In recent years, social networking sites have spread rapidly, raising new issues in terms of privacy and self-disclosure online. For a better understanding of how privacy issues determine self-disclosure, a model which includes privacy awareness, privacy social norms, privacy policy, privacy control, privacy value, privacy concerns and self-disclosure was built. A total of 661 respondents participated in an online survey and a structural equation modeling was used to evaluate the model. The findings indicated a significant relationship between privacy value/privacy concerns and self-disclosure, privacy awareness and privacy concerns/self-disclosure, privacy social norms and privacy value/self-disclosure, privacy policy and privacy value/privacy concerns/self-disclosure, privacy control and privacy value/privacy concerns. The model from the study should contribute new knowledge concerning privacy issues and their shaping of self-disclosure on social networking sites. It could also help networking sites service providers understand how to encourage users to disclose more information.
COBISS.SI-ID: 18341142
This article presents a survey of genetic algorithms that are designed for solving multi depot vehicle routing problem. In this context, most of the articles focus on different genetic approaches, methods and operators, commonly used in practical applications to solve this well-known and researched problem. Besides providing an up-to-date overview of the research in the field, the results of a thorough experiment are presented and discussed, which evaluated the efficiency of different existing genetic methods on standard benchmark problems in detail. In this manner, the insights into strengths and weaknesses of specific methods, operators and settings are presented, which should help researchers and practitioners to optimize their solutions in further studies done with the similar type of the problem in mind. Finally, genetic algorithm based solutions are compared with other existing approaches, both exact and heuristic, for solving this same problem.
COBISS.SI-ID: 18347286
Background: Patterns in general consumer online search logs have been used to monitor health conditions and to predict health-related activities, but the multiple contexts within which consumers perform online searches make significant associations difficult to interpret. Physician information-seeking behavior has typically been analyzed through survey-based approaches and literature reviews. Activity logs from health care professionals using online medical information resources are thus a valuable yet relatively untapped resource for large-scale medical surveillance. Objective: To analyze health care professionals% information-seeking behavior and assess the feasibility of measuring drug-safety alert response from the usage logs of an online medical information resource. Methods: Using two years (2011-2012) of usage logs from UpToDate, we measured the volume of searches related to medical conditions with significant burden in the United States, as well as the seasonal distribution of those searches. We quantified the relationship between searches and resulting page views. Using a large collection of online mainstream media articles and Web log posts we also characterized the uptake of a Food and Drug Administration (FDA) alert via changes in UpToDate search activity compared with general online media activity related to the subject of the alert. Results: Diseases and symptoms dominate UpToDate searches. Some searches result in page views of only short duration, while others consistently result in longer-than-average page views. The response to an FDA alert for Celexa, characterized by a change in UpToDate search activity, differed considerably from general online media activity. Changes in search activity appeared later and persisted longer in UpToDate logs. The volume of searches and page view durations related to Celexa before the alert also differed from those after the alert. Conclusions: Understanding the information-seeking behavior associated with online evidence sources can offer insight into the information needs of health professionals and enable large-scale medical surveillance. Our Web log mining approach has the potential to monitor responses to FDA alerts at a national level. Our findings can also inform the design and content of evidence-based medical information resources such as UpToDate
COBISS.SI-ID: 2145444
A new information literacy test (ILT) for higher education was developed, tested, and validated. The ILT contains 40 multiple-choice questions (available in Appendix) with four possible answers and follows the recommendations of information literacy (IL) standards for higher education. It assesses different levels of thinking skills and is intended to be freely available to educators, librarians, and higher education managers, as well as being applicable internationally for study programs in all scientific disciplines. Testing of the ILT was performed on a group of 536 university students. The overall test analysis confirmed the ILT reliability and discrimination power as appropriate (Cronbach's alpha 0.74; Ferguson's delta 0.97). The students' average overall achievement was 66%, and IL increased with the year of study. The students were less successful in advanced databasesearch strategies, which require a combination of knowledge, comprehension, and logic, and in topics related to intellectual property and ethics. A group of 163 students who took a second ILT assessment after participating in an IL-specific study course achieved an average posttest score of 78.6%, implying an average IL increase of 13.1%, with most significant improvements in advanced search strategies (23.7%), and in intellectual property and ethics (12.8%).
COBISS.SI-ID: 1585756
This research aims to explore the field of mobile data services and discover factors that influence their adoption. It constitutes a systematic literature review of 80 primary studies, with the goal of researching the field of acceptance of mobile data services. The review focuses on a broad field of mobile services to ensure the most valid results. In addition, it also focuses on the main mobile service categories to discover which of the acceptance models and factors are most suited for the analysis of each services category. It provides an aggregation of the most used factors, with their definitions and the extent of their usage. Furthermore, it tries to establish a basis for future works by aggregating the relations between factors and providing the rate of their significance. Additionally, it analyses the relation behaviour between different mobile service categories and tries to extract factors that could be limited to certain mobile services. Finally, based on the data retrieved from the literature, the review tries to propose a generic model for each of the mobile service categories in order to help researchers in future mobile services research.
COBISS.SI-ID: 18855190