Video Data for Escalator Accidents

Many videos of escalator accidents are available on social media, especially YouTube. A review of a large sample of such videos reveals information about some types of accidents not readily found or well described in hospital reports and behavioral observations. These include numerous deliberate misuse modes such as sliding or riding on handrails, as well as risky activity such as wearing clothes that can become entangled in the mechanism and traveling in the wrong direction, and various mechanical problems. Advantages and limitations of video data are discussed, along with suggestions for possible safety interventions.

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Social Media and the Knowledge Gap

10.4018/978-1-7998-8630-3.ch019 ◽

2022 ◽

pp. 344-361

Author(s):

Çiçek Topçu

Keyword(s):

Social Media ◽

Field Research ◽

Knowledge Gap ◽

Communication Tool ◽

Media Environment ◽

Large Sample ◽

Level Of Knowledge ◽

Use Of Social Media ◽

The Relationship ◽

Empirical Field

This study aims to test the relationship between the use of social media and the knowledge gap regarding COVID-19 in the Turkish environment. For this purpose of this empirical field, research was carried out throughout Turkey involving a large sample (N= 1033) in an effort to reveal how level of knowledge of social media users in Turkey regarding an issue in a particular question is shaped. The study discusses the data obtained in the field research. The conclusion, contrary to what is expected, emphasizes that social media environment has a particular presence as a communication tool, which closes the knowledge gap and fosters knowledge acquisition.

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Characteristics and beach safety knowledge of beachgoers on unpatrolled surf beaches in Australia

10.5194/nhess-2021-318 ◽

2021 ◽

Author(s):

Lea Uebelhoer ◽

William Koon ◽

Mitchell D. Harley ◽

Jasmin C. Lawes ◽

Robert W. Brander

Keyword(s):

Risk Factors ◽

Social Media ◽

New South ◽

Hazard Identification ◽

Rip Current ◽

Beach Safety ◽

Factors Associated ◽

South Wales ◽

Safety Interventions ◽

Safety Knowledge

Abstract. The majority of drowning deaths on Australian beaches occur significant distances away from lifeguard services. This study uses results of 459 surveys of beachgoers at five beaches unpatrolled by lifeguards in New South Wales, Australia to improve understanding of who visits these beaches and why, and to identify risk factors associated with their beach safety knowledge and behaviour. Many unpatrolled beach users were infrequent beachgoers and weak swimmers, with poor rip current hazard identification skills, who did not observe safety signage that was present, and yet intended to enter the water to swim despite being aware that no lifeguards were present. The survey found that the main reasons beachgoers visited unpatrolled beaches were because they were conveniently close to their holiday accommodation, or they represented a quieter location away from crowds. Future beach safety interventions in Australia need to extend beyond the standard ‘swim between the flags’ message in recognition that people will always frequent unpatrolled beaches. Future beach safety interventions for unpatrolled beaches should be tailored towards the varied types of demographic beach users, such as domestic tourist families, males, and day visitors attracted by social media.

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Utilization of Big Data Analysis Through Public Video, Virus Data Cooperation, and Social Media as the Surveillance to COVID-19 in Indonesia

Jurnal Ilmu Sosial dan Ilmu Politik ◽

10.22146/jsp.56491 ◽

2021 ◽

Vol 25 (1) ◽

pp. 1

Author(s):

Achmad Maulana Sirojjudin

Keyword(s):

Social Media ◽

Big Data ◽

Data Analysis ◽

Virus Disease ◽

Big Data Analysis ◽

Video Data ◽

Communication Process ◽

Mediated Communication ◽

Communication Practices ◽

Geographical Characteristics

This article discusses Big Data's use as a surveillance tool for the spread of Corona Virus Disease 2019 (COVID-19), both in Indonesia and the world. In Indonesia, the range of COVID-19 is increasingly sporadic, causing mass panic and Indonesia's geographical characteristics, which will be difficult when this spread could not control quickly. Researchers are conducting several studies to overcome this pandemic, including supervision, features, handling, mobility, patient interaction, treatment evaluation, and the biological structure. These studies become data and lead to Big Data. This article explores how to use Big Data analysis to monitor the spread of COVID-19 as a communication process that reflects mediated communication as a form of mobility and spatial relationships in communication practices. The method used in this article is a literature review and uses meta-synthesis techniques as its analysis. The literature sources used are articles in highly reputable international journals. Based on the reports, various ways to monitor the virus's spread, through public video data, GPS, and social media tracking, trace the patient's movement. Big Data can also provide data collaboration for viruses and pathogens for further research as digital mediated communication is anchored by the diversity of places and the mobility of people, data, and objects.

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A feasibility study on identifying drinking-related contents in Facebook through mining heterogeneous data

Health Informatics Journal ◽

10.1177/1460458218798084 ◽

2018 ◽

Vol 25 (4) ◽

pp. 1756-1767 ◽

Cited By ~ 6

Author(s):

Omar ElTayeby ◽

Todd Eaglin ◽

Malak Abdullah ◽

David Burlinson ◽

Wenwen Dou ◽

...

Keyword(s):

Social Media ◽

Feasibility Study ◽

Prediction Models ◽

Heterogeneous Data ◽

Video Data ◽

Data Types ◽

Text Data ◽

Related Text ◽

Text Images ◽

Severe Health Problem

Binge drinking is a severe health problem faced by many US colleges and universities. College students often post drinking-related text and images on social media, portraying their alcohol use as socially desirable. In this project, we investigated the feasibility of mining the heterogeneous data (e.g. text, images, and videos) on Facebook to identify drinking-related contents. We manually annotated 4266 posts during 21 October 2011 and 3 November 2014 from “I’m Shmacked” group on Facebook, where 511 posts were drinking-related. Our machine learning models show that by combining heterogeneous data types, we were able to identify drinking-related posts with an F1-score of 0.81. Prediction models built on text data were more reliable compared to those built on image and video data for predicting drinking-related contents. As the first step of our efforts in this direction, this feasibility study showed promise toward unleashing the potential of mining social media to identify students who binge drink.

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Assessing the Impact of the COVID-19 Pandemic in Spain: Large-Scale, Online, Self-Reported Population Survey

Journal of Medical Internet Research ◽

10.2196/21319 ◽

2020 ◽

Vol 22 (9) ◽

pp. e21319 ◽

Cited By ~ 2

Author(s):

Nuria Oliver ◽

Xavier Barber ◽

Kirsten Roomp ◽

Kristof Roomp

Keyword(s):

Social Media ◽

Social Behavior ◽

Economic Impact ◽

Large Scale ◽

Online Survey ◽

Spanish Population ◽

Survey Method ◽

Economic Damage ◽

Large Sample ◽

The Impact

Background Spain has been one of the countries most impacted by the COVID-19 pandemic. Since the first confirmed case was reported on January 31, 2020, there have been over 405,000 cases and 28,000 deaths in Spain. The economic and social impact is without precedent. Thus, it is important to quickly assess the situation and perception of the population. Large-scale online surveys have been shown to be an effective tool for this purpose. Objective We aim to assess the situation and perception of the Spanish population in four key areas related to the COVID-19 pandemic: social contact behavior during confinement, personal economic impact, labor situation, and health status. Methods We obtained a large sample using an online survey with 24 questions related to COVID-19 in the week of March 28-April 2, 2020, during the peak of the first wave of COVID-19 in Spain. The self-selection online survey method of nonprobability sampling was used to recruit 156,614 participants via social media posts that targeted the general adult population (age >18 years). Given such a large sample, the 95% CI was ±0.843 for all reported proportions. Results Regarding social behavior during confinement, participants mainly left their homes to satisfy basic needs. We found several statistically significant differences in social behavior across genders and age groups. The population’s willingness to comply with the confinement measures is evident. From the survey answers, we identified a significant adverse economic impact of the pandemic on those working in small businesses and a negative correlation between economic damage and willingness to stay in confinement. The survey revealed that close contacts play an important role in the transmission of the disease, and 28% of the participants lacked the necessary resources to properly isolate themselves. We also identified a significant lack of testing, with only 1% of the population tested and 6% of respondents unable to be tested despite their doctor’s recommendation. We developed a generalized linear model to identify the variables that were correlated with a positive SARS-CoV-2 test result. Using this model, we estimated an average of 5% for SARS-CoV-2 prevalence in the Spanish population during the time of the study. A seroprevalence study carried out later by the Spanish Ministry of Health reported a similar level of disease prevalence (5%). Conclusions Large-scale online population surveys, distributed via social media and online messaging platforms, can be an effective, cheap, and fast tool to assess the impact and prevalence of an infectious disease in the context of a pandemic, particularly when there is a scarcity of official data and limited testing capacity.

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Survei Pengetahuan Orang Tua melalui Kegiatan Sekolah Keluarga Balita (SKB) dengan Online Learning

Jurnal Bidan Cerdas (JBC) ◽

10.33860/jbc.v2i3.91 ◽

2020 ◽

Vol 2 (3) ◽

pp. 147-153

Author(s):

Ari Indra Susanti ◽

Dani Ferdian ◽

Eka Noyan Nur Annisa ◽

Raya Faiha Calista

Keyword(s):

Social Media ◽

Online Learning ◽

Health Education ◽

Research Method ◽

Sampling Technique ◽

Video Data ◽

Learning Activities ◽

Cross Sectional ◽

Digital Era ◽

Information Media

Health education in the digital era requires one social media, namely WhatsApp as an information media that is considered effective and efficient. Thus, parents get health education through WhatsApp in the Sekolah Keluarga Balita (SKB) online learning activities with the agreed time. This study aims to determine the knowledge of parents about the First 1000 Days of Life (HPK) through the SKB online learning that used WhatsApp. The research method used description with a cross-sectional approach. This research was conducted in March 2020 among parents of toddlers living in the fostered villages of Kampung Bestari Astra (KBA) as many as 150 people. The sampling technique was used accidental sampling. This questionnaire was given to the respondent in the form of bit.ly/ (google form). This questionnaire was filled out by respondents before being given a health education video. Data analysis using univariate have presented in the form of a frequency distribution table. The results showed that most participants in the Joint Decree were 135 people, with the age of 20-35 years as many as 60 people, and 78 parents were unfavorable knowledge. The conclusion in this study that some parents aged 20-35 years have less knowledge about the First 1000 Days of Life (HPK) so that health education is needed in a Toddler Family School (SKB) online using WhatsApp.

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Assessing the Impact of the COVID-19 Pandemic in Spain: Large-Scale, Online, Self-Reported Population Survey (Preprint)

10.2196/preprints.21319 ◽

2020 ◽

Author(s):

Nuria Oliver ◽

Xavier Barber ◽

Kirsten Roomp ◽

Kristof Roomp

Keyword(s):

Social Media ◽

Social Behavior ◽

Economic Impact ◽

Large Scale ◽

Online Survey ◽

Spanish Population ◽

Survey Method ◽

Economic Damage ◽

Large Sample ◽

The Impact

BACKGROUND Spain has been one of the countries most impacted by the COVID-19 pandemic. Since the first confirmed case was reported on January 31, 2020, there have been over 405,000 cases and 28,000 deaths in Spain. The economic and social impact is without precedent. Thus, it is important to quickly assess the situation and perception of the population. Large-scale online surveys have been shown to be an effective tool for this purpose. OBJECTIVE We aim to assess the situation and perception of the Spanish population in four key areas related to the COVID-19 pandemic: social contact behavior during confinement, personal economic impact, labor situation, and health status. METHODS We obtained a large sample using an online survey with 24 questions related to COVID-19 in the week of March 28-April 2, 2020, during the peak of the first wave of COVID-19 in Spain. The self-selection online survey method of nonprobability sampling was used to recruit 156,614 participants via social media posts that targeted the general adult population (age >18 years). Given such a large sample, the 95% CI was ±0.843 for all reported proportions. RESULTS Regarding social behavior during confinement, participants mainly left their homes to satisfy basic needs. We found several statistically significant differences in social behavior across genders and age groups. The population’s willingness to comply with the confinement measures is evident. From the survey answers, we identified a significant adverse economic impact of the pandemic on those working in small businesses and a negative correlation between economic damage and willingness to stay in confinement. The survey revealed that close contacts play an important role in the transmission of the disease, and 28% of the participants lacked the necessary resources to properly isolate themselves. We also identified a significant lack of testing, with only 1% of the population tested and 6% of respondents unable to be tested despite their doctor’s recommendation. We developed a generalized linear model to identify the variables that were correlated with a positive SARS-CoV-2 test result. Using this model, we estimated an average of 5% for SARS-CoV-2 prevalence in the Spanish population during the time of the study. A seroprevalence study carried out later by the Spanish Ministry of Health reported a similar level of disease prevalence (5%). CONCLUSIONS Large-scale online population surveys, distributed via social media and online messaging platforms, can be an effective, cheap, and fast tool to assess the impact and prevalence of an infectious disease in the context of a pandemic, particularly when there is a scarcity of official data and limited testing capacity.

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