Tracking and analysis of discourse dynamics and polarity during the early Corona pandemic in Iran

Spatio-temporal evaluation of social media as a tool for livestock disease surveillance

“…For instance, Aria et al (2022) highlighted that the pandemic caused a rise in social media usage for sharing experiences and seeking information, impacting discussions on diverse subjects, including animal diseases [ 16 ]. Jafarinejad et al (2021) made a similar observation, stating that the pandemic in 2021 highlighted how social discourse underwent extreme changes, impacting community morale and polarisation, with potential implications for discussions [ 17 ].…”

Novel informatics approaches to COVID-19 Research: From methods to applications

“…(1) Wu et al [33] proposed an unsupervised approach that can efficiently mine clinically relevant information from a set of about 52 million COVID-19-related tweets, enabling real-time analysis of social media signals without much manual annotation. Two other papers have focused on detecting public perceptions on social distancing: (2) one was to detect facets of social distancing in a spatiotemporal context using US-based tweets [34] and (3) another one was to analyze social media data and news stories in Iran (Persian), to track discourse dynamics and analyze polarity from the community [35] . Methods proposed by those papers provide new ways to extract and analyze social media data during the COVID-19 pandemic, which can be applied to future pandemics, e.g., to understand public perception and to identify misinformation from social media.…”

“… Original Research [34] Defining facets of social distancing during the COVID-19 pandemic: Twitter analysis Kwon, J. Original Research [35] Tracking and analysis of discourse dynamics and polarity during the early Corona pandemic in Iran Jafarinejad, F. Special Communication [36] Building an OMOP common data model-compliant annotated corpus for COVID-19 clinical trials Sun, Y. Original Research Translational bioinformatics (4) [37] A scheme for inferring viral-host associations based on codon usage patterns identifies the most affected signaling pathways during COVID-19 Das, J. K. Original Research [38] Causal discovery using compression-complexity measures Sy, P. Original Research [39] Machine learning enabled identification of potential SARS-CoV-2 3CLpro inhibitors based on fixed molecular fingerprints and Graph-CNN neural representations Haneczok, J.…”

Political and Economic Patterns in COVID-19 News: From Lockdown to Vaccination

“…hourly, daily, monthly, or yearly). In fact, the order and arrangement of documents reflects the evolving set of topics [39]. These pooling techniques are famous for social media where set of documents/tweets are partitioned based on hashtags, and authors, etc.…”