Investigating Lexical Concept and Semantic Representation of COVID-19 in Coronavirus Corpus: A Corpus-Based Study

This article discusses the lexical and semantic representation through the collocation that appeared in the Coronavirus Corpus. This research investigates the frequent collocates that appeared together with the node word Corona and find out how those collocates construct the meaning through the linguistic system and conceptual system as they are involved in lexical representation. This research offers a new insight into teaching language using Lexical Concepts and Cognitive Models (Evans, 2009). The data collected are from the Coronavirus corpus by using the corpus-based method. The strength of the keywords and collocate is measured by using Mutual Information (MI). The MI was set in 5, therefore, three lexemes resulted, i.e., cases, patients, and outbreak. The data were analyzed using the lexical concept and cognitive model proposed by Evans (2009). The research results, in general, reveal that the information is coming from the "authorized institution" and "government's representative", it needs "the official approval or agreement" before publishing to the media, and in the passive form, it describes the foregrounded information and agentless informational assertion. Therefore, the information should be accurate and firm. However, another lexical concept reveals that the information is terrorizing and terrifying, the educated and trained person should also conduct the treatment.

A Corpus-Based Comparison of Inclusiveness in L2 Reading Materials for Refugee Children

Despite increased emphasis on the role of inclusive practices and materials in post-COVID-19 classrooms and warnings about implicit biases against disadvantaged groups, the textbook problem has rarely been approached with equity measures in mind. This multimethod study aimed to investigate to what extent L2 reading materials, locally produced and used for refugee education in Turkey and New Zealand, include all children with different proficiency levels, gender identities and cultural backgrounds using corpus-driven methods. All verbal and nonverbal texts from ten thematically similar third-grade storybooks were subjected to qualitative and quantitative analysis. Comparisons against measures of grammatical and lexical complexity, and of gender and cultural equity revealed that despite both being far from achieving the ideal composition for creating inclusive learning-friendly environments, TSL materials were lagging further behind ESL counterparts. They depended on almost uniform sets of easy-to-read narratives embodying simpler grammatical features and high-frequency words, and thus needed extension with relatively elaborate ones to accommodate mixed-abilities. Gender disparities were institutionalised through male overrepresentation in hero-making, negative stereotyping, familial and occupational identification, and engagement in monetary and mobility activities, but occasionally ameliorated, in the ESL case, by reversing conventionally-gendered domestic, technical and intellectual skills in texts and illustrations. The widest gap was observed in cultural representations because TSL materials, written from a tourist's perspective, focused on imposing superficial knowledge of target-culture elements, and ESL materials on ensuring relevance through greater use of elements from diverse cultures. Therefore, egalitarian representations in gendered and cultural contents are required for their rehabilitation.

Have Patients' Attitudes towards Doctors Changed with COVID-19? Insights from Online Doctor Reviews in Beijing, China

The COVID-19 pandemic has brought many challenges, including doctor-patient relationships (DPRs). This study aims to investigate the change in patients' attitudes towards doctors during the pandemic. We collected 24,000 reviews in Beijing, China from an online health platform, with half of the data from 2019 and another half from 2020. These data were compared using sentiment and word frequency analyses. Results show that the number of negative reviews has reduced significantly, and the salient topics of negative reviews have shifted from doctor-related to administration-related. These findings suggest that the DPRs have improved but there is room for managerial improvements in the health sector. © 2022 ACM.

Changes in Doctor-Patient Relationships in China during COVID-19: A Text Mining Analysis.

Doctor-patient relationships (DPRs) in China have been straining. With the emergence of the COVID-19 pandemic, the relationships and interactions between patients and doctors are changing. This study investigated how patients' attitudes toward physicians changed during the pandemic and what factors were associated with these changes, leading to insights for improving management in the healthcare sector. This paper collected 58,600 comments regarding Chinese doctors from three regions from the online health platform Good Doctors Online (haodf.com, accessed on 13 October 2022). These comments were analyzed using text mining techniques, such as sentiment and word frequency analyses. The results showed improvements in DPRs after the pandemic, and the degree of improvement was related to the extent to which a location was affected. The findings also suggest that administrative services in the healthcare sector need further improvement. Based on these results, we summarize relevant recommendations at the end of this paper.

The Language of Russian Fake Stories: A Corpus-Based Study of the Topical Change in the Viral Disinformation

The spread of disinformation during the Covid-19 pandemic is largely associated with social media and online messengers. Viral disinformation disseminated in 2020-2021 was related to a wide range of topics that caused panic among people. Many false narratives emerged and attracted public interest over time, which mainly reflected the general public's utmost belief in these topics. Text mining can be used to analyze the frequencies of keywords and topic-related vocabulary in order to track the changing focus of the public concerning online disinformation. In this paper, we present the results of a corpus-based study of Russian viral fake stories circulating during the first year of the Covid-19 pandemic. We propose a method for analyzing the central topics and dynamics of topical change in the context of the Russian Covid-19-fake story. In order to accomplish this objective, we make use of a set of tools to extract keywords, count their frequencies and analyze corresponding contexts. We apply these tools to the compiled specialized diachronic corpus of Russian viral false Covid-19-related stories. The obtained data is evaluated to determine the dynamic of topical shifts by tracking the changes in keyword frequencies as well as the use of other high-frequency corpus words. The findings of the work concerning topical fluctuations in the Russian viral Covid-19 disinformation agenda as well as given explanations for the identified drifts in public interest in the topics during the first year of the pandemic can contribute to developing effective strategies for combating the spread of fakes in the future.

Perinatal Distress During COVID-19: Thematic Analysis of an Online Parenting Forum.

BACKGROUND: The COVID-19 global pandemic has impacted the whole of society, requiring rapid implementation of individual-, population-, and system-level public health responses to contain and reduce the spread of infection. Women in the perinatal period (pregnant, birthing, and postpartum) have unique and timely needs for directives on health, safety, and risk aversion during periods of isolation and physical distancing for themselves, their child or children, and other family members. In addition, they are a vulnerable group at increased risk of psychological distress that may be exacerbated in the context of social support deprivation and a high-risk external environment. OBJECTIVE: The aim of this study is to examine the public discourse of a perinatal cohort to understand unmet health information and support needs, and the impacts on mothering identity and social dynamics in the context of COVID-19. METHODS: A leading Australian online support forum for women pre- through to postbirth was used to interrogate all posts related to COVID-19 from January 27 to May 12, 2020, inclusive. Key search terms included "COVID," "corona," and "pandemic." A three-phase analysis was conducted, including thematic analysis, sentiment analysis, and word frequency calculations. RESULTS: The search yielded 960 posts, of which 831 were included in our analysis. The qualitative thematic analysis demonstrated reasonable understanding, interpretation, and application of relevant restrictions in place, with five emerging themes identified. These were (1) heightened distress related to a high-risk external environment; (2) despair and anticipatory grief due to deprivation of social and family support, and bonding rituals; (3) altered family and support relationships; (4) guilt-tampered happiness; and (5) family future postponed. Sentiment analysis revealed that the content was predominantly negative (very negative: n=537 and moderately negative: n=443 compared to very positive: n=236 and moderately positive: n=340). Negative words were frequently used in the 831 posts with associated derivatives including "worried" (n=165, 19.9%), "risk" (n=143, 17.2%), "anxiety" (n=98, 11.8%), "concerns" (n=74, 8.8%), and "stress" (n=69, 8.3%). CONCLUSIONS: Women in the perinatal period are uniquely impacted by the current pandemic. General information on COVID-19 safe behaviors did not meet the particular needs of this cohort. The lack of nuanced and timely information may exacerbate the risk of psychological and psychosocial distress in this vulnerable, high-risk group. State and federal public health departments need to provide a central repository of information that is targeted, consistent, accessible, timely, and reassuring. Compensatory social and emotional support should be considered, using alternative measures to mitigate the risk of mental health disorders in this cohort.

The Impact of COVID-19 Epidemic Declaration on Psychological Consequences: A Study on Active Weibo Users.

COVID-19 (Corona Virus Disease 2019) has significantly resulted in a large number of psychological consequences. The aim of this study is to explore the impacts of COVID-19 on people's mental health, to assist policy makers to develop actionable policies, and help clinical practitioners (e.g., social workers, psychiatrists, and psychologists) provide timely services to affected populations. We sample and analyze the Weibo posts from 17,865 active Weibo users using the approach of Online Ecological Recognition (OER) based on several machine-learning predictive models. We calculated word frequency, scores of emotional indicators (e.g., anxiety, depression, indignation, and Oxford happiness) and cognitive indicators (e.g., social risk judgment and life satisfaction) from the collected data. The sentiment analysis and the paired sample t-test were performed to examine the differences in the same group before and after the declaration of COVID-19 on 20 January, 2020. The results showed that negative emotions (e.g., anxiety, depression and indignation) and sensitivity to social risks increased, while the scores of positive emotions (e.g., Oxford happiness) and life satisfaction decreased. People were concerned more about their health and family, while less about leisure and friends. The results contribute to the knowledge gaps of short-term individual changes in psychological conditions after the outbreak. It may provide references for policy makers to plan and fight against COVID-19 effectively by improving stability of popular feelings and urgently prepare clinical practitioners to deliver corresponding therapy foundations for the risk groups and affected people.