Using Twitter-Based Data for Sexual Violence Research: Scoping Review.

BACKGROUND: Scholars have used data from in-person interviews, administrative systems, and surveys for sexual violence research. Using Twitter as a data source for examining the nature of sexual violence is a relatively new and underexplored area of study. OBJECTIVE: We aimed to perform a scoping review of the current literature on using Twitter data for researching sexual violence, elaborate on the validity of the methods, and discuss the implications and limitations of existing studies. METHODS: We performed a literature search in the following 6 databases: APA PsycInfo (Ovid), Scopus, PubMed, International Bibliography of Social Sciences (ProQuest), Criminal Justice Abstracts (EBSCO), and Communications Abstracts (EBSCO), in April 2022. The initial search identified 3759 articles that were imported into Covidence. Seven independent reviewers screened these articles following 2 steps: (1) title and abstract screening, and (2) full-text screening. The inclusion criteria were as follows: (1) empirical research, (2) focus on sexual violence, (3) analysis of Twitter data (ie, tweets or Twitter metadata), and (4) text in English. Finally, we selected 121 articles that met the inclusion criteria and coded these articles. RESULTS: We coded and presented the 121 articles using Twitter-based data for sexual violence research. About 70% (89/121, 73.6%) of the articles were published in peer-reviewed journals after 2018. The reviewed articles collectively analyzed about 79.6 million tweets. The primary approaches to using Twitter as a data source were content text analysis (112/121, 92.5%) and sentiment analysis (31/121, 25.6%). Hashtags (103/121, 85.1%) were the most prominent metadata feature, followed by tweet time and date, retweets, replies, URLs, and geotags. More than a third of the articles (51/121, 42.1%) used the application programming interface to collect Twitter data. Data analyses included qualitative thematic analysis, machine learning (eg, sentiment analysis, supervised machine learning, unsupervised machine learning, and social network analysis), and quantitative analysis. Only 10.7% (13/121) of the studies discussed ethical considerations. CONCLUSIONS: We described the current state of using Twitter data for sexual violence research, developed a new taxonomy describing Twitter as a data source, and evaluated the methodologies. Research recommendations include the following: development of methods for data collection and analysis, in-depth discussions about ethical norms, exploration of specific aspects of sexual violence on Twitter, examination of tweets in multiple languages, and decontextualization of Twitter data. This review demonstrates the potential of using Twitter data in sexual violence research.

Exploring the Influencing Factors of COVID-19 Vaccination Willingness among Young Adults in China

Vaccine uptake is considered as one of the most effective methods of defending against COVID-19 (coronavirus disease 2019). However, many young adults are hesitant regarding COVID-19 vaccines, and they actually play an important role in virus transmission. Based on a multi-theory model, this study aims to explore the influencing factors related to COVID-19 vaccine willingness among young adults in China. Using semi-structured interviews, this study explored the factors that would motivate young adults with vaccine hesitancy to get the COVID-19 vaccine. Thematic analysis was used to analyze the interview data with topic modeling as a complementarity method. After comparing the differences and similarities of results generated by thematic analysis and topic modeling, this study ultimately identified ten key factors related to COVID-19 vaccination intention, including the effectiveness and safety of vaccines, application range of vaccine, etc. This study combined thematic analysis with machine learning and provided a comprehensive and nuanced picture of facilitating factors for COVID-19 vaccine uptake among Chinese young adults. Results may be taken as potential themes for authorities and public health workers in vaccination campaigns.

Exploring the Influencing Factors of COVID-19 Vaccination Willingness among Young Adults in China.

Vaccine uptake is considered as one of the most effective methods of defending against COVID-19 (coronavirus disease 2019). However, many young adults are hesitant regarding COVID-19 vaccines, and they actually play an important role in virus transmission. Based on a multi-theory model, this study aims to explore the influencing factors related to COVID-19 vaccine willingness among young adults in China. Using semi-structured interviews, this study explored the factors that would motivate young adults with vaccine hesitancy to get the COVID-19 vaccine. Thematic analysis was used to analyze the interview data with topic modeling as a complementarity method. After comparing the differences and similarities of results generated by thematic analysis and topic modeling, this study ultimately identified ten key factors related to COVID-19 vaccination intention, including the effectiveness and safety of vaccines, application range of vaccine, etc. This study combined thematic analysis with machine learning and provided a comprehensive and nuanced picture of facilitating factors for COVID-19 vaccine uptake among Chinese young adults. Results may be taken as potential themes for authorities and public health workers in vaccination campaigns.

One microRNA has the potential to target whole viral mRNAs in a given human coronavirus

MicroRNAs (miRNAs) can repress viral replication by targeting viral messenger RNA (mRNA), which makes them potential antiviral agents. The antiviral effects of miRNAs on infectious viruses have been explored extensively;however, recent studies mainly considered the action modes of miRNAs, neglecting another key factor, the molecular biology of viruses, which may be particularly important in the study of miRNA actions against a given virus. In this paper, the action modes of miRNAs and the molecular biology of viruses are jointly considered for the first time and based on the reported roles of miRNAs on viruses and human coronaviruses (HCoVs) molecular biology, the general and specific interaction modes of miRNAs-HCoVs are systematically reviewed. It was found that HCoVs transcriptome is a nested set of subgenomic mRNAs, sharing the same 5′ leader, 3′ untranslated region (UTR) and open reading frame (ORF). For a given HCoV, one certain miRNA with a target site in the 5′ leader or 3’ UTR has the potential to target all viral mRNAs, indicating tremendous antiviral effects against HCoVs. However, for the shared ORFs, some parts are untranslatable attributed to the translation pattern of HCoVs mRNA, and it is unknown whether the base pairing between the untranslated ORFs and miRNAs plays a regulatory effect on the local mRNAs where the untranslated ORFs are located;therefore, the regulatory effects of miRNAs with targets within the shared ORFs are complicated and need to be confirmed. Collectively, miRNAs may bepromising antiviral agents against HCoVs due to their intrinsically nested set of mRNAs, and some gaps are waiting to be filled. In this review, insight is provided into the exploration of miRNAs that can interrupt HCoVs infection.

Attenuated Viral Replication of Avian Infectious Bronchitis Virus with a Novel 82-Nucleotide Deletion in the 5a Gene Indicates a Critical Role for 5a in Virus-Host Interactions.

We previously found that a deletion in γ-coronavirus Infectious bronchitis virus (IBV) accessory gene 5a is critical for decreased viral pathogenicity in chickens. Here, we systematically analyzed IBV virus infection: invasion, genome replication, subgenomic mRNA (sgmRNA) synthesis, protein synthesis, and virion release. The ability of the mutant IBV strain rYN-Δ5a to invade susceptible cells was not significantly different from that of parental rYN. However, compared with rYN, the level of sgmRNA synthesis and genome replication after cell entry by rYN-Δ5a was significantly lower in the early stage, resulting in a significantly lower level of nucleoprotein (N) synthesis and a consequent significantly lower number of offspring viruses released into the supernatant. The detected 5a protein was diffusely distributed in the cytoplasm and perinuclear area. We identified 16 differentially expressed host proteins, 8 of which were found to be host nuclear and cytoplasmic transport-related proteins. Coimmunoprecipitation revealed an interaction between hemagglutinin (HA)-tagged TNPO1, TNPO3, XPO1, XPOT, RanBP1, and EIF2B4 proteins and Flag-tagged 5a protein, and laser confocal microscopy confirmed 5a protein colocalization with these proteins, indicating that 5a protein can cause changes in the host protein localization. These host proteins promote the nuclear localization of N proteins, so we believe that 5a protein can hijack host nucleoplasmic transport-related proteins to help N enter the nucleus. This may involve regulating the cell cycle to promote the optimal intracellular conditions for virus assembly or by participating in the regulation of nucleolar function as a strategy to optimize virus replication. IMPORTANCE Coronaviruses (CoVs) have a huge impact on humans and animals. It is important for the prevention and control of the viruses to assess the molecular mechanisms related to virulence attenuation. Here, we systematically analyzed a single cycle of virus infection by γ-CoV IBV lacking accessory protein 5a. We observed that a 5a deletion in the IBV genome affected virus replication and sgmRNA synthesis early in the virus life cycle, leading to decreases in protein synthesis, offspring virus assembly, and virion release in chicken embryonic kidney cells. IBV 5a protein was found to interact with multiple host nuclear and cytoplasmic transport- and translation-related proteins, which can also interact with IBV N and relocate it into the cell nucleus. These findings provide a comprehensive view regarding the importance of IBV accessory protein 5a and an important theoretical basis for studying the interaction between coronavirus and host cell proteins.

Preventing the Growing Transmission of COVID Clusters: An Integration of the Maslow's Hierarchy of Needs in the Risk Chain.

PURPOSE: China's success in containing the coronavirus is an ongoing process of identifying loopholes and refining the management in the COVID-19 risk chain. This article discusses the role of personal needs in epidemic control and linked psychological needs with management measures to propose intervention advice on curbing viral transmission in a systematic way. METHODS: Based on case studies, we showed the integration of the Maslow's Hierarchy of Needs in the COVID-19 risk chain. The analysis combined the micro-view from individual needs and macro influences from governmental measures. The proposed chain of vulnerabilities could help identify critical links of COVID-19 crisis management in case that cascading effects such as super-spread can be intercepted in time. RESULTS: The article mainly focused on curbing the viral transmission timely whenever cluster of cases resurge. Considering the triggered activities from personal needs may facilitate the spread, minimizing the impact scale while managing the crisis could start with protecting vulnerable population, well governing potential hotspots, and necessary restrictions on group activities. Besides, "individual" protections combined with "institutional" solutions are strongly advocated. The worst scenario would be the governance link slackened or made mistakes, together with delayed identification, plus unprotected way of living and gathering. In order to cut the transmission in time, besides virus-blocking strategies and vaccination approach, screening measures in combination with the satisfaction of personal needs would help identify confirmed cases earlier. Publicizing the model citizen of being responsible could show needs' satisfaction can live with the virus elimination. At the emergency response stage, it is also crucial to secure fewer loopholes in the health system and strengthen the self-protection barrier by all means. CONCLUSION: China's experience offers a reference for the balance between the resurgence of clustered cases and sustained recovery. As long as the global pandemic continues, its impact on personal activities will not stop, and vice versa. The chain of vulnerabilities integrating psychological needs into the COVID-19 risk management can provide clear clues for cutting further transmission in an efficient and more socially acceptable way.

Public Opinions and Concerns Regarding the Canadian Prime Minister's Daily COVID-19 Briefing: Longitudinal Study of YouTube Comments Using Machine Learning Techniques.

BACKGROUND: During the COVID-19 pandemic in Canada, Prime Minister Justin Trudeau provided updates on the novel coronavirus and the government's responses to the pandemic in his daily briefings from March 13 to May 22, 2020, delivered on the official Canadian Broadcasting Corporation (CBC) YouTube channel. OBJECTIVE: The aim of this study was to examine comments on Canadian Prime Minister Trudeau's COVID-19 daily briefings by YouTube users and track these comments to extract the changing dynamics of the opinions and concerns of the public over time. METHODS: We used machine learning techniques to longitudinally analyze a total of 46,732 English YouTube comments that were retrieved from 57 videos of Prime Minister Trudeau's COVID-19 daily briefings from March 13 to May 22, 2020. A natural language processing model, latent Dirichlet allocation, was used to choose salient topics among the sampled comments for each of the 57 videos. Thematic analysis was used to classify and summarize these salient topics into different prominent themes. RESULTS: We found 11 prominent themes, including strict border measures, public responses to Prime Minister Trudeau's policies, essential work and frontline workers, individuals' financial challenges, rental and mortgage subsidies, quarantine, government financial aid for enterprises and individuals, personal protective equipment, Canada and China's relationship, vaccines, and reopening. CONCLUSIONS: This study is the first to longitudinally investigate public discourse and concerns related to Prime Minister Trudeau's daily COVID-19 briefings in Canada. This study contributes to establishing a real-time feedback loop between the public and public health officials on social media. Hearing and reacting to real concerns from the public can enhance trust between the government and the public to prepare for future health emergencies.

Virtual Reality or Augmented Reality as a Tool for Studying Bystander Behaviors in Interpersonal Violence: Scoping Review.

BACKGROUND: To provide participants with a more real and immersive intervening experience, virtual reality (VR) and/or augmented reality (AR) technologies have been integrated into some bystander intervention training programs and studies measuring bystander behaviors. OBJECTIVE: We focused on whether VR or AR can be used as a tool to enhance training bystanders. We reviewed the evidence from empirical studies that used VR and/or AR as a tool for examining bystander behaviors in the domain of interpersonal violence research. METHODS: Two librarians searched for articles in databases, including APA PsycInfo (Ovid), Criminal Justice Abstracts (EBSCO), Medline (Ovid), Applied Social Sciences Index & Abstracts (ProQuest), Sociological Abstracts (ProQuest), and Scopus till April 15, 2020. Studies focusing on bystander behaviors in conflict situations were included. All study types (except reviews) written in English in any discipline were included. RESULTS: The search resulted in 12,972 articles from six databases, and the articles were imported into Covidence. Eleven studies met the inclusion and exclusion criteria. All 11 articles examined the use of VR as a tool for studying bystander behaviors. Most of the studies were conducted in US young adults. The types of interpersonal violence were school bullying, dating violence, sexual violence/assault, and soccer-associated violence. VR technology was used as an observational measure and bystander intervention program. We evaluated the different uses of VR for bystander behaviors and noted a lack of empirical evidence for AR as a tool. We also discuss the empirical evidence regarding the design, effectiveness, and limitations of implementing VR as a tool in the reviewed studies. CONCLUSIONS: The reviewed results have implications and recommendations for future research in designing and implementing VR/AR technology in the area of interpersonal violence. Future studies in this area may further contribute to the use of VR as an observational measure and explore the potential use of AR to study bystander behaviors.

Mutations in the Methyltransferase Motifs of L Protein Attenuate Newcastle Disease Virus by Regulating Viral Translation and Cell-to-Cell Spread.

The large (L) polymerase proteins of most nonsegmented, negative-stranded (NNS) RNA viruses have conserved methyltransferase motifs, (G)-G-G-D and K-D-K-E, which are important for the stabilization and translation of mRNA. However, the function of the (G)-G-G-D and K-D-K-E motifs in the NNS RNA virus Newcastle disease virus (NDV) remains unclear. We observed G-G-D and K-D-K-E motifs in all NDV genotypes. By using the infection cloning system of NDV rSG10 strain, recombinant NDVs with a single amino acid mutated to alanine in one motif (G-G-D or K-D-K-E) were rescued. The intracerebral pathogenicity index and mean death time assay results revealed that the G-G-D motif and K-D-K-E motif attenuate the virulence of NDV to various degrees. The replication, transcription, and translation levels of the K-D-K-E motif-mutant strains were significantly higher than those of wild-type virus owing to their altered regulation of the affinity between nucleocapsid protein and eukaryotic translation initiation factor 4E. When the infection dose was changed from a multiplicity of infection (MOI) of 10 to an MOI of 0.01, the cell-to-cell spread abilities of G-G-D- and K-D-K-E-mutant strains were reduced, according to plaque assay and dynamic indirect immunofluorescence assay results. Finally, we found that NDV strains with G-G-D or K-D-K-E motif mutations had less pathogenicity in 3-week-old specific-pathogen-free chickens than wild-type NDV. Therefore, these methyltransferase motifs can affect virulence by regulating the translation and cell-to-cell spread abilities of NDV. This work provides a feasible approach for generating vaccine candidates for viruses with methyltransferase motifs. IMPORTANCE Newcastle disease virus (NDV) is an important pathogen that is widespread globally. Research on its pathogenic mechanism is an important means of improving prevention and control efforts. Our study found that a deficiency in its methyltransferase motifs (G-G-D and K-D-K-E motifs) can attenuate NDV and revealed the molecular mechanism by which these motifs affect pathogenicity, which provides a new direction for the development of NDV vaccines. In addition to the (G)-G-G-D and K-D-K-E motifs of many nonsegmented, negative-stranded RNA viruses, similar motifs have been found in dengue virus, Zika virus, Japanese encephalitis virus (JEV), and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This suggests that such motifs may be present in more viruses. Our finding also provides a molecular basis for the discovery and functional study of (G)-G-G-D and K-D-K-E motifs of other viruses.

Exploring the Changes of Suicide Probability During COVID-19 Among Chinese Weibo Users.

Background: Coronavirus disease 2019 (COVID-19) threatens people's physical and mental health, globally, and it may even trigger suicide ideation and suicidal behavior. Aims: We aimed to examine the impact of COVID-19 on suicide risk by sampling Chinese Weibo users and analyzing their social media messages. Method: We predicted the probability of suicide (including hopelessness, suicidal ideation, negative self-evaluation, and hostility) of Weibo users in order to assess the changes in suicide probability at different times. Repeated-measures ANOVA was performed to examine the differences in suicide probability in different regions during different periods. Results: There was no significant difference in suicide probability between profoundly infected areas (PIAs) and less infected areas (LIAs) before the outbreak of COVID-19. LIAs had an increase in hopelessness during the COVID-19 growth period, while hopelessness and hostility in PIA increased during the COVID-19 decline period, indicating potential suicide probability. Limitations: Results should be interpreted with caution, and cross-cultural research may be considered in the future. Conclusion: COVID-19 has a dynamic impact on suicide probability. Using data from online social networks may help to understand the impact pattern of COVID-19 on people's suicide probability.

The furin-S2' site in avian coronavirus plays a key role in central nervous system damage progression.

The furin cleavage site plays an important role in virus pathogenicity. The spike protein of SARS-CoV-2 harbors a furin cleavage site insertion in contrast to SARS-CoV, which may be related to its stronger communicability. An avian coronavirus with an extra furin cleavage site upstream of the fusion peptide (S2' site) infected monocyte cells and neuron cells leading to viremia or encephalitis, respectively. Immunohistochemistry and real-time quantitative polymerase chain reaction were used to follow disease progression and demonstrated differences between the parent avian coronavirus and mutated avian coronavirus with a furin-S2' site. Magnetic resonance imaging and biological dye to evaluate the blood-brain barrier permeability showed that avian coronavirus with a furin-S2' site had increased permeability compared with parent avian coronavirus. Immunohistochemistry of brains after intracerebral injection of avian coronavirus and immunofluorescence staining of primary neuron cells demonstrated the furin-S2' site expanded the cell tropism of the mutant avian coronavirus to neuron cells. TNF-α, which has a key role in blood-brain barrier permeability, was highly induced by avian coronavirus with a furin-S2' site compared with the parent avian coronavirus. We demonstrated the process involved in mutant avian coronavirus-induced disease and that the addition of a furin-S2' site changed the virus cell tropism.IMPORTANCECoronaviruses have broken out three times in two decades. Spike (S) protein plays a key role in the process of infection. To clarify importance of furin cleavage site in spike protein for coronavirus, we investigated the pathogenesis of neurotropic avian coronavirus whose spike protein contains an extra furin cleavage site (furin-S2' site). By combining real-time quantitative polymerase chain reaction and immunohistochemistry we demonstrated that infectious bronchitis virus (IBV) infects brain instead of trachea when its S protein contains furin-S2' site. Moreover, the virus was shown to increase the permeability of blood-brain barrier, infect neuron cells and induce high expression of TNF-α. Based on these results we further show that furin cleavage site in S protein plays an important role in coronavirus pathogenicity and cell tropism. Our study extends previous publications on function of S protein of coronavirus, increasing the understanding of researchers to coronavirus.

Twitter Discussions and Emotions About the COVID-19 Pandemic: Machine Learning Approach.

BACKGROUND: It is important to measure the public response to the COVID-19 pandemic. Twitter is an important data source for infodemiology studies involving public response monitoring. OBJECTIVE: The objective of this study is to examine COVID-19-related discussions, concerns, and sentiments using tweets posted by Twitter users. METHODS: We analyzed 4 million Twitter messages related to the COVID-19 pandemic using a list of 20 hashtags (eg, "coronavirus," "COVID-19," "quarantine") from March 7 to April 21, 2020. We used a machine learning approach, Latent Dirichlet Allocation (LDA), to identify popular unigrams and bigrams, salient topics and themes, and sentiments in the collected tweets. RESULTS: Popular unigrams included "virus," "lockdown," and "quarantine." Popular bigrams included "COVID-19," "stay home," "corona virus," "social distancing," and "new cases." We identified 13 discussion topics and categorized them into 5 different themes: (1) public health measures to slow the spread of COVID-19, (2) social stigma associated with COVID-19, (3) COVID-19 news, cases, and deaths, (4) COVID-19 in the United States, and (5) COVID-19 in the rest of the world. Across all identified topics, the dominant sentiments for the spread of COVID-19 were anticipation that measures can be taken, followed by mixed feelings of trust, anger, and fear related to different topics. The public tweets revealed a significant feeling of fear when people discussed new COVID-19 cases and deaths compared to other topics. CONCLUSIONS: This study showed that Twitter data and machine learning approaches can be leveraged for an infodemiology study, enabling research into evolving public discussions and sentiments during the COVID-19 pandemic. As the situation rapidly evolves, several topics are consistently dominant on Twitter, such as confirmed cases and death rates, preventive measures, health authorities and government policies, COVID-19 stigma, and negative psychological reactions (eg, fear). Real-time monitoring and assessment of Twitter discussions and concerns could provide useful data for public health emergency responses and planning. Pandemic-related fear, stigma, and mental health concerns are already evident and may continue to influence public trust when a second wave of COVID-19 occurs or there is a new surge of the current pandemic.

Public emotion responses during COVID-19 in China on social media: An observational study

Abstract COVID-19 (Corona Virus Disease 2019) has attacked many countries around world and caused profound impacts on public life. The outbreak of pandemic and other relevant factors are considered to cause emotion responses of residents. And the emotion responses of individuals are crucial for the execution of the prevention and control measures. By analyzing the linguistic features of posts on social media, this study aims to explore the change of public emotion responses during COVID-19 in China. We sampled 22,423 Weibo users and collected their Weibo posts by provincial area each day from January 1st, 2020 to April 18th, 2020. Next, we extracted linguistic features from posts according to the emotion-related dictionary. Based on important news and information released by the national and international organizations of public health, we divided the period from January 1st, 2020 to April 18th, 2020 into four stages (the initial period, the outbreak period, the stable period, and the prevention and control period). Then we gathered linguistic features by stage. After that, ANOVA was performed to examine the differences among these four stages. The results showed that the frequencies of 11 word categories showed significant differences among four stages, including fear, disappointment, guilt, missing, anger, panic, blessing, faith, love, praise, and surprise. The uses of several negative emotion words, such as fear, disappointment, guilt, and anger, increased saliently in the outbreak period compared with the initial period. Besides, panic words decreased significantly in the prevention and control period compared with the outbreak period. However, missing words were used more in the prevention and control period than other three periods. Moreover, people expressed more faith words and less love words in the outbreak period than the initial periods. Besides, people used more blessing words in the outbreak period compared with the stable period and prevention and control period. And praise words were used more in the outbreak period and the stable period compared with the initial period. The frequency of surprise words was significantly low only in the initial period. This study contributed to the understanding of public emotion responses during COVID-19, and had implications for the evidence-based execution of prevention and control measures.

The Hidden Pandemic of Family Violence During COVID-19: Unsupervised Learning of Tweets.

BACKGROUND: Family violence (including intimate partner violence/domestic violence, child abuse, and elder abuse) is a hidden pandemic happening alongside COVID-19. The rates of family violence are rising fast, and women and children are disproportionately affected and vulnerable during this time. OBJECTIVE: This study aims to provide a large-scale analysis of public discourse on family violence and the COVID-19 pandemic on Twitter. METHODS: We analyzed over 1 million tweets related to family violence and COVID-19 from April 12 to July 16, 2020. We used the machine learning approach Latent Dirichlet Allocation and identified salient themes, topics, and representative tweets. RESULTS: We extracted 9 themes from 1,015,874 tweets on family violence and the COVID-19 pandemic: (1) increased vulnerability: COVID-19 and family violence (eg, rising rates, increases in hotline calls, homicide); (2) types of family violence (eg, child abuse, domestic violence, sexual abuse); (3) forms of family violence (eg, physical aggression, coercive control); (4) risk factors linked to family violence (eg, alcohol abuse, financial constraints, guns, quarantine); (5) victims of family violence (eg, the LGBTQ [lesbian, gay, bisexual, transgender, and queer or questioning] community, women, women of color, children); (6) social services for family violence (eg, hotlines, social workers, confidential services, shelters, funding); (7) law enforcement response (eg, 911 calls, police arrest, protective orders, abuse reports); (8) social movements and awareness (eg, support victims, raise awareness); and (9) domestic violence-related news (eg, Tara Reade, Melissa DeRosa). CONCLUSIONS: This study overcomes limitations in the existing scholarship where data on the consequences of COVID-19 on family violence are lacking. We contribute to understanding family violence during the pandemic by providing surveillance via tweets. This is essential for identifying potentially useful policy programs that can offer targeted support for victims and survivors as we prepare for future outbreaks.

Public discourse and sentiment during the COVID 19 pandemic: Using Latent Dirichlet Allocation for topic modeling on Twitter.

The study aims to understand Twitter users' discourse and psychological reactions to COVID-19. We use machine learning techniques to analyze about 1.9 million Tweets (written in English) related to coronavirus collected from January 23 to March 7, 2020. A total of salient 11 topics are identified and then categorized into ten themes, including "updates about confirmed cases," "COVID-19 related death," "cases outside China (worldwide)," "COVID-19 outbreak in South Korea," "early signs of the outbreak in New York," "Diamond Princess cruise," "economic impact," "Preventive measures," "authorities," and "supply chain." Results do not reveal treatments and symptoms related messages as prevalent topics on Twitter. Sentiment analysis shows that fear for the unknown nature of the coronavirus is dominant in all topics. Implications and limitations of the study are also discussed.

Modern Senicide in the Face of a Pandemic: An Examination of Public Discourse and Sentiment About Older Adults and COVID-19 Using Machine Learning.

OBJECTIVES: This study examined public discourse and sentiment regarding older adults and COVID-19 on social media and assessed the extent of ageism in public discourse. METHODS: Twitter data (N = 82,893) related to both older adults and COVID-19 and dated from January 23 to May 20, 2020, were analyzed. We used a combination of data science methods (including supervised machine learning, topic modeling, and sentiment analysis), qualitative thematic analysis, and conventional statistics. RESULTS: The most common category in the coded tweets was "personal opinions" (66.2%), followed by "informative" (24.7%), "jokes/ridicule" (4.8%), and "personal experiences" (4.3%). The daily average of ageist content was 18%, with the highest of 52.8% on March 11, 2020. Specifically, more than 1 in 10 (11.5%) tweets implied that the life of older adults is less valuable or downplayed the pandemic because it mostly harms older adults. A small proportion (4.6%) explicitly supported the idea of just isolating older adults. Almost three-quarters (72.9%) within "jokes/ridicule" targeted older adults, half of which were "death jokes." Also, 14 themes were extracted, such as perceptions of lockdown and risk. A bivariate Granger causality test suggested that informative tweets regarding at-risk populations increased the prevalence of tweets that downplayed the pandemic. DISCUSSION: Ageist content in the context of COVID-19 was prevalent on Twitter. Information about COVID-19 on Twitter influenced public perceptions of risk and acceptable ways of controlling the pandemic. Public education on the risk of severe illness is needed to correct misperceptions.

Examining the Impact of COVID-19 Lockdown in Wuhan and Lombardy: A Psycholinguistic Analysis on Weibo and Twitter.

Many countries are taking strict quarantine policies to prevent the rapid spread of COVID-19 (Corona Virus Disease 2019) around the world, such as city lockdown. Cities in China and Italy were locked down in the early stage of the pandemic. The present study aims to examine and compare the impact of COVID-19 lockdown on individuals' psychological states in China and Italy. We achieved the aim by (1) sampling Weibo users (geo-location = Wuhan, China) and Twitter users (geo-location = Lombardy, Italy); (2) fetching all the users' published posts two weeks before and after the lockdown in each region (e.g., the lockdown date of Wuhan was 23 January 2020); (3) extracting the psycholinguistic features of these posts using the Simplified Chinese and Italian version of Language Inquiry and Word Count (LIWC) dictionary; and (4) conducting Wilcoxon tests to examine the changes in the psycholinguistic characteristics of the posts before and after the lockdown in Wuhan and Lombardy, respectively. Results showed that individuals focused more on "home", and expressed a higher level of cognitive process after a lockdown in both Wuhan and Lombardy. Meanwhile, the level of stress decreased, and the attention to leisure increased in Lombardy after the lockdown. The attention to group, religion, and emotions became more prevalent in Wuhan after the lockdown. Findings provide decision-makers timely evidence on public reactions and the impacts on psychological states in the COVID-19 context, and have implications for evidence-based mental health interventions in two countries.

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.