scholarly journals Psychometric Analysis and Coupling of Emotions Between State Bulletins and Twitter in India During COVID-19 Infodemic

2021 ◽  
Vol 6 ◽  
Author(s):  
Palash Aggrawal ◽  
Baani Leen Kaur Jolly ◽  
Amogh Gulati ◽  
Amarjit Sethi ◽  
Ponnurangam Kumaraguru ◽  
...  
Keyword(s):  
Social Media ◽  
Management Strategy ◽  
State Level ◽  
Medical Emergency ◽  
Governance Systems ◽  
The Social ◽  
Health Related ◽  
The Government ◽  
Epidemic Response ◽  
Second Wave

COVID-19 infodemic has been spreading faster than the pandemic itself. The misinformation riding upon the infodemic wave poses a major threat to people’s health and governance systems. Managing this infodemic not only requires mitigating misinformation but also an early understanding of underlying psychological patterns. In this study, we present a novel epidemic response management strategy. We analyze the psychometric impact and coupling of COVID-19 infodemic with official COVID-19 bulletins at the national and state level in India. We looked at them from the psycholinguistic lens of emotions and quantified the extent and coupling between them. We modified Empath, a deep skipgram-based lexicon builder, for effective capture of health-related emotions. Using this, we analyzed the lead-lag relationships between the time-evolution of these emotions in social media and official bulletins using Granger’s causality. It showed that state bulletins led the social media for some emotions such as Medical Emergency. In contrast, social media led the government bulletins for some topics such as hygiene, government, fun, and leisure. Further insights potentially relevant for policymakers and communicators engaged in mitigating misinformation are also discussed. We also introduce CoronaIndiaDataset, the first social-media-based Indian COVID-19 dataset at the national and state levels with over 5.6 million national and 2.6 million state-level tweets for the first wave of COVID-19 in India and 1.2 million national tweets for the second wave of COVID-19 in India.

scholarly journals A Panel Evaluation of the Changes in the General Public’s Social-Media-Following of United States’ Public Health Departments during COVID-19 Pandemic

2021 ◽  
Vol 12 ◽  
pp. 215013272199545
Author(s):  
Areej Khokhar ◽  
Aaron Spaulding ◽  
Zuhair Niazi ◽  
Sikander Ailawadhi ◽  
Rami Manochakian ◽  
...  
Keyword(s):  
Public Health ◽  
Social Media ◽  
State Level ◽  
The State ◽  
Public Health Department ◽  
Health Departments ◽  
The Public ◽  
Public Health Departments ◽  
The Social ◽  
The U.S

Importance: Social media is widely used by various segments of society. Its role as a tool of communication by the Public Health Departments in the U.S. remains unknown. Objective: To determine the impact of the COVID-19 pandemic on social media following of the Public Health Departments of the 50 States of the U.S. Design, Setting, and Participants: Data were collected by visiting the Public Health Department web page for each social media platform. State-level demographics were collected from the U.S. Census Bureau. The Center for Disease Control and Prevention was utilized to collect information regarding the Governance of each State’s Public Health Department. Health rankings were collected from “America’s Health Rankings” 2019 Annual report from the United Health Foundation. The U.S. News and World Report Education Rankings were utilized to provide information regarding the public education of each State. Exposure: Data were pulled on 3 separate dates: first on March 5th (baseline and pre-national emergency declaration (NED) for COVID-19), March 18th (week following NED), and March 25th (2 weeks after NED). In addition, a variable identifying the total change across platforms was also created. All data were collected at the State level. Main Outcome: Overall, the social media following of the state Public Health Departments was very low. There was a significant increase in the public interest in following the Public Health Departments during the early phase of the COVID-19 pandemic. Results: With the declaration of National Emergency, there was a 150% increase in overall public following of the State Public Health Departments in the U.S. The increase was most noted in the Midwest and South regions of the U.S. The overall following in the pandemic “hotspots,” such as New York, California, and Florida, was significantly lower. Interesting correlations were noted between various demographic variables, health, and education ranking of the States and the social media following of their Health Departments. Conclusion and Relevance: Social media following of Public Health Departments across all States of the U.S. was very low. Though, the social media following significantly increased during the early course of the COVID-19 pandemic, but it still remains low. Significant opportunity exists for Public Health Departments to improve social media use to engage the public better.

scholarly journals Social Media in an Emergency: Use of Social Media in Rescuing Abducted School Girls in Nigeria

2019 ◽  
Vol 13 ◽  
pp. 67-75
Author(s):  
Muhammad Abdullahi Maigari ◽  
Uthman Abdullahi Abdul-Qadir
Keyword(s):  
Social Media ◽  
Secondary Sources ◽  
The Social ◽  
Security Challenges ◽  
Social Media Platforms ◽  
Information And Communication ◽  
School Girls ◽  
The Government ◽  
Use Of Social Media ◽  
Domestic Assistance

This paper examines the abduction of the schoolgirls in Chibok Local Government Area of Borno State, Nigeria in 2014. The paper examined how the abduction of the schoolgirls generated responses and support for the rescue of the abducted girls from people and organization from different parts of the globe. The Islamists terrorist organization operating in Borno State has attracted the attention of the world since 2009 when they started attacking government establishments and security installations northeast which later escalated to major cities in Northern Nigeria. Methodologically, the paper utilized secondary sources of data to analyze the phenomenon studied. The paper revealed that the development and innovations in information and communication technology which dismantled traditional and colonial boundaries enabled people to express support, solidarity and assist victims of conflict who resides millions of Kilometers away. This shows that Internet-based communications technology has reduced the distance of time and space that characterised traditional mass media. The campaign for the release of the schoolgirls on the social media platforms particularly Twitter and Facebook has tremendously contributed to the release of some of them. Furthermore, the girls freed from abduction have received proper attention: education and reintegration programmes which enable them to start post-abduction life. In this regard, social media has become a tool for supporting the government in moments of security challenges which the Bring Back Our Girls campaign attracted foreign and domestic assistance to Nigeria in the search of the abducted girls and the fight against the Islamist insurgents.

DEMOCRATIC CHALLENGES OF INDONESIA IN THE SOCIAL MEDIA ERA

2017 ◽  
Vol 2 (2) ◽  
pp. 349
Author(s):  
Nunik Nurhayati ◽  
Rohmad Suryadi
Keyword(s):  
Social Media ◽  
Critical Discourse Analysis ◽  
Public Space ◽  
Political Influence ◽  
Political Support ◽  
The Social ◽  
The Government ◽  
Use Of Social Media ◽  
Democratic Life ◽  
The Impact

The era of social media today bring significant change to democracy in Indonesia. Social media can to bring the expansion of the public space in cyberspace, citizens can directly deliver aspirations regarding the state policy. However, on the other side, social media vulnerable to abuse because of many the anonymous account, which acts as the buzzer political influence public perceptions and to get political support but is not elegant way. This shows, social media provides a challenge to democracy, including Indonesia as a third largest country that has access to the social media in the world's. Based on it’s the problems, this research aims to identify the impact of the social media on democratic life, and how the challenges of democracy in Indonesia ahead in the social media today.This Research using qualitative methods. Data collection through the study of literature. Then analyzed with a critical discourse analysis. The results of the study showed that the impact of social media in Indonesia has brought problems such as hoax, which is currently a serious concern of the government. Attempts were made through the campaign against hoax and make regulation, Information and Electronic Transactions Law (ITE Law), which aims to regulate the use of social media and to prevent hoaxes. The life of democracy in Indonesia receive significant challenges,but of the repressive laws against users of social media may actually weaken the democratic life in Indonesia.

scholarly journals Automated extraction of treatment patterns from social media posts: an exploratory analysis in renal cell carcinoma

2019 ◽  
Vol 15 (31) ◽  
pp. 3587-3596
Author(s):  
Sreeram V Ramagopalan ◽  
Bill Malcolm ◽  
Evie Merinopoulou ◽  
Laura McDonald ◽  
Andrew Cox
Keyword(s):  
Renal Cell Carcinoma ◽  
Social Media ◽  
Cell Carcinoma ◽  
Language Processing ◽  
Renal Cell ◽  
Treatment Patterns ◽  
The Social ◽  
Health Related ◽  
Development And Validation ◽  
Further Development

Aim: The use of health-related social media forums by patients is increasing and the size of these forums creates a rich record of patient opinions and experiences, including treatment histories. This study aimed to understand the possibility of extracting treatment patterns in an automated manner for patients with renal cell carcinoma, using natural language processing, rule-based decisions, and machine learning. Patients & methods: Obtained results were compared with those from published observational studies. Results: 42 comparisons across seven therapies, three lines of treatment, and two-time periods were made; 37 of the social media estimates fell within the variation seen across the published studies. Conclusion: This exploratory work shows that estimating treatment patterns from social media is possible and generates results within the variation seen in published studies, although further development and validation of the approach is needed.

Social Media News Classification in Healthcare Communication

2019 ◽  
Vol 9 (6) ◽  
pp. 1215-1223 ◽  
Author(s):  
Fiaz Majeed ◽  
Muhammad Waqas Asif ◽  
Muhammad Awais Hassan ◽  
Syed Ali Abbas ◽  
M. Ikramullah Lali
Keyword(s):  
Social Media ◽  
Support Vector ◽  
Learning Approaches ◽  
Healthcare Organizations ◽  
Significant Information ◽  
Health News ◽  
Related Data ◽  
The Social ◽  
Health Related ◽  
Better Than

The trend of news transmission is rapidly shifting from electronic media to social media. Currently, news channels in general, while health news channels specifically send health related news on social media sites. These news are beneficial for the patients, medical professionals and the general public. A lot of health related data is available on the social media that may be used to extract significant information and present several predictions from it to assist physicians, patients and healthcare organizations for decision making. However, A little research is found on health news data using machine learning approaches, thus in this paper, we have proposed a framework for the data collection, modeling, and visualization of the health related patterns. For the analysis, the tweets of 13 news channels are collected from the Twitter. The dataset holds approximately 28k tweets available under 280 hashtags. Furthermore, a comprehensive set of experiments are performed to extract patterns from the data. A comparative analysis is carried among the baseline method and four classification algorithms which include Naive Bayes (NB), Support Vector Machine (SVM), Logistic Regression (LR), Decision Tree (J48). For the evaluation of the results, the standard measures accuracy, precision, recall and f-measure have been used. The results of the study are encouraging and better than the other studies of such kind.

How to strengthen the social media interactivity of e-government

2016 ◽  
Vol 40 (1) ◽  
pp. 79-96 ◽  
Author(s):  
xiaoling Hao ◽  
Daqing Zheng ◽  
Qingfeng Zeng ◽  
Weiguo Fan
Keyword(s):  
Social Media ◽  
Local Governments ◽  
Structural Features ◽  
Content Type ◽  
The Public ◽  
Positive Effects ◽  
Popular Government ◽  
The Social ◽  
Social Media Platforms ◽  
The Government

Purpose – The purpose of this paper is to explore how to use social media in e-government to strengthen interactivity between government and the general public. Design/methodology/approach – Categorizing the determinants to interactivity covering depth and breadth into two aspects that are the structural features and the content features, this study employs general linear model and ANOVA method to analyse 14,910 posts belonged to the top list of the 96 most popular government accounts of Sina, one of the largest social media platforms in China. Findings – The main findings of the research are that both variables of the ratio of multimedia elements, and the ratio of external links have positive effects on the breadth of interactivity, while the ratio of multimedia features, and the ratio of originality have significant effects on the depth of interactivity. Originality/value – The contributions are as follows. First, the authors analyse the properties and the topics of government posts to draw a rich picture of how local governments use the micro-blog as a communications channel to interact with the public. Second, the authors conceptualize the government online interactivity in terms of the breadth and depth. Third, the authors identify factors that will enhance the interactivity from two aspects: structural features and content features. Lastly, the authors offer suggestions to local governments on how to strengthen the e-government interactivity in social media.

scholarly journals Data and systems for medication-related text classification and concept normalization from Twitter: insights from the Social Media Mining for Health (SMM4H)-2017 shared task

2018 ◽  
Vol 25 (10) ◽  
pp. 1274-1283 ◽  
Author(s):  
Abeed Sarker ◽  
Maksim Belousov ◽  
Jasper Friedrichs ◽  
Kai Hakala ◽  
Svetlana Kiritchenko ◽  
...  
Keyword(s):  
Social Media ◽  
Text Classification ◽  
Training Data ◽  
Support Vector ◽  
Shared Task ◽  
Social Media Mining ◽  
The Social ◽  
Related Text ◽  
Health Related ◽  
Media Mining

AbstractObjectiveWe executed the Social Media Mining for Health (SMM4H) 2017 shared tasks to enable the community-driven development and large-scale evaluation of automatic text processing methods for the classification and normalization of health-related text from social media. An additional objective was to publicly release manually annotated data.Materials and MethodsWe organized 3 independent subtasks: automatic classification of self-reports of 1) adverse drug reactions (ADRs) and 2) medication consumption, from medication-mentioning tweets, and 3) normalization of ADR expressions. Training data consisted of 15 717 annotated tweets for (1), 10 260 for (2), and 6650 ADR phrases and identifiers for (3); and exhibited typical properties of social-media-based health-related texts. Systems were evaluated using 9961, 7513, and 2500 instances for the 3 subtasks, respectively. We evaluated performances of classes of methods and ensembles of system combinations following the shared tasks.ResultsAmong 55 system runs, the best system scores for the 3 subtasks were 0.435 (ADR class F1-score) for subtask-1, 0.693 (micro-averaged F1-score over two classes) for subtask-2, and 88.5% (accuracy) for subtask-3. Ensembles of system combinations obtained best scores of 0.476, 0.702, and 88.7%, outperforming individual systems.DiscussionAmong individual systems, support vector machines and convolutional neural networks showed high performance. Performance gains achieved by ensembles of system combinations suggest that such strategies may be suitable for operational systems relying on difficult text classification tasks (eg, subtask-1).ConclusionsData imbalance and lack of context remain challenges for natural language processing of social media text. Annotated data from the shared task have been made available as reference standards for future studies (http://dx.doi.org/10.17632/rxwfb3tysd.1).

scholarly journals Comprehension, Perception, and Practice of Indians about COVID-19 Anticipating the Second Wave of the Pandemic

2021 ◽  
Vol 11 (4) ◽  
pp. 215-224
Author(s):  
Prakash Gondode ◽  
◽  
Amrusha Raipure ◽  
Bhuvaneswari Balasubramanian ◽  
Abhinav Lambe ◽  
...  
Keyword(s):  
Social Media ◽  
Informed Consent ◽  
Good Practice ◽  
The Self ◽  
Convenience Sample ◽  
The Social ◽  
True Answer ◽  
Practice Knowledge ◽  
The City ◽  
Second Wave

Background: We assessed knowledge, attitudes, practice, and perceptions about COVID-19 among a convenience sample of the general public in India anticipating the second wave of the pandemic. Methods: This questionnaire-based survey was conducted among the general population quarantined at various institutional quarantine facilities in the city of Nagpur, Maharashtra, India. Informed consent was obtained from each participant. The self-designed questionnaire comprised 25 questions regarding knowledge, eight for attitude, and ten for practice. Knowledge questions were responded to on a Yes/No basis with an additional ‘don’t know’ option. The true answer was given 1 point and false/I don’t know answers were given 0 point. Results: The majority of the participants were aware of COVID-19 (97.9%) and did not either wash or knew how to properly dispose of the used mask (88.02%). Only 10.96% of the participants agreed that they verify the social media posts shared over WhatsApp and Facebook on government authentic websites before sharing them with family and friends. Conclusion: Awareness about the virus, modes of spread, good practice, and an optimistic attitude is the prime requisite to curb the spread and to avoid the impending severity anticipating the second wave of the pandemic.

scholarly journals Social consequences of the 2020 regional elections in Indonesia under the covid-19 pandemic

2021 ◽  
Vol 21 (3) ◽  
pp. 536-542
Author(s):  
V. L. Muzykant ◽  
M. A. Muqsith
Keyword(s):  
Social Media ◽  
Public Sphere ◽  
Public Space ◽  
Social Life ◽  
Political Activism ◽  
Social Consequences ◽  
The Political ◽  
The Social ◽  
The Government ◽  
Regional Elections

The article considers the relationship between the 2020 regional elections in Indonesia under the covid-19 pandemic, public space, and political activism in the social media. The covid-19 pandemic has changed the social, political and cultural fabric of the contemporary world. First, the covid-19 threatened the countrys healthcare system, then it affected other aspects of social life, including the political sphere. The pandemic has been exacerbated by the spread of misinformation about the covid-19, which is also known as the infodemic. Thus, the covid-19 pandemic influenced the choice of holding elections or delaying it until the situation is under control. The development of the social media encourages political activism in the political public sphere and makes it more diverse in the sphere of egalitarianism. The political public sphere becomes increasingly dynamic and critical to various policies. Indonesia did not postpone the 2020 regional elections under the covid-19 crisis. According to the health protocol, this decision had its pros and cons in the digital space. The authors show that political activists in the social media called for prioritizing health rather than the process of democratization through elections, while the government supporters insisted on having elections even in the covid-19 pandemic situation. Finally, the 2020 regional elections were held but were followed by various incidents. The question is whether the governments argument to hold elections under the covid-19 pandemic was reasonable or, on the contrary, contributed to the wider spread of the covid-19 in Indonesia. Deliberative democracy should consider civil participation as the main pillar of the political system, which is relevant for the new social reality as based on the new social media technologies.

scholarly journals Mathematical Modelling the Impact Evaluation of Lockdown on Infection Dynamics of COVID-19 in Italy.

2020 ◽  
Author(s):  
Daniyar Yergesh ◽  
Shirali Kadyrov ◽  
Hayot Saydaliev ◽  
Alibek Orynbassar
Keyword(s):  
Policy Implementation ◽  
Impact Evaluation ◽  
Infection Dynamics ◽  
The Social ◽  
The World ◽  
Small Wave ◽  
Before And After ◽  
The Government ◽  
The Impact ◽  
Second Wave

The Severe Acute Respiratory Syndrome Coronavirus 2 (SARSCoV-2), the cause of the coronavirus disease-2019 (COVID-19), within months of emergence from Wuhan, China, has rapidly spread, exacting a devastating human toll across around the world reaching the pandemic stage at the the beginning of March 2020. Thus, COVID-19s daily increasing cases and deaths have led to worldwide lockdown, quarantine and some restrictions. Covid-19 epidemic in Italy started as a small wave of 2 infected cases on January 31. It was followed by a bigger wave mainly from local transmissions reported in 6387 cases on March 8. It caused the government to impose a lockdown on 8 March to the whole country as a way to suppress the pandemic. This study aims to evaluate the impact of the lockdown and awareness dynamics on infection in Italy over the period of January 31 to July 17 and how the impact varies across different lockdown scenarios in both periods before and after implementation of the lockdown policy. The findings SEIR reveal that implementation lockdown has minimised the social distancing flattening the curve. The infections associated with COVID-19 decreases with quarantine initially then easing lockdown will not cause further increasing transmission until a certain period which is explained by public high awareness. Completely removing lockdown may lead to sharp transmission second wave. Policy implementation and limitation of the study were evaluated at the end of the paper. Keywords COVID-19 - Lockdown - Epidemic model - SEIR - Awareness - Dynamical systems.

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