prediction of case prevalence from viral numbers by modelling, and determination of detection limits. Communication to the Australian public of WM of SARS-CoV-2 has been via interactive, visual dashboards. Once SARS-CoV-2 vaccinations are introduced, WM could help track the underlying circulation of the virus in the population, the spread of known variants and its future evolution.
ABSTRACT
Rapid spread of the COVID-19 pandemic is making traditional manual contact tracing challenging;in response, digital contact tracing mobile apps have been developed by the software industry and promoted by governments and health authorities worldwide. However, deploying contact tracing apps across a population at scale have raised many privacy concerns. In this paper, we propose a venue-access-based contact tracing solution, VenueTrace, which preserves user privacy by designs by: (i) enabling the contact tracing of venue-to-user, instead of user-to-user;(ii) avoiding information exchanges between users;and (iii) ensuring no private data is exposed to back-end servers, while enabling proximity contact tracing. © 2020 Owner/Author.