scholarly journals The Online Vaccine Debate: Study of a Visual Analytics System

Informatics ◽  
2020 ◽  
Vol 7 (1) ◽  
pp. 3
Author(s):  
Anton Ninkov ◽  
Kamran Sedig
Keyword(s):  
Public Health ◽  
Language Processing ◽  
Visual Analytics ◽  
User Study ◽  
The Other ◽  
Sense Making ◽  
Online Information ◽  
Sources Of Information ◽  
Reported Study ◽  
Vaccine Debate

Online debates, specifically the ones about public health issues (e.g., vaccines, medications, and nutrition), occur frequently and intensely, and are having an impact on our world. Many public health topics are debated online, one of which is the efficacy and morality of vaccines. When people examine such online debates, they encounter numerous and conflicting sources of information. This information forms the basis upon which people take a position on such debates. This has profound implications for public health. It necessitates a need for public health stakeholders to be able to examine online debates quickly and effectively. They should be able to easily perform sense-making tasks on the vast amount of online information, such as sentiments, online presence, focus, or geographic locations. In this paper, we report the results of a user study of a visual analytic system (VAS), and whether and how this VAS can help with such sense-making tasks. Specifically, we report a usability evaluation of VINCENT (VIsual aNalytiCs systEm for investigating the online vacciNe debaTe), a VAS previously described. To help the reader, we briefly discuss VINCENT’s design in this paper as well. VINCENT integrates webometrics, natural language processing, data visualization, and human-data interaction. In the reported study, we gave users tasks requiring them to make sense of the online vaccine debate. Thirty-four participants were asked to perform these tasks by investigating data from 37 vaccine-focused websites. Half the participants were given access to the system, while the other half were not. Selected study participants from both groups were subsequently asked to be interviewed by the study administrator. Examples of questions and issues discussed with interviewees were: how they went about completing specific tasks, what they meant by some of the feedback they provided, and how they would have performed on the tasks if they had been placed in the other group. Overall, we found that VINCENT was a highly valuable resource for users, helping them make sense of the online vaccine debate much more effectively and faster than those without the system (e.g., users were able to compare websites similarities, identify emotional tone of websites, and locate websites with a specific focus). In this paper, we also identify a few issues that should be taken into consideration when developing VASes for online public health debates.

scholarly journals VINCENT: A visual analytics system for investigating the online vaccine debate

2019 ◽  
Vol 11 (2) ◽  
Author(s):  
Anton Ninkov ◽  
Kamran Sedig
Keyword(s):  
Public Health ◽  
Natural Language Processing ◽  
Natural Language ◽  
Data Visualization ◽  
Language Processing ◽  
Visual Analytics ◽  
Complex Data ◽  
Text Data ◽  
Human Data ◽  
Vaccine Debate

This paper reports and describes VINCENT, a visual analytics system that is designed to help public health stakeholders (i.e., users) make sense of data from websites involved in the online debate about vaccines. VINCENT allows users to explore visualizations of data from a group of 37 vaccine-focused websites. These websites differ in their position on vaccines, topics of focus about vaccines, geographic location, and sentiment towards the efficacy and morality of vaccines, specific and general ones. By integrating webometrics, natural language processing of website text, data visualization, and human-data interaction, VINCENT helps users explore complex data that would be difficult to understand, and, if at all possible, to analyze without the aid of computational tools.The objectives of this paper are to explore A) the feasibility of developing a visual analytics system that integrates webometrics, natural language processing of website text, data visualization, and human-data interaction in a seamless manner; B) how a visual analytics system can help with the investigation of the online vaccine debate; and C) what needs to be taken into consideration when developing such a system. This paper demonstrates that visual analytics systems can integrate different computational techniques; that such systems can help with the exploration of public health online debates that are distributed across a set of websites; and that care should go into the design of the different components of such systems. 

scholarly journals Towards the Other Side of Complexity: Values and Decisions in a Time of Uncertainty

2021 ◽  
pp. 211-214
Author(s):  
Marcelo Knobel
Keyword(s):  
Public Health ◽  
Scientific Community ◽  
The Other ◽  
Highly Qualified ◽  
Sources Of Information ◽  
Health Consequences ◽  
Health Measures ◽  
Great Uncertainty ◽  
Short Time ◽  
First Time

AbstractHumanity is experiencing a moment of great uncertainty. This is not the first time a pandemic threatens the lives of millions of people. However, the speed with which governments and scientists are reacting to events is unprecedented. In an incredibly short time after the discovery of the virus, public health measures were implemented, and the development of defences in the form of public policies, medical therapies, and vaccines began. At this precarious moment, when the proliferation of information (and misinformation) from a variety of sources contribute to the spread of panic, universities and the scientific community emerge as the best and most reliable sources of information. It is only highly qualified specialists who can truly address the pandemic and its terrible economic, political, and public health consequences.

scholarly journals Single Document Automatic Text Summarization using Term Frequency-Inverse Document Frequency (TF-IDF)

2016 ◽  
Vol 7 (4) ◽  
pp. 285 ◽  
Author(s):  
Hans Christian ◽  
Mikhael Pramodana Agus ◽  
Derwin Suhartono
Keyword(s):  
Language Processing ◽  
Text Summarization ◽  
The Other ◽  
Online Information ◽  
Inverse Document Frequency ◽  
Automatic Text Summarization ◽  
Document Frequency ◽  
Online Source ◽  
Automatic Text ◽  
F Measure

The increasing availability of online information has triggered an intensive research in the area of automatic text summarization within the Natural Language Processing (NLP). Text summarization reduces the text by removing the less useful information which helps the reader to find the required information quickly. There are many kinds of algorithms that can be used to summarize the text. One of them is TF-IDF (TermFrequency-Inverse Document Frequency). This research aimed to produce an automatic text summarizer implemented with TF-IDF algorithm and to compare it with other various online source of automatic text summarizer. To evaluate the summary produced from each summarizer, The F-Measure as the standard comparison value had been used. The result of this research produces 67% of accuracy with three data samples which are higher compared to the other online summarizers.

Covid-19 – rumours and facts in media

2020 ◽  
Vol 11 (SPL1) ◽  
pp. 171-174
Author(s):  
Tarare Toshida ◽  
Chaple Jagruti
Keyword(s):  
Social Media ◽  
Preventive Measures ◽  
Vital Role ◽  
The Other ◽  
Sources Of Information ◽  
Other Hand ◽  
Corona Virus ◽  
The People ◽  
The World

The covid-19 resulted in broad range of spread throughout the world in which India has also became a prey of it and in this situation the means of media is extensively inϑluencing the mentality of the people. Media always played a role of loop between society and sources of information. In this epidemic also media is playing a vital role in shaping the reaction in ϑirst place for both good and ill by providing important facts regarding symptoms of Corona virus, preventive measures against the virus and also how to deal with any suspect of disease to overcome covid-19. On the other hand, there are endless people who spread endless rumours overs social media and are adversely affecting life of people but we always count on media because they provide us with valuable answers to our questions, facts and everything in need. Media always remains on top of the line when it comes to stop the out spread of rumours which are surely dangerous kind of information for society. So on our side we should react fairly and maturely to handle the situation to keep it in the favour of humanity and help government not only to ϑight this pandemic but also the info emic.

Japanese-language videos on YouTube as a source of public health information for COVID-19 (Preprint)

2020 ◽  
Author(s):  
Takeo Yasu
Keyword(s):  
Public Health ◽  
Health Information ◽  
Scientific Evidence ◽  
The State ◽  
Video Content ◽  
Sources Of Information ◽  
State Of Emergency ◽  
Public Health Information ◽  
Youtube Videos ◽  
Spread Of Infection

BACKGROUND Serious public health problems, such as the COVID-19 pandemic, can cause an infodemic. Sources of information that may cause an infodemic include social networking services; YouTube, which consists of content created and uploaded by individuals, is one such source. OBJECTIVE To survey the content and changes in YouTube videos that present public health information about COVID-19 in Japan. METHODS We surveyed YouTube content regarding public health information pertaining to COVID-19 in Japan. YouTube searches were performed on March 6, 2020 (before the state of emergency), April 14 (during the state of emergency), and May 27 (after the state of emergency was lifted), with 136, 113, and 140 sample videos evaluated, respectively. The main outcome measures were: (1) The total number of views for each video, (2) video content, and (3) the usefulness of the video. RESULTS In the 100 most viewed YouTube videos during the three periods, the number of videos on public health information in March was significantly higher than in May (p = .02). Of the 331 unique videos, 9.1% (n = 30) were released by healthcare professionals. Useful videos providing public health information about the prevention of the spread of infection comprised only 13.0% of the sample but were viewed significantly more often than not useful videos (p = .006). CONCLUSIONS Individuals need to take care when obtaining information from YouTube before or early in a pandemic, during which time scientific evidence is scarce.

scholarly journals Machine Learning in Medical Emergencies: a Systematic Review and Analysis

2021 ◽  
Vol 45 (10) ◽  
Author(s):  
Inés Robles Mendo ◽  
Gonçalo Marques ◽  
Isabel de la Torre Díez ◽  
Miguel López-Coronado ◽  
Francisco Martín-Rodríguez
Keyword(s):  
Machine Learning ◽  
Systematic Review ◽  
Language Processing ◽  
Emergency Services ◽  
Clinical Decision ◽  
Quality Of Healthcare ◽  
The Other ◽  
Other Hand ◽  
Increasing Demand ◽  
Commercial Applications

AbstractDespite the increasing demand for artificial intelligence research in medicine, the functionalities of his methods in health emergency remain unclear. Therefore, the authors have conducted this systematic review and a global overview study which aims to identify, analyse, and evaluate the research available on different platforms, and its implementations in healthcare emergencies. The methodology applied for the identification and selection of the scientific studies and the different applications consist of two methods. On the one hand, the PRISMA methodology was carried out in Google Scholar, IEEE Xplore, PubMed ScienceDirect, and Scopus. On the other hand, a review of commercial applications found in the best-known commercial platforms (Android and iOS). A total of 20 studies were included in this review. Most of the included studies were of clinical decisions (n = 4, 20%) or medical services or emergency services (n = 4, 20%). Only 2 were focused on m-health (n = 2, 10%). On the other hand, 12 apps were chosen for full testing on different devices. These apps dealt with pre-hospital medical care (n = 3, 25%) or clinical decision support (n = 3, 25%). In total, half of these apps are based on machine learning based on natural language processing. Machine learning is increasingly applicable to healthcare and offers solutions to improve the efficiency and quality of healthcare. With the emergence of mobile health devices and applications that can use data and assess a patient's real-time health, machine learning is a growing trend in the healthcare industry.

scholarly journals Delivery of the National Child Measurement Programme in England

2020 ◽  
pp. 1-21
Author(s):  
Martin Čadek ◽  
Stuart W. Flint ◽  
Ralph Tench
Keyword(s):  
Public Health ◽  
Local Government ◽  
Best Practice ◽  
Online Survey ◽  
The Other ◽  
Service Availability ◽  
Healthy Weight ◽  
Weight Category ◽  
Convenience Sampling

Abstract Objective: The National Child Measurement Programme (NCMP) is a mandatory initiative delivered in England to children in reception and year 6. To date, no research has explored the methods used to deliver the NCMP by Local Government Authorities (LGA) across England. Design: An online survey was administered between February 2018 and May 2018 to explore the delivery of the NCMP across the 152 LGAs in England and disseminated using non-probability convenience sampling. Setting: LGAs received an anonymous link to the survey. Participants: A total of 92 LGAs participated in the survey. Results: Most LGAs who responded provide result feedback (86%), a proactive follow-up (71%) and referrals to services (80%). Additionally, 65% of the authorities tailor Public Health England specimen result letters to suit their needs, and 84% provide attachments alongside. Out of 71% of LGAs who provide proactive follow-up, 19 (29%) provide the proactive follow-up only to upper weight categories, and only 4 (6 %) include Healthy Weight category with other categories in proactive follow-up. Regarding the service availability for children, out of 80% of LGAs who indicated that services are available, 32 (43%) targeted solely upper weight categories while the other 42 (57%) offered services across all weight categories. Finally, most LGAs (88%) commission providers to manage various parts of the NCMP. Conclusions: The results show that LGAs in England localise the NCMP. Further guidance regarding standards of best practice would help LGAs to find the most suitable localisation out of various options that exist across other LGAs.

scholarly journals COVID-19: systematic learning across boundaries requires a conceptual agreement

2021 ◽  
pp. 140349482110270
Author(s):  
Knut Ole Sundnes ◽  
Geir Sverre Braut
Keyword(s):  
Public Health ◽  
Knowledge Base ◽  
External Validity ◽  
Evaluation Research ◽  
The Other ◽  
Basic Knowledge ◽  
Early Publication ◽  
Number Of Publications ◽  
Short Time

The COVID-19 epidemic has revealed a shortage of basic knowledge and understanding of pandemics, especially regarding their dynamics and how to contain them. The results are a host of governments’ decrees and instructions, one replacing the other, often within the same week. It has further, in a truly short time, resulted in an overwhelming number of publications, many of them prioritising early publication over quality. This commentary addresses the concept of structured research related to disasters and how the use of endorsed guidelines will facilitate well-designed evaluation research with improved rigour and external validity, even if applied retrospectively. The outcome should be a solidified knowledge base. Further, the important role of public health efforts is to be highlighted, as their role has proved crucial during the COVID-19 pandemic.

scholarly journals Development of a Genoserotyping Method for Salmonella Infantis Detection on the Basis of Pangenome Analysis

2020 ◽  
Vol 9 (1) ◽  
pp. 67
Author(s):  
Seung-Min Yang ◽  
Jiwon Baek ◽  
Eiseul Kim ◽  
Hyeon-Be Kim ◽  
Seyoung Ko ◽  
...  
Keyword(s):  
Public Health ◽  
Polymerase Chain Reaction ◽  
Bacterial Species ◽  
Cost Effective ◽  
The Other ◽  
Gene Marker ◽  
Diagnostic Assay ◽  
Chain Reaction ◽  
Polymerase Chain ◽  
Substantial Economic Burden

In recent years, Salmonella Infantis has become a predominant serovariant in clinical and poultry isolates, thereby imposing a substantial economic burden on both public health and the livestock industry. With the aim of coping with the steep increase in serovar Infantis prevalence, a polymerase chain reaction (PCR)-based rapid and accurate diagnostic assay was developed in this study through pangenome profiling of 60 Salmonella serovars. A gene marker, SIN_02055, was identified, which is present in the S. Infantis genome but not in the pangenome of the other serovars. Primers specific to SIN_02055 were used to accurately detect serovar Infantis, and to successfully differentiate Infantis from the other 59 serovars in real-time PCR with a R2 of 0.999 and an efficiency of 95.76%. The developed method was applied to 54 Salmonella strains belonging to eight dominant serovars, and distinguished Infantis from the other seven serovars with an accuracy of 100%. The diagnostic primer set also did not show false positive amplification with 32 strains from eight non-Salmonella bacterial species. This cost-effective and rapid method can be considered an alternative to the classic serotyping using antisera.

scholarly journals Examining Australian’s beliefs, misconceptions and sources of information for COVID-19: a national online survey

BMJ Open ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. e043421
Author(s):  
Rae Thomas ◽  
Hannah Greenwood ◽  
Zoe A Michaleff ◽  
Eman Abukmail ◽  
Tammy C Hoffmann ◽  
...  
Keyword(s):  
Public Health ◽  
Online Survey ◽  
Health Behaviours ◽  
National Sample ◽  
Sources Of Information ◽  
Cross Sectional Survey ◽  
Commercial Television ◽  
Cross Sectional ◽  
And Gender ◽  
Public Health Strategies

ObjectivePublic cooperation to practise preventive health behaviours is essential to manage the transmission of infectious diseases such as COVID-19. We aimed to investigate beliefs about COVID-19 diagnosis, transmission and prevention that have the potential to impact the uptake of recommended public health strategies.DesignAn online cross-sectional survey.ParticipantsA national sample of 1500 Australian adults with representative quotas for age and gender provided by an online panel provider.Main outcome measureProportion of participants with correct/incorrect knowledge of COVID-19 preventive behaviours and reasons for misconceptions.ResultsOf the 1802 potential participants contacted, 289 did not qualify, 13 declined and 1500 participated in the survey (response rate 83%). Most participants correctly identified ‘washing your hands regularly with soap and water’ (92%) and ‘staying at least 1.5 m away from others’ (90%) could help prevent COVID-19. Over 40% (incorrectly) considered wearing gloves outside of the home would prevent them from contracting COVID-19. Views about face masks were divided. Only 66% of participants correctly identified that ‘regular use of antibiotics’ would not prevent COVID-19.Most participants (90%) identified ‘fever, fatigue and cough’ as indicators of COVID-19. However, 42% of participants thought that being unable to ‘hold your breath for 10 s without coughing’ was an indicator of having the virus. The most frequently reported sources of COVID-19 information were commercial television channels (56%), the Australian Broadcasting Corporation (43%) and the Australian Government COVID-19 information app (31%).ConclusionsPublic messaging about hand hygiene and physical distancing to prevent transmission appears to have been effective. However, there are clear, identified barriers for many individuals that have the potential to impede uptake or maintenance of these behaviours in the long term. We need to develop public health messages that harness these barriers to improve future cooperation. Ensuring adherence to these interventions is critical.

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