An iterative topic model filtering framework for short and noisy user-generated data: analyzing conspiracy theories on twitter [0.03%]
一种迭代主题模型过滤框架：用于分析短而杂乱的用户生成数据中的阴谋论
Gillian Kant,Levin Wiebelt,Christoph Weisser et al.
Gillian Kant et al.
Conspiracy theories have seen a rise in popularity in recent years. Spreading quickly through social media, their disruptive effect can lead to a biased public view on policy decisions and events. We present a novel approach for LDA-pre-pro...
Explainability of the COVID-19 epidemiological model with nonnegative tensor factorization [0.03%]
基于非负张量分解的COVID-19流行病模型的可解释性研究
Thirunavukarasu Balasubramaniam,David J Warne,Richi Nayak et al.
Thirunavukarasu Balasubramaniam et al.
The world is witnessing the devastating effects of the COVID-19 pandemic. Each country responded to contain the spread of the virus in the early stages through diverse response measures. Interpreting these responses and their patterns globa...
Ensemble clustering of longitudinal bivariate HIV biomarker profiles to group patients by patterns of disease progression [0.03%]
通过联合聚类HIV生物标志物纵向双变量资料对患者进行分组以了解疾病的进展规律
Miranda L Lynch,Victor DeGruttola
Miranda L Lynch
This paper describes an ensemble cluster analysis of bivariate profiles of HIV biomarkers, viral load and CD4 cell counts, which jointly measure disease progression. Data are from a prevalent cohort of HIV positive participants in a clinica...
Eigenvalue analysis of SARS-CoV-2 viral load data: illustration for eight COVID-19 patients [0.03%]
SARS-CoV-2病毒载量数据的特征值分析及八例COVID-19患者的特征描述
Till D Frank
Till D Frank
Eigenvalue analysis is an important tool in economics and nonlinear physics to analyze industrial processes and instability phenomena, respectively. A model-based eigenvalue analysis of viral load data from eight symptomatic COVID-19 patien...
Sadiq Muhammed T,Saji K Mathew
Sadiq Muhammed T
The spread of misinformation in social media has become a severe threat to public interests. For example, several incidents of public health concerns arose out of social media misinformation during the COVID-19 pandemic. Against the backdro...
Beyond belief: a cross-genre study on perception and validation of health information online [0.03%]
超越信念：网上健康信息感知与确认的跨类型研究
Chaoyuan Zuo,Kritik Mathur,Dhruv Kela et al.
Chaoyuan Zuo et al.
Natural language undergoes significant transformation from the domain of specialized research to general news intended for wider consumption. This transition makes the information vulnerable to misinterpretation, misrepresentation, and inco...
Fake news detection based on news content and social contexts: a transformer-based approach [0.03%]
基于新闻内容和社会背景的假新闻检测：一种Transformer方法
Shaina Raza,Chen Ding
Shaina Raza
Fake news is a real problem in today's world, and it has become more extensive and harder to identify. A major challenge in fake news detection is to detect it in the early phase. Another challenge in fake news detection is the unavailabili...
A spatiotemporal machine learning approach to forecasting COVID-19 incidence at the county level in the USA [0.03%]
一种用于预测美国县一级COVID-19病例的时空机器学习方法
Benjamin Lucas,Behzad Vahedi,Morteza Karimzadeh
Benjamin Lucas
With COVID-19 affecting every country globally and changing everyday life, the ability to forecast the spread of the disease is more important than any previous epidemic. The conventional methods of disease-spread modeling, compartmental mo...
The impact of information sources on COVID-19 knowledge accumulation and vaccination intention [0.03%]
信息来源对新冠肺炎知识积累和疫苗接种意愿的影响
Madalina Vlasceanu,Alin Coman
Madalina Vlasceanu
During a global health crisis, people are exposed to vast amounts of information from a variety of sources. Here, we assessed which information source could increase knowledge about COVID-19 (Study 1) and COVID-19 vaccines (Study 2). In Stu...
Conspiracy theories on Twitter: emerging motifs and temporal dynamics during the COVID-19 pandemic [0.03%]
新冠疫情下Twitter上的阴谋论：新兴模式和时间演变特性分析
Veronika Batzdorfer,Holger Steinmetz,Marco Biella et al.
Veronika Batzdorfer et al.
The COVID-19 pandemic resulted in an upsurge in the spread of diverse conspiracy theories (CTs) with real-life impact. However, the dynamics of user engagement remain under-researched. In the present study, we leverage Twitter data across 1...