Query: social media efforts in controlling coronavirus infection

title: Will firm's marketing efforts on owned social media payoff? A quasi experimental analysis of tourism products
abstract: A growing number of travel agencies use social media to promote their services and reach target customers despite some doubt regarding the effectiveness of these tools. Nevertheless, most prior studies adopt a customer centric perspective to explore the usefulness of earned social media run by third parties. Few have examined a firm's active role in online social interactions. This paper distinguishes owned media from earned media by site ownerships and communication paths, and examines a firm's marketing efforts on its owned Facebook brand page. Working with a leading travel agency, we collected a matched sample of products with Facebook marketing (treatment group) and those without Facebook marketing (control group) Using a quasi experimental design and difference in difference estimation, we evaluate the effect of a firm's efforts on Facebook marketing campaigns after controlling time fixed selection bias and common time series heterogeneity. The results show that Facebook campaign activities have a positive impact on sales of tourism products. Furthermore, based on the cognitive fit theory, sales are found to increase when a travel agency promotes tourism products that are highly structured, medium priced, or medium length, or that require more tourist involvement. Such effects are further examined across different quantiles of sales and in different time spans to see when product moderations are more prominent. The empirical findings facilitate decision making of e commerce managers in the tourism industry not only by justifying the effectiveness as well as budget allocation of owned social media marketing, but also by providing a rudimentary guidance on the product selection in Facebook marketing campaigns. Other than customers' reviews, examine firms' marketing efforts in owned social mediaSupported by quasi experimental data and DID estimation to go beyond correlationsFacilitate the decision making of e commerce managers in tourismJustify the effectiveness of Facebook marketing and the budget allocation accordinglyProvide a rudimentary guidance on marketing campaigns at the product level

title: Substantial undocumented infection facilitates the rapid dissemination of novel coronavirus (SARS CoV 2)
abstract: Undetected cases The virus causing coronavirus disease 2019 (COVID 19) has now become pandemic. How has it managed to spread from China to all around the world within 3 to 4 months? Li et al. used multiple sources to infer the proportion of early infections that went undetected and their contribution to virus spread. The researchers combined data from Tencent, one of the world's largest social media and technology companies, with a networked dynamic metapopulation model and Bayesian inference to analyze early spread within China. They estimate that ~86% of cases were undocumented before travel restrictions were put in place. Before travel restriction and personal isolation were implemented, the transmission rate of undocumented infections was a little more than half that of the known cases. However, because of their greater numbers, undocumented infections were the source for ~80% of the documented cases. Immediately after travel restrictions were imposed, ~65% of cases were documented. These findings help to explain the lightning fast spread of this virus around the world. Science, this issue p. 489 Prior to travel restrictions, most SARS CoV 2 infections went undocumented and substantially contributed to global virus spread. Estimation of the prevalence and contagiousness of undocumented novel coronavirus [severe acute respiratory syndrome coronavirus 2 (SARS CoV 2) infections is critical for understanding the overall prevalence and pandemic potential of this disease. Here, we use observations of reported infection within China, in conjunction with mobility data, a networked dynamic metapopulation model, and Bayesian inference, to infer critical epidemiological characteristics associated with SARS CoV 2, including the fraction of undocumented infections and their contagiousness. We estimate that 86% of all infections were undocumented [95% credible interval (CI) 82 90% before the 23 January 2020 travel restrictions. The transmission rate of undocumented infections per person was 55% the transmission rate of documented infections (95% CI: 46 62% yet, because of their greater numbers, undocumented infections were the source of 79% of the documented cases. These findings explain the rapid geographic spread of SARS CoV 2 and indicate that containment of this virus will be particularly challenging.

title: Mining Coronavirus (COVID 19) Posts in Social Media
abstract: World Health Organization (WHO) characterized the novel coronavirus (COVID 19) as a global pandemic on March 11th, 2020. Before this and in late January, more specifically on January 27th, while the majority of the infection cases were still reported in China and a few cruise ships, we began crawling social media user postings using the Twitter search API. Our goal was to leverage machine learning and linguistic tools to better understand the impact of the outbreak in China. Unlike our initial expectation to monitor a local outbreak, COVID 19 rapidly spread across the globe. In this short article we report the preliminary results of our study on automatically detecting the positive reports of COVID 19 from social media user postings using state of the art machine learning models.

title: Using Social Media To Increase HIV Testing Among Men Who Have Sex with Men Beijing, China, 2013 2017
abstract: The prevalence of human immunodeficiency virus (HIV) infection in China is low overall (0.06% (1) however, it is substantially higher (8.0% among men who have sex with men (MSM) (2) and the stigmatization of same sex behaviors in China presents challenges for HIV prevention and treatment efforts. In 2015, Blued, a Beijing based media company that operates an online dating application popular among Chinese MSM, launched an ongoing HIV testing campaign that combined its push notification+ platform and geolocation capabilities to encourage HIV testing among MSM in Beijing. To assess trends in use of HIV testing services, Blued and CDC's China HIV program examined testing at six Blued operated Beijing HIV testing centers from 2 years before the campaign launch in 2015 through December 31, 2017. A sharp increase in HIV testing followed the launch of Blued's online campaign, indicating that leveraging social media platforms and their geolocation based text messaging functionality might be useful in increasing HIV testing among MSM, particularly those aged =35 years.

title: Polarization and Public Health: Partisan Differences in Social Distancing During the Coronavirus Pandemic
abstract: We study partisan differences in Americans' response to the COVID 19 pandemic. Political leaders and media outlets on the right and left have sent divergent messages about the severity of the crisis, which could impact the extent to which Republicans and Democrats engage in social distancing and other efforts to reduce disease transmission. We develop a simple model of a pandemic response with heterogeneous agents that clarifies the causes and consequences of heterogeneous responses. We use location data from a large sample of smartphones to show that areas with more Republicans engaged in less social distancing, controlling for other factors including public policies, population density, and local COVID cases and deaths. We then present new survey evidence of significant gaps at the individual level between Republicans and Democrats in self reported social distancing, beliefs about personal COVID risk, and beliefs about the future severity of the pandemic.

title: Towards Algorithmic Experience: Initial Efforts for Social Media Contexts
abstract: Algorithms influence most of our daily activities, decisions, and they guide our behaviors. It has been argued that algorithms even have a direct impact on democratic societies. Human Computer Interaction research needs to develop analytical tools for describing the interaction with, and experience of algorithms. Based on user participatory workshops focused on scrutinizing Facebook's newsfeed, an algorithm influenced social media, we propose the concept of Algorithmic Experience (AX) as an analytic framing for making the interaction with and experience of algorithms explicit. Connecting it to design, we articulate five functional categories of AX that are particularly important to cater for in social media: profiling transparency and management, algorithmic awareness and control, and selective algorithmic memory.

title: Mental health problems and social media exposure during COVID 19 outbreak
abstract: Huge citizens expose to social media during a novel coronavirus disease (COVID 19) outbroke in Wuhan, China. We assess the prevalence of mental health problems and examine their association with social media exposure. A cross sectional study among Chinese citizens aged>=18 years old was conducted during Jan 31 to Feb 2, 2020. Online survey was used to do rapid assessment. Total of 4872 participants from 31 provinces and autonomous regions were involved in the current study. Besides demographics and social media exposure (SME) depression was assessed by The Chinese version of WHO Five Well Being Index (WHO 5) and anxiety was assessed by Chinese version of generalized anxiety disorder scale (GAD 7) multivariable logistic regressions were used to identify associations between social media exposure with mental health problems after controlling for covariates. The prevalence of depression, anxiety and combination of depression and anxiety (CDA) was 48.3% (95%CI: 46.9% 49.7% 22.6% (95%CI: 21.4% 23.8% and 19.4% (95%CI: 18.3% 20.6% during COVID 19 outbroke in Wuhan, China. More than 80% (95%CI:80.9% 83.1% of participants reported frequently exposed to social media. After controlling for covariates, frequently SME was positively associated with high odds of anxiety (OR 1.72, 95%CI: 1.31 2.26) and CDA (OR 1.91, 95%CI: 1.52 2.41) compared with less SME. Our findings show there are high prevalence of mental health problems, which positively associated with frequently SME during the COVID 19 outbreak. These findings implicated the government need pay more attention to mental health problems, especially depression and anxiety among general population and combating with "infodemic" while combating during public health emergency.

title: Understanding coronavirus disease (COVID 19) risk perceptions among the public to enhance risk communication efforts: a practical approach for outbreaks, Finland, February 2020
abstract: Understanding risk perceptions of the public is critical for risk communication. In February 2020, the Finnish Institute for Health and Welfare started collecting weekly qualitative data on coronavirus disease (COVID 19) risk perception that informs risk communication efforts. The process is based on thematic analysis of emails and social media messages from the public and identifies factors linked to appraisal of risk magnitude, which are developed into risk communication recommendations together with health and communication experts.

title: Effects of Timely Control Intervention on the Spread of Middle East Respiratory Syndrome Coronavirus Infection
abstract: The 2015 Middle East Respiratory Syndrome Coronavirus (MERS CoV) outbreak in Korea caused major economic and social problems. The control intervention was conducted during the MERS CoV outbreak in Korea immediately after the confirmation of the index case. This study investigates whether the early risk communication with the general public and mass media is an effective preventive strategy.  The SEIR (Susceptible, Exposed, Infectious, Recovered) model with estimated parameters for the time series data of the daily MERS CoV incidence in Korea was considered from May to December 2015. For 10,000 stochastic simulations, the SEIR model was computed using the Gillespie algorithm. Depending on the time of control intervention on the 20th, 40th, and 60th days after the identification of the index case, the box plots of MERS CoV incidences in Korea were computed, and the results were analyzed via ANOVA.  The box plots showed that there was a significant difference between the non intervention and intervention groups (the 20th day, 40th day, and 60th day groups) and seemed to show no significant difference based on the time of intervention. However, the ANOVA revealed that early intervention was a good strategy to control the disease.  Appropriate risk communication can secure the confidence of the general public in the public health authorities.

title: Controlling the Spread of Corruption through Social Media A Mathematical Modelling Approach
abstract: In this paper, corruption is treated as an infection that spreads through social interactions. We developed and analyzed a new mathematical model of corruption in a population with constant recruitment rate, incorporating standard incidence rate, effort rate against corruption andeffect of the embarrassment faced by corrupt individuals due tosocial media freedom, which makes some corrupt individuals temporarily quit corruption. The effective reproduction number and its values are computed using four different control strategies. Results showed that if at least 40% of the corrupt individuals are embarrassed on social media, corruption can be significantly controlled. This may not be a short time effect but will take years to be achieved. A feasible solution to the control of corruption is suggested, i.e a 50% coverage rate of each ofeffort rate against corruption, social media freedom, and embarrassing corrupt individuals on social media. These effects are sizable making them effective tools against corruption.