Dataset Information

ISBP: Understanding the Security Rule of Users' Information-Sharing Behaviors in Partnership.

ABSTRACT: The rapid growth of social network data has given rise to high security awareness among users, especially when they exchange and share their personal information. However, because users have different feelings about sharing their information, they are often puzzled about who their partners for exchanging information can be and what information they can share. Is it possible to assist users in forming a partnership network in which they can exchange and share information with little worry? We propose a modified information sharing behavior prediction (ISBP) model that can help in understanding the underlying rules by which users share their information with partners in light of three common aspects: what types of items users are likely to share, what characteristics of users make them likely to share information, and what features of users' sharing behavior are easy to predict. This model is applied with machine learning techniques in WEKA to predict users' decisions pertaining to information sharing behavior and form them into trustable partnership networks by learning their features. In the experiment section, by using two real-life datasets consisting of citizens' sharing behavior, we identify the effect of highly sensitive requests on sharing behavior adjacent to individual variables: the younger participants' partners are more difficult to predict than those of the older participants, whereas the partners of people who are not computer majors are easier to predict than those of people who are computer majors. Based on these findings, we believe that it is necessary and feasible to offer users personalized suggestions on information sharing decisions, and this is pioneering work that could benefit college researchers focusing on user-centric strategies and website owners who want to collect more user information without raising their privacy awareness or losing their trustworthiness.

SUBMITTER: Wu H

PROVIDER: S-EPMC4780783 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

ISBP: Understanding the Security Rule of Users' Information-Sharing Behaviors in Partnership.

Wu Hongchen H Wang Xinjun X

PloS one 20160307 3

The rapid growth of social network data has given rise to high security awareness among users, especially when they exchange and share their personal information. However, because users have different feelings about sharing their information, they are often puzzled about who their partners for exchanging information can be and what information they can share. Is it possible to assist users in forming a partnership network in which they can exchange and share information with little worry? We pro ...[more]

PMID: 26950064

Similar Datasets

Project description:BackgroundSparse relative effectiveness evidence is a frequent problem in Health Technology Assessment (HTA). Where evidence directly pertaining to the decision problem is sparse, it may be feasible to expand the evidence-base to include studies that relate to the decision problem only indirectly: for instance, when there is no evidence on a comparator, evidence on other treatments of the same molecular class could be used; similarly, a decision on children may borrow-strength from evidence on adults. Usually, in HTA, such indirect evidence is either included by ignoring any differences ('lumping') or not included at all ('splitting'). However, a range of more sophisticated methods exists, primarily in the biostatistics literature. The objective of this study is to identify and classify the breadth of the available information-sharing methods.MethodsForwards and backwards citation-mining techniques were used on a set of seminal papers on the topic of information-sharing. Papers were included if they specified (network) meta-analytic methods for combining information from distinct populations, interventions, outcomes or study-designs.ResultsOverall, 89 papers were included. A plethora of evidence synthesis methods have been used for information-sharing. Most papers (n=79) described methods that shared information on relative treatment effects. Amongst these, there was a strong emphasis on methods for information-sharing across multiple outcomes (n=42) and treatments (n=25), with fewer papers focusing on study-designs (n=23) or populations (n=8). We categorise and discuss the methods under four 'core' relationships of information-sharing: functional, exchangeability-based, prior-based and multivariate relationships, and explain the assumptions made within each of these core approaches.ConclusionsThis study highlights the range of information-sharing methods available. These methods often impose more moderate assumptions than lumping or splitting. Hence, the degree of information-sharing that they impose could potentially be considered more appropriate. Our identification of four 'core' methods of information-sharing allows for an improved understanding of the assumptions underpinning the different methods. Further research is required to understand how the methods differ in terms of the strength of sharing they impose and the implications of this for health care decisions.

Project description:BACKGROUND:As the US health care system is embracing data-driven care, personal health information (PHI) has become a valuable resource for various health care stakeholders. In particularly, health consumers are expected to autonomously manage and share PHI with their health care partners. To date, there have been mixed views on the factors influencing individuals' health data-sharing behaviors. OBJECTIVE:This study aimed to identify a key factor to better understand health information sharing behavior from a health consumer's perspective. We focused on daily settings, wherein health data-sharing behavior becomes a part of individuals' daily information management activities. Considering the similarity between health and finance information management, we explicitly examined whether health consumers' daily habit of similar data sharing from the financial domain affects their PHI-sharing behaviors in various scenarios. METHODS:A Web-based survey was administered to US health consumers who have access to and experience in using the internet. We collected individual health consumers' intention to share PHI under varying contexts, habit of financial information management (operationalized as internet banking [IB] use in this paper), and the demographic information from the cross-sectional Web-based survey. To isolate the effect of daily IB on PHI-sharing behaviors in everyday contexts, propensity score matching was used to estimate the average treatment effect (ATE) and average treatment effect on the treated (ATET) regarding IB use. We balanced the treatment and control groups using caliper matching based on the observed confounding variables (ie, gender, income, health status, and access to primary care provider), all of which resulted in a minimal level of bias between unmatched and matched samples (bias <5%). RESULTS:A total of 339 responses were obtained from a cross-sectional Web-based survey. The ATET results showed that in terms of sharing contents, those who used IB daily were more likely to share general information (P=.01), current information (P=.003), and entire data (P=.04). Regarding occasions for sharing occasions, IB users were prone to share their information in all cases (P=.02). With regard to sharing recipients, daily IB users were more willing to share their personal health data with stakeholders who were not directly involved in their care, such as health administrators (P=.05). These results were qualitatively similar to the ATE results. CONCLUSIONS:This study examined whether daily management of similar information (ie, personal financial information) changes health consumers' PHI-sharing behavior under varying sharing conditions. We demonstrated that daily financial information management can encourage health information sharing to a much broader extent, in several instances, and with many stakeholders. We call for more attention to this unobserved daily habit driven by the use of various nonhealth technologies, all of which can implicitly affect patterns and the extent of individuals' PHI-sharing behaviors.

Dataset Information

ISBP: Understanding the Security Rule of Users' Information-Sharing Behaviors in Partnership.

Publications

ISBP: Understanding the Security Rule of Users' Information-Sharing Behaviors in Partnership.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets