Privacy and Security Concerns Associated with MHealth Technologies: A Social Media Mining Perspective

mHealth technologies seek to improve personal wellness; however, there are stillsignificant privacy and security challenges. With social networking sites serving as lens through which public sentiments and perspectives can be easily accessed, little has been done to investigate the privacy and security concerns of users, associated with mHealth technologies, through social media mining. Therefore, this study investigated various privacy and security concerns conveyed by social media users, in relation to the use of mHealth wearable technologies, using text mining and grounded theory. In addition, the study examined the general sentiments toward mHealth privacy and security related issues, while unearthing how the various issues have evolved over time. Our target social media platform for data collection was the microblogging platform Twitter, which was accessed through Brandwatch providing access to the “Twitter firehose” to extract English tweets. Triangulation was conducted on a representative sample to confirm the results of the Latent Dirichlet Allocation (LDA) Topic Modeling using manual coding through ATLAS.ti. By using the grounded theory analysis methodology, we developed the D-MIT Emergent Theoretical Model which explains that the concerns of users can be categorized as relating to data management, data invasion, or technical safety issues. This model claims that issues affecting data management of mHealth users through the misuse of their data by entities such as wearable companies and other third-party applications, negatively impact their adoption of these devices. Also, concerns of data invasion via real-time data, security breaches, and data surveillance inhibit the adoption of mHealth wearables, which is further impacted by technical safety issues. Further, when users perceived that they do not have full control over their wearables or patient applications, then their acceptance of these mHealth technologies is diminished. While a lack of data and privacy protection policies contribute negatively to users’ adoption of these devices, it also plays a pivotal role in the data management issues presented in this emergent model. Therefore, the importance of having robust legal and policy frameworks that can support mHealth users is desired. Theoretically, the results support the literature on user acceptance of mHealth wearables. These findings were compared with extant literature, and confirmations found across several studies. Further, the results show that over time, mHealth users are still concerned about areas such as security breaches, real-time data invasion, surveillance, and how companies use the data collected from these devices. The findings reveal that more than 75% of the posts analyzed were categorized as depicting anger, fear, or demonstrating levels of disgust. Additionally, 70% of the posts exhibited negative sentiments, whereas 26% were positive, which indicates that users are ambivalent concerning privacy and security, notwithstanding mentions of privacy or security issues in their posts

Discovering mHealth Users’ Privacy and Security Concerns through Social Media Mining

The purpose of this study is to explore the various privacy and security concerns conveyed by social media users in relation to the use of mHealth wearable technologies, using Grounded Theory and Text Mining methodologies. The results of the emerging theory explain that the concerns of users can be categorized as relating to data management, data surveillance, data invasion, technical safety, or legal & policy issues. The results show that over time, mHealth users are still concerned about areas such as security breaches, real-time data invasion, surveillance, and how companies use the data collected from these devices. Further, the results from the emotion and sentiment analyses revealed that users generally exhibited anger and fear, and sentiments that were negatively expressed. Theoretically, the results also support the literature on user acceptance of mHealth wearables as influenced by the distrust of companies and their utilization of personally harvested data

The effect of privacy policies on information sharing behavior on social networks: A Systematic Literature Review

Online social networks (OSN) such as Facebook and Instagram have dramatically changed the way people operate. It, however, raises specific privacy concerns due to their inherent handling of personal data. The paper highlights the privacy concerns associated with OSN, strategies to protect the users’ privacy, and finally the overall effect of privacy policies on information sharing behavior on OSN. We examined a sample of 51 full papers that explore privacy concerns in OSN, strategies to protect users’ privacy, and the effects of privacy policies on the users’ information sharing behavior. The overall findings disclosed that users are concerned about their identity being stolen, and how third-party applications use their information. However, privacy policies do not have a direct impact on the information sharing behavior of OSN users. The findings help researchers and practitioners better understand the impact of privacy concern on users\u27 information sharing behaviors on OSN

Discovering mHealth Users’ Privacy and Security Concerns through Social Media Mining

The purpose of this study is to explore the various privacy and security concerns conveyed by social media users in relation to the use of mHealth wearable technologies, using Grounded Theory and Text Mining methodologies. The results of the emerging theory explain that the concerns of users can be categorized as relating to data management, data surveillance, data invasion, technical safety, or legal & policy issues. The results show that over time, mHealth users are still concerned about areas such as security breaches, real-time data invasion, surveillance, and how companies use the data collected from these devices. Further, the results from the emotion and sentiment analyses revealed that users generally exhibited anger and fear, and sentiments that were negatively expressed. Theoretically, the results also support the literature on user acceptance of mHealth wearables as influenced by the distrust of companies and their utilization of personally harvested data

Privacy and Security Concerns Associated with mHealth Technologies: A Computational Social Science Approach

mHealth technologies seek to improve personal wellness; however, there are still significant privacy and security challenges. The purpose of this study is to analyze tweets through social media mining to understand user-reported concerns associated with mHealth devices. Triangulation was conducted on a representative sample to confirm the results of the topic modeling using manual coding. The results of the emotion analysis showed 67% of the posts were largely associated with anger and fear, while 71% revealed an overall negative sentiment. The findings demonstrate the viability of leveraging computational techniques to understand the social phenomenon in question and confirm concerns such as accessibility of data, lack of data protection, surveillance, misuse of data, and unclear policies. Further, the results extend existing findings by highlighting critical concerns such as users’ distrust of these mHealth hosting companies and the inherent lack of data control

Privacy and Online Social Networks: A Systematic Literature Review of Concerns, Preservation, and Policies

Background: Social media usage is one of the most popular online activities, but with it comes privacy concerns due to how personal data are handled by these social networking sites. Prior literature aimed at identifying users’ privacy concerns as well as user behavior associated with privacy mitigation strategies and policies. However, OSN users continue to divulge private information online and privacy remains an issue. Accordingly, this review aims to present extant research on this topic, and to highlight any potential research gaps. Method: The paper presents a systematic literature review for the period 2006 - 2021, in which 33 full papers that explored privacy concerns in online social networks (OSN), users’ behavior associated with privacy preservation strategies and OSN privacy policies were examined. Results: The findings indicate that users are concerned about their identity being stolen, the disclosure of sensitive information by third-party applications and through data leakage and the degree of control users have over their data. Strategies such as encryption, authentication, and privacy settings configuration, can be used to address users’ concerns. Users generally do not leverage privacy settings available to them, or read the privacy policies, but will opt to share information based on the benefits to be derived from OSNs. Conclusion: OSN users have specific privacy concerns due primarily to the inherent way in which personal data are handled. Different preservation strategies are available to be used by OSN users. Policies are provided to inform users, however, these policies at times are difficult to read and understand, but studies show that there is no direct effect on the behavior of OSN users. Further research is needed to elucidate the correlation between the relative effectiveness of different privacy preservation strategies and the privacy concerns exhibited by users. Extending the research to comparatively assess different social media sites could help with better awareness of the true influence of privacy policies on user behavior

Insights into non-Fickian solute transport in carbonates

[1] We study and explain the origin of early breakthrough and long tailing plume behavior by simulating solute transport through 3‐D X‐ray images of six different carbonate rock samples, representing geological media with a high degree of pore‐scale complexity. A Stokes solver is employed to compute the flow field, and the particles are then transported along streamlines to represent advection, while the random walk method is used to model diffusion. We compute the propagators (concentration versus displacement) for a range of Peclet numbers (Pe ) and relate it to the velocity distribution obtained directly on the images. There is a very wide distribution of velocity that quantifies the impact of pore structure on transport. In samples with a relatively narrow spread of velocities, transport is characterized by a small immobile concentration peak, representing essentially stagnant portions of the pore space, and a dominant secondary peak of mobile solute moving at approximately the average flow speed. On the other hand, in carbonates with a wider velocity distribution, there is a significant immobile peak concentration and an elongated tail of moving fluid. An increase in Pe , decreasing the relative impact of diffusion, leads to the faster formation of secondary mobile peak(s). This behavior indicates highly anomalous transport. The implications for modeling field‐scale transport are discussed

Reproducibility in the absence of selective reporting: An illustration from large‐scale brain asymmetry research

The problem of poor reproducibility of scientific findings has received much attention over recent years, in a variety of fields including psychology and neuroscience. The problem has been partly attributed to publication bias and unwanted practices such as p‐hacking. Low statistical power in individual studies is also understood to be an important factor. In a recent multisite collaborative study, we mapped brain anatomical left–right asymmetries for regional measures of surface area and cortical thickness, in 99 MRI datasets from around the world, for a total of over 17,000 participants. In the present study, we revisited these hemispheric effects from the perspective of reproducibility. Within each dataset, we considered that an effect had been reproduced when it matched the meta‐analytic effect from the 98 other datasets, in terms of effect direction and significance threshold. In this sense, the results within each dataset were viewed as coming from separate studies in an “ideal publishing environment,” that is, free from selective reporting and p hacking. We found an average reproducibility rate of 63.2% (SD = 22.9%, min = 22.2%, max = 97.0%). As expected, reproducibility was higher for larger effects and in larger datasets. Reproducibility was not obviously related to the age of participants, scanner field strength, FreeSurfer software version, cortical regional measurement reliability, or regional size. These findings constitute an empirical illustration of reproducibility in the absence of publication bias or p hacking, when assessing realistic biological effects in heterogeneous neuroscience data, and given typically‐used sample sizes

Peripheral rods: a specialized developmental cell type in Myxococcus xanthus

In response to nutrient deprivation, the ubiquitous Gram-negative soil bacterium Myxococcus xanthus undergoes a well-characterized developmental response, resulting in the formation of a multicellular fruiting body. The center of the fruiting body consists of myxospores; surrounding this structure are rod-shaped peripheral cells. Unlike spores, the peripheral rods are a metabolically active cell type that inhabits nutrient-deprived environments. The survival characteristics exhibited by peripheral rods, protection from oxidative stress and heat shock, are common survival characteristics exhibited by cells in stationary phase including modifications to morphology and metabolism. Vegetative M. xanthus cells undergo a number of physiological changes during the transition into stationary phase similar to other proteobacteria. In M. xanthus, stationary-phase cells are not considered a component of the developmental response and occur when cells are grown on nutrient-rich plates or in dispersed aqueous media. However, this cell type is not routinely studied and little of its physiology is known. Similarities between these two stress-induced cell types led to the question of whether peripheral rods are actually a distinct developmental cell type or simply cells in stationary phase. In this study, we examine the transcriptome of peripheral rods and its relationship to development. This work demonstrates that peripheral rods are in fact a distinct developmentally differentiated cell type. Although peripheral rods and stationary phase cells display similar characteristics, each transcriptomic pattern is unique and quite different from that of any other M. xanthus cell type