scholarly journals Exploring the Expression Differences Between Professionals and Laypeople Toward the COVID-19 Vaccine: Text Mining Approach (Preprint)

2021 ◽  
Author(s):  
Chen Luo ◽  
Kaiyuan Ji ◽  
Yulong Tang ◽  
Zhiyuan Du
Keyword(s):  
Text Mining ◽  
Topic Modeling ◽  
Vaccine Development ◽  
Vaccination Campaign ◽  
Vaccine Effectiveness ◽  
Social Implications ◽  
Significant Difference ◽  
Question And Answer ◽  
Question Category ◽  
Expression Characteristics

BACKGROUND COVID-19 is still rampant all over the world. Until now, the COVID-19 vaccine is the most promising measure to subdue contagion and achieve herd immunity. However, public vaccination intention is suboptimal. A clear division lies between medical professionals and laypeople. While most professionals eagerly promote the vaccination campaign, some laypeople exude suspicion, hesitancy, and even opposition toward COVID-19 vaccines. OBJECTIVE This study aims to employ a text mining approach to examine expression differences and thematic disparities between the professionals and laypeople within the COVID-19 vaccine context. METHODS We collected 3196 answers under 65 filtered questions concerning the COVID-19 vaccine from the China-based question and answer forum Zhihu. The questions were classified into 5 categories depending on their contents and description: adverse reactions, vaccination, vaccine effectiveness, social implications of vaccine, and vaccine development. Respondents were also manually coded into two groups: professional and laypeople. Automated text analysis was performed to calculate fundamental expression characteristics of the 2 groups, including answer length, attitude distribution, and high-frequency words. Furthermore, structural topic modeling (STM), as a cutting-edge branch in the topic modeling family, was used to extract topics under each question category, and thematic disparities were evaluated between the 2 groups. RESULTS Laypeople are more prevailing in the COVID-19 vaccine–related discussion. Regarding differences in expression characteristics, the professionals posted longer answers and showed a conservative stance toward vaccine effectiveness than did laypeople. Laypeople mentioned countries more frequently, while professionals were inclined to raise medical jargon. STM discloses prominent topics under each question category. Statistical analysis revealed that laypeople preferred the “safety of Chinese-made vaccine” topic and other vaccine-related issues in other countries. However, the professionals paid more attention to medical principles and professional standards underlying the COVID-19 vaccine. With respect to topics associated with the social implications of vaccines, the 2 groups showed no significant difference. CONCLUSIONS Our findings indicate that laypeople and professionals share some common grounds but also hold divergent focuses toward the COVID-19 vaccine issue. These incongruities can be summarized as “qualitatively different” in perspective rather than “quantitatively different” in scientific knowledge. Among those questions closely associated with medical expertise, the “qualitatively different” characteristic is quite conspicuous. This study boosts the current understanding of how the public perceives the COVID-19 vaccine, in a more nuanced way. Web-based question and answer forums are a bonanza for examining perception discrepancies among various identities. STM further exhibits unique strengths over the traditional topic modeling method in statistically testing the topic preference of diverse groups. Public health practitioners should be keenly aware of the cognitive differences between professionals and laypeople, and pay special attention to the topics with significant inconsistency across groups to build consensus and promote vaccination effectively.

Factors Driving the Popularity and Virality of COVID-19 Vaccine Discourse on Twitter: Text Mining and Data Visualization Study (Preprint)

2021 ◽  
Author(s):  
Jueman Zhang ◽  
Yi Wang ◽  
Molu Shi ◽  
Xiuli Wang
Keyword(s):  
Network Analysis ◽  
Text Mining ◽  
Vaccine Efficacy ◽  
Topic Modeling ◽  
English Language ◽  
Vaccine Development ◽  
Linguistic Features ◽  
The Public ◽  
Social Media Platforms ◽  
Positive Valence

BACKGROUND COVID-19 vaccination is considered a critical prevention measure to help end the pandemic. Social media platforms such as Twitter have played an important role in the public discussion about COVID-19 vaccines. OBJECTIVE The aim of this study was to investigate message-level drivers of the popularity and virality of tweets about COVID-19 vaccines using machine-based text-mining techniques. We further aimed to examine the topic communities of the most liked and most retweeted tweets using network analysis and visualization. METHODS We collected US-based English-language public tweets about COVID-19 vaccines from January 1, 2020, to April 30, 2021 (N=501,531). Topic modeling and sentiment analysis were used to identify latent topics and valence, which together with autoextracted information about media presence, linguistic features, and account verification were used in regression models to predict likes and retweets. Among the 2500 most liked tweets and 2500 most retweeted tweets, network analysis and visualization were used to detect topic communities and present the relationship between the topics and the tweets. RESULTS Topic modeling yielded 12 topics. The regression analyses showed that 8 topics positively predicted likes and 7 topics positively predicted retweets, among which the topic of vaccine development and people’s views and that of vaccine efficacy and rollout had relatively larger effects. Network analysis and visualization revealed that the 2500 most liked and most retweeted retweets clustered around the topics of vaccine access, vaccine efficacy and rollout, vaccine development and people’s views, and vaccination status. The overall valence of the tweets was positive. Positive valence increased likes, but valence did not affect retweets. Media (photo, video, gif) presence and account verification increased likes and retweets. Linguistic features had mixed effects on likes and retweets. CONCLUSIONS This study suggests the public interest in and demand for information about vaccine development and people’s views, and about vaccine efficacy and rollout. These topics, along with the use of media and verified accounts, have enhanced the popularity and virality of tweets. These topics could be addressed in vaccine campaigns to help the diffusion of content on Twitter.

Investigating Diseases and Chemicals in COVID-19 Literature with Text Mining (Preprint)

2020 ◽  
Author(s):  
Amir Karami ◽  
Brandon Bookstaver ◽  
Melissa Nolan
Keyword(s):  
Text Mining ◽  
Literature Review ◽  
Topic Modeling ◽  
Large Scale ◽  
Clinical Manifestations ◽  
International Health ◽  
Research Papers ◽  
Strategic Plans ◽  
Funding Agencies ◽  
The Relationship

BACKGROUND The COVID-19 pandemic has impacted nearly all aspects of life and has posed significant threats to international health and the economy. Given the rapidly unfolding nature of the current pandemic, there is an urgent need to streamline literature synthesis of the growing scientific research to elucidate targeted solutions. While traditional systematic literature review studies provide valuable insights, these studies have restrictions, including analyzing a limited number of papers, having various biases, being time-consuming and labor-intensive, focusing on a few topics, incapable of trend analysis, and lack of data-driven tools. OBJECTIVE This study fills the mentioned restrictions in the literature and practice by analyzing two biomedical concepts, clinical manifestations of disease and therapeutic chemical compounds, with text mining methods in a corpus containing COVID-19 research papers and find associations between the two biomedical concepts. METHODS This research has collected papers representing COVID-19 pre-prints and peer-reviewed research published in 2020. We used frequency analysis to find highly frequent manifestations and therapeutic chemicals, representing the importance of the two biomedical concepts. This study also applied topic modeling to find the relationship between the two biomedical concepts. RESULTS We analyzed 9,298 research papers published through May 5, 2020 and found 3,645 disease-related and 2,434 chemical-related articles. The most frequent clinical manifestations of disease terminology included COVID-19, SARS, cancer, pneumonia, fever, and cough. The most frequent chemical-related terminology included Lopinavir, Ritonavir, Oxygen, Chloroquine, Remdesivir, and water. Topic modeling provided 25 categories showing relationships between our two overarching categories. These categories represent statistically significant associations between multiple aspects of each category, some connections of which were novel and not previously identified by the scientific community. CONCLUSIONS Appreciation of this context is vital due to the lack of a systematic large-scale literature review survey and the importance of fast literature review during the current COVID-19 pandemic for developing treatments. This study is beneficial to researchers for obtaining a macro-level picture of literature, to educators for knowing the scope of literature, to journals for exploring most discussed disease symptoms and pharmaceutical targets, and to policymakers and funding agencies for creating scientific strategic plans regarding COVID-19.

Residents’ perception towards tourism impacts in Kashmir

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Asif Hamid Charag ◽  
Asif Iqbal Fazili ◽  
Irfan Bashir
Keyword(s):  
Planning Process ◽  
Economic Impacts ◽  
Tourism Development ◽  
Policy Framework ◽  
Social Implications ◽  
Cultural Economic ◽  
Tourism Impacts ◽  
Content Type ◽  
City Tourism ◽  
Significant Difference

Purpose The purpose of this study is to understand the residents’ perception towards environmental, social, cultural and economic impacts of tourism development in Kashmir. Design/methodology/approach The research instrument containing 27 items pertaining to six variables is adopted from the literature. A mix-method survey approach is used to solicit residents’ perceptions regarding environmental, social, cultural and economic impacts of the current level of tourism development. A total of 326 useful responses were subjected to descriptive statistics, analysis of variance (ANOVA) and post hoc analysis using SPSS (Version 22.0). Findings In general, the negative and positive impacts of tourism development are well perceived by the residents. The results indicate that the residents display positive perception regarding economic impacts, however, social and environmental impacts are negatively perceived. Furthermore, barring level of education, the study found no significant difference in the residents’ perception towards tourism impacts (environmental, social, cultural, economic, quality of life and cost of living). Research limitations/implications The paper identifies perceived impacts and issues of tourism development thereby, proposing possible mitigating measures. Also, the study identifies the need to develop a comprehensive policy framework addressing the issues related to the resident’s negative feelings towards tourism impacts. Further, the study envisages the need for engaging residents in developing a progressive and participatory planning process for future tourism activities in the area. Social implications The study offers critical social implications for city tourism development. It suggests a community-based approach should be adopted to sensitize residents about the positive benefits of tourism. Originality/value The study is a novel attempt concerning residents’ residents perceptual differences towards tourism impacts. Furthermore, this study investigated socio-cultural impacts of tourism under two separate categories for better understanding. in doing so, this study provides finer understanding of perception of residents towards tourism impacts in Indian context. The findings of the study will prove critical for different stakeholders in developing future tourism framework and policies in the region.

scholarly journals Measles Outbreak Associated With Low Vaccine Effectiveness Among Adults in Pohnpei State, Federated States of Micronesia, 2014

2016 ◽  
Vol 3 (2) ◽  
Author(s):  
Craig M. Hales ◽  
Eliaser Johnson ◽  
Louisa Helgenberger ◽  
Mark J. Papania ◽  
Maribeth Larzelere ◽  
...  
Keyword(s):  
Confidence Interval ◽  
Vaccination Campaign ◽  
Vaccine Effectiveness ◽  
Mass Vaccination ◽  
Cold Chain ◽  
Primary Case ◽  
Federated States Of Micronesia ◽  
Measles Outbreak ◽  
Mass Vaccination Campaign ◽  
Vaccination Campaigns

Abstract Background.  A measles outbreak in Pohnpei State, Federated States of Micronesia in 2014 affected many persons who had received ≥1 dose of measles-containing vaccine (MCV). A mass vaccination campaign targeted persons aged 6 months to 49 years, regardless of prior vaccination. Methods.  We evaluated vaccine effectiveness (VE) of MCV by comparing secondary attack rates among vaccinated and unvaccinated contacts after household exposure to measles. Results.  Among 318 contacts, VE for precampaign MCV was 23.1% (95% confidence interval [CI], −425 to 87.3) for 1 dose, 63.4% (95% CI, −103 to 90.6) for 2 doses, and 95.9% (95% CI, 45.0 to 100) for 3 doses. Vaccine effectiveness was 78.7% (95% CI, 10.1 to 97.7) for campaign doses received ≥5 days before rash onset in the primary case and 50.4% (95% CI, −52.1 to 87.9) for doses received 4 days before to 3 days after rash onset in the primary case. Vaccine effectiveness for most recent doses received before 2010 ranged from 51% to 57%, but it increased to 84% for second doses received in 2010 or later. Conclusions.  Low VE was a major source of measles susceptibility in this outbreak; potential reasons include historical cold chain inadequacies or waning of immunity. Vaccine effectiveness of campaign doses supports rapid implementation of vaccination campaigns in outbreak settings.

scholarly journals Measles Outbreak in Complex Emergency: Estimating Vaccine Effectiveness and Evaluation of the Vaccination Campaign in Borno State, Nigeria, 2019

2020 ◽  
Author(s):  
Anne Eudes Jean Baptiste ◽  
John Wagai ◽  
Richard Ray Luce ◽  
Balcha Girma Masresha ◽  
Don Klinkenberg ◽  
...  
Keyword(s):  
Vaccination Campaign ◽  
Screening Method ◽  
Population Level ◽  
Vaccine Effectiveness ◽  
Sensitivity Analyses ◽  
Outbreak Response ◽  
Internally Displaced ◽  
Complex Emergency ◽  
Campaign Coverage ◽  
Measles Outbreaks

Abstract Background: From January to May 2019, large measles outbreaks affected Nigeria. Borno state was the most affected, recording 15,237 suspected cases with the state capital of Maiduguri having 1,125 cases investigated and line-listed by March 2019. In Borno state, 22 of the 27 Local Government Areas (LGAs or Districts), including 37 internally displaced persons (IDPs) camps were affected. In response to the situation, an outbreak response immunization (ORI) campaign was conducted in the 13 most affected LGAs. In addition to conventional vaccination teams, special teams were deployed in security compromised areas, areas with migrants, and for nomadic and IDPs. Here we describe the outbreak and the ORI campaign. We also assess the measles-containing vaccine (MCV) coverage and vaccine effectiveness (VE) in order to quantify the population-level impactMethods: We reviewed the ORI activities, and conducted an analysis of the surveillance and the outbreak investigation reports. We assessed VE of MCV by applying the screening-method. Sensitivity analyses were also conducted to assess the effect of final classification of cases on the VE of MCV. The MCV coverage was assessed by a post-campaign coverage survey (PCCS) after completion of the ORI through a quantitative survey in the 12 LGAs that were accessible. . Results: Of the total 15,237 reported measles cases, 2,002 cases were line-listed and investigated, and 737 were confirmed for measles by week 9 of 2019. Of the investigated cases 67.3% (n = 1,348) were between 9 and 59 months of age. Among the 737 confirmed cases, only 9% (n = 64) stated being vaccinated with at least 1 dose of MCV. The overall VE for MCV was 98.4 (95%CI: 97.8 – 98.8). No significant differences were observed in the VE estimates of lab-confirmed and epi-linked cases when compared to the original estimates. The aggregated weighted vaccination coverage was 85.7% (95% CI: 79.6 – 90.1).Conclusion: The experience in Borno demonstrates that adequate VE can be obtained in conflict-affected areas. In complex emergency affected by measles outbreaks, health authorities may consider integration with other health strategies and the engagement of security personnel as part of the ORI activities.

scholarly journals IMPACTS OF AEROBIC EXERCISE ON HDL LEVEL OF ADULTS; IT’S SOCIAL IMPLICATIONS IN EDUCATIONAL INSTITUTES

2021 ◽  
Vol 9 (4) ◽  
pp. 65-68
Author(s):  
Noor Muhammad Marwat ◽  
Shah Khalid ◽  
Pir Muhammad Abdul Aziz Shah ◽  
Fayaz ul Hasnain ◽  
Rashid Naeem Khan
Keyword(s):  
High Density Lipoprotein ◽  
Aerobic Exercise ◽  
Heart Valves ◽  
Density Lipoprotein ◽  
High Density ◽  
Social Implications ◽  
Exercise Protocol ◽  
Post Intervention ◽  
The Social ◽  
Significant Difference

Purpose: The purpose of this study to find out the impacts of a 6-weeks supervised aerobic exercise protocol on High-Density Lipoprotein among adults aged between 25-35 years was evaluated. Methodology: Researchers through a non-probability sampling procedure selected thirty (30) volunteers ranging from 25-35 untrained adults from Lakki Marwat. Researchers used a six-week aerobic exercise protocol to collect relevant information from the targeted dependent variables. The CHOD PAP method was used to measure the High-Density Lipoprotein (HDL) of adults. All the data collected from pre-and post- (HDL) tests were recorded in numerical form and analyzed by using a t-test. Main Findings: The results of the study indicate that the six-week aerobic exercise protocol program had no significant difference on pre-and post-intervention quantities of HDL of Experimental Group which is (P>0.05). The implication of the Study: The aerobic exercise programs used for this particular study may help adults to improve and maintain their health status, proper social stature, and lipid profile. An increase in the HLD is ideal as this increase in the HDL helps to prevent cardiovascular diseases particularly the heart valves from stroke and cardiac arrest and academic achievements of the participants. Novelty: So far, no particular research has been conducted on the social implications of exercise effects on adults. Future researchers may work on the social habits of physically fit adults and their input to society.

scholarly journals Tracking patients healthcare experiences during the COVID-19 outbreak: Topic modeling and sentiment analysis of doctor reviews

2021 ◽  
Vol 9 (3A) ◽  
Author(s):  
Adnan M. Shah ◽  
◽  
Xiangbin Yan ◽  
Samia tariq ◽  
Syed Asad A. Shah ◽  
...  
Keyword(s):  
Quality Of Care ◽  
Sentiment Analysis ◽  
Topic Modeling ◽  
Swot Analysis ◽  
Vaccine Development ◽  
Time Slice ◽  
Healthcare Organizations ◽  
Physician Rating ◽  
Physician Rating Website

Emerging voices of patients in the form of opinions and expectations about the quality of care can improve healthcare service quality. A large volume of patients’ opinions as online doctor reviews (ODRs) are available online to access, analyze, and improve patients’ perceptions. This paper aims to explore COVID-19-related conversations, complaints, and sentiments using ODRs posted by users of the physician rating website. We analyzed 96,234 ODRs of 5,621 physicians from a prominent health rating website in the United Kingdom (Iwantgreatcare.org) in threetime slices (i.e., from February 01 to October 31, 2020). We employed machine learning approach, dynamic topic modeling, to identify prominent bigrams, salient topics and labels, sentiments embedded in reviews and topics, and patient-perceived root cause and strengths, weaknesses, opportunities, and threats (SWOT) analyses to examine SWOT for healthcare organizations. This method finds a total of 30 latent topics with 10 topics across each time slice. The current study identified new discussion topics about COVID-19 occurring from time slice 1 to time slice 3, such as news about the COVID-19 pandemic, violence against the lockdown, quarantine process and quarantine centers at different locations, and vaccine development/treatment to stop virus spread. Sentiment analysis reveals that fear for novel pathogen prevails across all topics. Based on the SWOT analysis, our findings provide a clue for doctors, hospitals, and government officials to enhance patients’ satisfaction and minimize dissatisfaction by satisfying their needs and improve the quality of care during the COVID-19 crisis.

Clinical trials of COVID 19 vaccines and vaccination campaign: ethical issues

2021 ◽  
Author(s):  
VE Goncharova
Keyword(s):  
Clinical Trials ◽  
Preventive Measures ◽  
Ethical Issues ◽  
Vaccine Development ◽  
Vaccination Campaign ◽  
Public Confidence ◽  
Basic Principles ◽  
Literary Sources ◽  
The World ◽  
Decisive Action

For many centuries, infectious diseases have posed a serious threat: epidemics and pandemics claim lives and multiply the burden on health systems and countries' economies. Humanity managed to defeat a number of infections only thanks to specific preventive measures, i.e., vaccination. In 2020, society faced the new COVID-19 virus that has swept the whole world. The situation required swift and decisive action, including in what concerned vaccine development. It has also raised a number of ethical issues. The article analyzes ethical issues related to clinical trials and vaccination against COVID-19 by studying the regulations, literary sources and bioethical incidents. The key problems identified are: human participation in clinical trials during a pandemic, availability and, simultaneously, voluntariness of vaccination, public confidence in the SARS-Cov-2 vaccines approved for clinical practice. The study showed that the basic principles of clinical trials, voluntariness and awareness, are violated. It was revealed that despite all the efforts of public organizations and WHO initiatives in the world, there is a pronounced imbalance in the availability of the developed vaccines, while the vaccination voluntariness principle is violated by application of various mechanisms to put pressure on people, and public confidence in the developed vaccines can be called insufficient. In general, the problem of vaccination against COVID-19 remains relevant and requires comprehensive discussion.

Assessment of the history and trends of “The Journal of Intellectual Capital”: a bibliometrics, altmetrics and text mining analysis

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mohammadreza Esmaeili Givi ◽  
Mohammad Karim Saberi ◽  
Mojtaba Talafidaryani ◽  
Mahdi Abdolhamid ◽  
Rahim Nikandish ◽  
...  
Keyword(s):  
Text Mining ◽  
Bibliometric Analysis ◽  
Intellectual Capital ◽  
Topic Modeling ◽  
Editorial Team ◽  
International Studies ◽  
Content Type ◽  
Number Of Publications ◽  
Relative Prevalence ◽  
Increasing Trends

PurposeThe Journal of Intellectual Capital (JIC) celebrated its 20th anniversary in 2020. Therefore, the present study aims to provide a general overview of the history and key trends in this journal during 2000–2019.Design/methodology/approachTwo types of citation and textual data during a 20-year journal period were retrieved from the Scopus database. The citation structures and contents were explored based on a combination of bibliometric analysis, altmetric analysis and text mining. The journal themes and trends of their changes were analyzed through citation bursts, mapping and topic modeling. To make a better comparison, the text mining process for the topic modeling of the IC field was performed in addition to the topic modeling of JIC.FindingsBibliometric analysis indicated that JIC has experienced a remarkable growth in terms of the number of publications and citations over the last 20 years. The results indicated that JIC plays a significant role among IC researchers. Additionally, a large number of researchers, institutes and countries have made contributions to this journal and cited its research papers. Altmetric analysis showed that JIC has been shared in different social media such as Twitter, Facebook, Wikipedia, Mendeley, Citeulike, news and blogs. Text mining abstract of JIC articles indicated that “measurement,” “financial performance” and “IC reporting” have the relative prevalence with increasing trends over the past 20 years. In addition, “research trends” and “national and international studies” had a stable trend with low thematic share.Research limitations/implicationsThe findings have important implications for the JIC editorial team in order to make informed decisions about the further development of JIC as well as for IC researchers and practitioners to make more valuable contributions to the journal.Originality/valueUsing bibliometric analysis, altmetric analysis and text mining, this study provided a systematic and comprehensive analysis of JIC. The simultaneous use of these methods provides an interesting, unique and suitable capacity to analyze the journals by considering their various aspects.

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