scholarly journals Can Health 2.0 Address Critical Healthcare Challenges? Insights from the Case of How Online Social Networks Can Assist in Combatting the Obesity Epidemic

Author(s):  
Janine Hacker ◽  
Nilmini Wickramasinghe ◽  
Carolin Durst

One of the serious concerns in healthcare in this 21st century is obesity. While the causes of obesity are multifaceted, social networks have been identified as one of the most important dimensions of people's social environment that may influence the adoption of many behaviours, including health-promoting behaviours. In this article, we examine the possibility of harnessing the appeal of online social networks to address the obesity epidemic currently plaguing society. Specifically, a design science research methodology is adopted to design, implement and test the Health 2.0 application called “Calorie Cruncher”. The application is designed specifically to explore the influence of online social networks on individual’s health-related behaviour. In this regard, pilot data collected based on qualitative interviews indicate that online social networks may influence health-related behaviours in several ways. Firstly, they can influence people’s norms and value system that have an impact on their health-related behaviours. Secondly, social control and pressure of social connections may also shape health-related behaviours, and operate implicitly when people make food selection decisions. Thirdly, social relationships may provide emotional support. Our study has implications for research and practice. From a theoretical perspective, the article inductively identifies three factors that influence specific types of health outcomes in the context of obesity. From a practical perspective, the study underscores the benefits of adopting a design science methodology to design and implement a technology solution for a healthcare issue as well as the key role for online social media to assist with health and wellness management and maintenance.

Author(s):  
Cameron Taylor ◽  
Alexander V. Mantzaris ◽  
Ivan Garibay

Polarization in online social networks has gathered a significant amount of attention in the research community and in the public sphere due to stark disagreements with millions of participants in topics surrounding politics, climate, the economy and other areas where an agreement is required. There are multiple approaches to investigating the scenarios in which polarization occurs and given that polarization is not a new phenomenon but that its virality may be supported by the low cost and latency messaging offered by online social media platforms; an investigation into the intrinsic dynamics of online opinion evolution is presented for complete networks. Extending a model which utilizes the Binary Voter Model (BVM) to examine the effect of the degree of freedom for selecting contacts based upon homophily, simulations show that different opinions are reinforced for a period of time when users have a greater range of choice for association. The facility of discussion threads and groups formed upon common views further delays the rate in which a consensus can form between all members of the network. This can temporarily incubate members from interacting with those who can present an alternative opinion where a voter model would then proceed to produce a homogeneous opinion based upon pairwise interactions.


2022 ◽  
Author(s):  
Dimiter Toshkov

Attitudes towards vaccination have proven to be a major factor determining the pace of national COVID-19 vaccination campaigns throughout 2021. In Europe, large differences in levels of vaccine hesitancy and refusal have emerged, which are highly correlated with actual vaccination levels. This article explores attitudes towards COVID-19 vaccination in 27 European countries based on data from Eurobarometer (May 2021). The statistical analyses show that demographic variables have complex effects on vaccine hesitancy and refusal. Trust in different sources of health-related information has significant effects as well, with people who trust the Internet, social networks and ‘people around’ in particular being much more likely to express vaccine skepticism. As expected, beliefs in the safety and effectiveness of vaccines have large predictive power, but – more interestingly – net of these two beliefs, the effects of trust in Internet, online social networks and people as sources of health information are significantly reduced. This study shows that the effects of demographic, belief-related and other individual-level factors on vaccine hesitancy and refusal are context-specific. Yet, explanations of the differences in vaccine hesitancy across Europe need to consider primarily different levels of trust and vaccine-relevant beliefs, and to a lesser extent their differential effects.


2019 ◽  
Vol 8 (4) ◽  
pp. 471-496
Author(s):  
Isabelle Freiling

Although online social networks (OSN) facilitate the distribution of misinformation, one way of reducing the spread of false information in OSN is for users to detect it. Building on the framework of how audiences act to authenticate information, this study provides a user perspective on which strategies people use in evaluating information in OSN. In 15 qualitative interviews, participants were asked to think aloud while evaluating whether the content of posts from their own newsfeeds and of interviewer-supplied posts was true or false. Their answers were analyzed to determine which evaluation strategies they used. Analyzing participants’ thoughts as they evaluate information is more reliable than directly asking participants which strategies they think they use. Results show that users’ strategies in information evaluation are searching for more information, knowledge of account or content carries the most weight, and every detail needs to fit. A comparison of strategy usage for posts from befriended versus unknown personal accounts as well as for posts from followed news outlets versus not followed news outlets shows that for posts from followed news outlets, knowledge of the account was the most-used strategy followed by knowledge of the content. For other types of posts, strategy usage varied more widely and depended on each post. This highlights the importance and possible higher ecological validity of research on posts from news outlets that users actually follow, as users’ experiences with previous posts seem to play a major role in how they go about evaluating information in new posts.


Author(s):  
Dan J. Kim ◽  
T. Andrew Yang ◽  
Ninad Naik

Recently, Web 2.0 applications such as blogs, wikis (e.g., Wikipedia), social networks (e.g., MySpace), 3-D virtual worlds (e.g., Second Life), and so forth, have created fresh interest in the Internet as a new medium of social interactions and human collaborative activities. Since the emergence of Web 2.0 applications, Web services that support online human activities have gained an unprecedented boost. There have been conceptual studies on and overviews of individual Web 2.0 applications like blogs, online social networks, and so forth, but there has not been a study to date which provides a theoretical perspective on the online human activity networks (OnHANs) formed by these Web 2.0 applications. In this chapter, we classify various forms of OnHANs focusing on their social and business purposes, analyzing the core components of representative OnHANs from the angle of the activity theory, and finally providing a theoretical discussion concerning how OnHANs provide values to the individuals and the organizations involved in those activities.


2021 ◽  
Vol 17 (4) ◽  
pp. 92-116
Author(s):  
Syed Shah Alam ◽  
Chieh-Yu Lin ◽  
Mohd Helmi Ali ◽  
Nor Asiah Omar ◽  
Mohammad Masukujjaman

Most businesses have online social media presence; therefore, understanding of working adult's perception on buying through online social networks is vital. The aim of this study is to examine the effect of perceived value, sociability, usability, perceived risk, trust, and e-word-of-mouth on buying intention through online social network sites. The research model for this study was developed based on the literature on information system research. This study adopted convenient sampling of non-probability sampling procedure. Data were collected through self-administered questionnaire, and PLS-based path analysis was used to analyse responses. The findings of the study shows that perceived value, sociability, usability, e-word-of-mouth, attitude, and subjective norm are significant constructs of buying intention through online social networks. This research can serve as a starting point for online shopping research through online social media while encouraging further exploration and integration addition adoption constructs.


Author(s):  
B.Mukunthan Et. al.

: Unlike traditional media social media is populated by unknown individuals who can broadcast whatever they like. This online social media culture is dynamic in its nature and transition to digital media is becoming a trend among people. In upcoming years the use of traditional media will decline, and the increasing use of Online Social Networks(OSNs) blur the actual information of the traditional media. The information generated by the authentic users gives useful information to the general users, on the other hand,Spammers spread irrelevant or misleading information that makes social media a plot for false news. So unwanted text or vulnerable links can be distributed to specific users. These false texts are anonymous and sometimes linked with potential URLs. Due to data restrictions and communication categories, the current systems do not deserve an exact statistical classification for a piece of news. We will study different research papers using various techniques for master training in the prediction and detection of malicious data on social networks online. We tried to find spam tweets from the tweets collected by using Enhanced Random forest classifications and NaiveBayes in this research. To evaluate the work, different validation metrics such as F1-scoring, accurcy and precision values are calculated.


Author(s):  
Cameron E. Taylor ◽  
Alexander V. Mantzaris ◽  
Ivan Garibay

Polarization in online social networks has gathered a significant amount of attention in the research community and in the public sphere due to stark disagreements with millions of participants in topics surrounding politics, climate, the economy and other areas where an agreement is required. There are multiple approaches to investigating the scenarios in which polarization occurs and given that polarization is not a new phenomenon but that its virality may be supported by the low cost and latency messaging offered by online social media platforms; an investigation into the intrinsic dynamics of online opinion evolution is presented for complete networks. Extending a model which utilizes the Binary Voter Model (BVM) to examine the effect of the degree of freedom for selecting contacts based upon homophily, simulations show that different opinions are reinforced for a period of time when users have a greater range of choice for association. The facility of discussion threads and groups formed upon common views further delays the rate in which a consensus can form between all members of the network. This can temporarily incubate members from interacting with those who can present an alternative opinion where a voter model would then proceed to produce a homogeneous opinion based upon pairwise interactions.


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