ABSTRACT
An information outbreak occurs on social media along with the COVID-19 pandemic and leads to an infodemic. Predicting the popularity of online content, known as cascade prediction, allows for not only catching in advance information that deserves attention, but also identifying false information that will widely spread and require quick response to mitigate its negative impact. Among the various information diffusion patterns leveraged in previous works, the spillover effect of the information exposed to users on their decisions to participate in diffusing certain information has not been studied. In this paper, we focus on the diffusion of information related to COVID-19 preventive measures due to its special role in consolidating public efforts to slow down the spread of the virus. Through our collected Twitter dataset, we validate the existence of the spillover effects. Building on this finding, we propose extensions to three cascade prediction methods based on Graph Neural Networks (GNNs). Experiments conducted on our dataset demonstrated that the use of the identified spillover effects significantly improves the state-of-the-art GNN methods in predicting the popularity of not only preventive measure messages, but also other COVID-19 messages.
ABSTRACT
The outbreak of the COVID-19 led to a burst of information in major online social networks (OSNs). Facing this constantly changing situation, OSNs have become an essential platform for people expressing opinions and seeking up-to-the-minute information. Thus, discussions on OSNs may become a reflection of reality. This paper aims to figure out how Twitter users in the Greater Region (GR) and related countries react differently over time through conducting a data-driven exploratory study of COVID-19 information using machine learning and representation learning methods. We find that tweet volume and COVID-19 cases in GR and related countries are correlated, but this correlation only exists in a particular period of the pandemic. Moreover, we plot the changing of topics in each country and region from 22 January 2020 to 5 June 2020, figuring out the main differences between GR and related countries.
ABSTRACT
To describe the epidemiological and clinical characteristics of patients with Corona Virus Disease 2019 (COVID-19) in Beijing. To analyze the application of corticosteroids in patients with severe pneumonia. We collected information on demographic characteristics, exposure history, clinical characteristics, corticosteroids use, and outcomes of the 65 confirmed cases of COVID-19 at Fifth Medical Center of PLA General Hospital from Jan 20 to Feb 23, 2020. The final follow-up date observed was April 15th, 2020. The number of patients with mild, general, severe, and critical type were 10 (15.38%), 32 (49.23%), 8 (12.31%), and 15 (23.08%), respectively. The median incubation period was 6 days. Notable outliers were 1 patient at 16 days and 1 patient at 21 days. In lymphocyte subgroup analysis, decreases in total, T, CD4, and CD8 lymphocytes were more common as the disease worsened (All P < 0.05). Methylprednisolone (mPSL) was applied to 31 (47.69%) patients with pneumonia, including 10 (31.25%) general, 8 (100%) severe, and 13 (86.67%) critical patients, respectively. Corticosteroids inhibited Interleukin-6(IL-6) production (P = 0.0215) but did not affect T lymphocyte (P = 0.0796). There was no significant difference between patients using lower dose (≤ 2 mg/kg day) and higher dose (> 2 mg/kg day) mPSL in inhibiting IL-6 production (P = 0.5856). Thirty of 31 patients (96.77%) had stopped mPSL due to improvement of pneumonia. Virus RNA clearance time lengthened with disease progression (P = 0.0001). In general type, there was no significant difference in virus clearance time between patients with (15, 12-19 days) and without (14.5, 11-18 days) (P = 0.7372) mPSL use. Lymphocyte, especially T lymphocyte, in severe and critical patients showed a dramatic decrease. Application of lower dose corticosteroids (≤ 2 mg/kg day) could inhibit IL-6 production (a representative of cytokines) as effectively as a higher dose. Proper use corticosteroids in general type patients did not delay virus clearance.