A Research on Perceptions of Health News of Individuals Who Lived in Istanbul in the COVID-19 Process

Health communication is a field that is increasing in importance and developing in public health and non-profit organizations and the business sector. COVID-19 is a new type of virus that affects the whole world and is diagnosed with fever, dry cough, malaise, and symptoms of dyspnea. This research was formed to masculate their perceptions related to individual health news in Istanbul. The study sample was formed by adults, individuals aged over 18 years, who lived in Istanbul. The research has been applied by personal information forms and perceptions of health news scale.

Tweet and Retweet Journalism During the Pandemic:

ABSTRACT – Starting from a gap identified in the literature regarding the use of social networks by newspapers to disseminate urgent news, this article aims to study strategies of journalistic content in social media, particularly in the context of a public crisis and to compare the effectiveness of different types of news disseminated in this medium, namely in terms of reach and generated interaction. The following research question was defined: how popular was public health news in Brazil during the covid-19 pandemic? Based on contributions in the literature, a quantitative study was carried out, using the content analysis technique. The study enable to better understand the sharing behavior of news in Twitter, the consumption behavior of newspaper readers on social networks and the generation of news during the pandemic. RESUMO – Partindo de uma lacuna identificada na literatura quanto ao uso das redes sociais pelos jornais para divulgação de notícias urgentes, este artigo tem como objetivo estudar estratégias no consumo de conteúdo jornalístico nas mídias sociais, particularmente durante uma crise mundial, e comparar a eficácia de diferentes modalidades de notícias divulgadas neste meio, nomeadamente ao nível do alcance e da interação gerada. Definiu-se a seguinte questão de pesquisa: qual a popularidade das notícias de saúde pública no Brasil durante a pandemia de covid-19? Com base nas contribuições da literatura, foi realizado um estudo quantitativo, utilizando a técnica de análise de conteúdo. O estudo possibilitou compreender melhor o comportamento de compartilhamento de notícias no Twitter, o comportamento de consumo dos leitores de jornais nas redes sociais e a geração de notícias durante a pandemia. RESUMEN – A partir de una brecha identificada en la literatura sobre el uso de las redes sociales por parte de los periódicos para difundir noticias urgentes, este artículo tiene como objetivo estudiar estrategias en el consumo de periodistas de noticias en las redes sociales, particularmente durante una crisis global y comparar la efectividad de diferentes modalidades de las noticias difundidas en este medio, es decir, en términos de alcance e interacción generada. Se definió la siguiente pregunta de investigación: ¿cuál es la popularidad de las noticias de salud pública en Brasil durante la pandemia de covid-19? Con base en aportes de la literatura, se realizó un estudio cuantitativo utilizando la técnica de análisis de contenido. El estudio permitió comprender mejor el comportamiento de compartir noticias en Twitter, el comportamiento de consumo de los lectores de periódicos en las redes sociales y la generación de noticias durante la pandemia.

Seeking Scientific Health Information for Empowerment: Empowered-Get-More-Empowered Effects

To explore the scientific value of information elements in health news, this article reports on common information elements that are associated with scientific value, according to the findings of surveys conducted in the United States and Taiwan. The design of two further studies in Taiwan reflects an effort to understand whether scientific information elements benefit only health conscious people, through empowered-get-more-empowered effects. A survey-based analysis of perceptions and an experimental test of causal effects of information exposure reveal that health conscious people seek health information, value scientific information elements in it, are persuaded by them, and act on advice.

An investigation into the deep learning approach in sentimental analysis using graph-based theories

Sentiment analysis is a branch of natural language analytics that aims to correlate what is expressed which comes normally within unstructured format with what is believed and learnt. Several attempts have tried to address this gap (i.e., Naive Bayes, RNN, LSTM, word embedding, etc.), even though the deep learning models achieved high performance, their generative process remains a “black-box” and not fully disclosed due to the high dimensional feature and the non-deterministic weights assignment. Meanwhile, graphs are becoming more popular when modeling complex systems while being traceable and understood. Here, we reveal that a good trade-off transparency and efficiency could be achieved with a Deep Neural Network by exploring the Credit Assignment Paths theory. To this end, we propose a novel algorithm which alleviates the features’ extraction mechanism and attributes an importance level of selected neurons by applying a deterministic edge/node embeddings with attention scores on the input unit and backward path respectively. We experiment on the Twitter Health News dataset were the model has been extended to approach different approximations (tweet/aspect and tweets’ source levels, frequency, polarity/subjectivity), it was also transparent and traceable. Moreover, results of comparing with four recent models on same data corpus for tweets analysis showed a rapid convergence with an overall accuracy of ≈83% and 94% of correctly identified true positive sentiments. Therefore, weights can be ideally assigned to specific active features by following the proposed method. As opposite to other compared works, the inferred features are conditioned through the users’ preferences (i.e., frequency degree) and via the activation’s derivatives (i.e., reject feature if not scored). Future direction will address the inductive aspect of graph embeddings to include dynamic graph structures and expand the model resiliency by considering other datasets like SemEval task7, covid-19 tweets, etc.

Detection of topic on Health News in Twitter Data

Electromyography (EMG) signal is an analysis of electrical signals generated during muscular contractions that have been used to measure and record electrical muscle activity usually applied for medical tests. In this research EMG signal is used to; (1) evaluate muscle activations on different gender during prolonged sitting task; (2) investigate the influence of various types of exercise during prolonged sitting on muscle activation and (3) proposed the best exercise that can help to prevent low back discomfort. Twenty subjects (10 males and 10 females) were recruited from undergraduate engineering student’s education background in UniMAP with age ranging between 20 to 24 years old. The subject must be asymptomatic back pain, normal BMI and right-handed. . Three different types of sitting, one hour per sitting were done by each subject in order to reach the goals of this study. First sitting (sitting without exercise) was conducted while second and third sitting (sitting with exercise) were done in order the investigate the effectiveness of the exercises. Two different types of exercise were performed in second and third sitting, both of exercises were chosen from Mc Kenzie’s exercise. EEGOTM sport device were used to record the EMG signal from four types of muscles which are Erector Spinae, Latissimus Dorsi, Internal Oblique and External Oblique. By comparing the Root Mean Square (RMS) values from EMG signals muscle activation during prolonged sitting and the effectiveness of performing the exercises have been evaluated based on RMS values. As the results, muscle become deactivate during prolonged sitting. The best exercise to reduce back pain discomfort is exercise type 1 (Seated Lumbar Exercise) and it is recommended to perform this exercise regularly to reduce the risk of getting hazardous disease due to prolonged sitting.

Communicating Health Information

Sharing and dissemination of health information needs careful planning to inform both the public and local health staff, local government departments, and the Ministry of Health, as well as other health-related sectors like agriculture, education, water, and environment, and non-governmental health organizations. Local radio and social media are very important for active communications between district teams, health workers, and the wider public. Policy briefs can be used to disseminated and circulate health news, reports and plans. The importance of making power-point presentations and presenting written reports and papers is emphasised.