Privacy concerns and benefits of engagement with social media-enabled apps: A privacy calculus perspective

Jozani, Mohsen; Ayaburi, Emmanuel; Ko, Myung; Choo, Kim‐Kwang Raymond

doi:10.1016/j.chb.2020.106260

Cited by 168 publications

(144 citation statements)

References 85 publications

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“…Recent scandals that have plagued social media and issues with privacy and misinformation may explain these findings. [25][26] Social media sources also were among the least trusted sources of information for survey participants. Similar to findings in other studies, families and friends, coworkers, and medical professionals were a significant source of information about COVID-19, with health care workers being the most trustworthy source.…”

Section: Discussionmentioning

confidence: 99%

Kansans in the Middle of the Pandemic: Risk Perception, Knowledge, Compliance with Preventive Measures, and Primary Sources of Information about COVID-19

Geana¹

2020

kjm

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Introduction. As we conduct this study, the world is in the grasp of a deadly pandemic. In less than six months since its first diagnosis in Wuhan, China, the COVID-19 infectious disease due to the novel coronavirus has infected over 5,000,000 people and claimed over 350,000 lives. In the United States, most of the cases are in large urban settings along the coasts, but the disease is slowly progressing through the mainland. Kansas, with its particular location in the midwest United States, has seen a relatively small number of cases, but these are increasing. The Kansas government took radical measures to prevent the spread of the disease. According to the Health Beliefs Model, an individual’s perception of risk will dictate engagement with preventive behaviors. Knowledge about the disease and preventive measures drive the risk assessment. Knowledge is dependant on the sources of information used. This study explored these metrics in a sample of Kansans living in the times of the COVID-19 pandemic. Methods. A combination of snowball samples and random distribution through social media was used to recruit participants to an online survey. The risk and knowledge instrument was developed and validated by WHO Europe. Data collection lasted 96 hours. Results. The attitudes and behaviors of Kansans concerning COVID-19 were consistent with its location in an area of the country with a relatively lower incidence of the disease. Participants had good knowledge about the disease and preventive measures and were willing to comply with recommendations from local authorities. Conclusion. Localized information sources that cater to the community are often primary, while social media is not a valuable source for information pertinent to COVID-19.

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Section: Discussionmentioning

confidence: 99%

Kansans in the Middle of the Pandemic: Risk Perception, Knowledge, Compliance with Preventive Measures, and Primary Sources of Information about COVID-19

Geana¹

2020

kjm

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“…One of the key reasons for the resistance against the use, download, and adoption of any contact tracing app is due to the potential invasion of personal privacy ( Findlay et al, 2020 ; Meade, 2020 ; Rudgard, 2020 ), which consumers must weigh against the potential benefits for public and also their personal health as with many other technological advances such as electronic health records ( Jozani, Ayaburi, Ko, & Choo, 2020 ; Park & Shin, 2020 ). Indeed, contact tracing apps often require giving away one's movements and possibly (depending on the app or country) medical information, increasing reluctance among the public to download and use these apps.…”

Section: Hypothetical Developmentmentioning

confidence: 99%

Privacy concerns can explain unwillingness to download and use contact tracing apps when COVID-19 concerns are high

Chan¹,

Saqib

2021

Computers in Human Behavior

153

106

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“…In terms of developing the privacy risk model, calculus knowledge should be used because it provides a precise and accurate privacy risk score [ 28 , 29 ]. Users can understand the risks they face based on their usage behaviour.…”

Section: Discussionmentioning

confidence: 99%

A Privacy Preservation Quality of Service (QoS) Model for Data Exposure in Android Smartphone Usage

Bakar

Singh

Shariff

2021

Sensors

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An Android smartphone contains built-in and externally downloaded applications that are used for entertainment, finance, navigation, communication, health and fitness, and so on. The behaviour of granting permissions requested by apps might expose the Android smartphone user to privacy risks. The existing works lack a formalized mathematical model that can quantify user and system applications risks. No multifaceted data collector tool can also be used to monitor the collection of user data and the risk posed by each application. A benchmark of the risk level that alerts the user and distinguishes between acceptable and unacceptable risk levels in Android smartphone user does not exist. Hence, to address privacy risk, a formalized privacy model called PRiMo that uses a tree structure and calculus knowledge is proposed. An App-sensor Mobile Data Collector (AMoDaC) is developed and implemented in real life to analyse user data accessed by mobile applications through the permissions granted and the risks involved. A benchmark is proposed by comparing the proposed PRiMo outcome with the existing available testing metrics. The results show that Tools & Utility/Productivity applications posed the highest risk as compared to other categories of applications. Furthermore, 29 users faced low and acceptable risk, while two users faced medium risk. According to the benchmark proposed, users who faced risks below 25% are considered as safe. The effectiveness and accuracy of the proposed work is 96.8%.

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Privacy concerns and benefits of engagement with social media-enabled apps: A privacy calculus perspective

Cited by 168 publications

References 85 publications

Kansans in the Middle of the Pandemic: Risk Perception, Knowledge, Compliance with Preventive Measures, and Primary Sources of Information about COVID-19

Kansans in the Middle of the Pandemic: Risk Perception, Knowledge, Compliance with Preventive Measures, and Primary Sources of Information about COVID-19

Privacy concerns can explain unwillingness to download and use contact tracing apps when COVID-19 concerns are high

A Privacy Preservation Quality of Service (QoS) Model for Data Exposure in Android Smartphone Usage

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