Modelling trust formation in health information contexts

This study explores trust formation in the context of health information. Trust as an interpersonal notion, when formed in a vulnerable state, is a response or belief about how the trusted will behave towards the trustor. This study focuses on the process of assessing the trustworthiness of information, in a dependency state of information need, through the identification of the many factors influencing this assessment. A set of propositions are developed to suggest the criteria by which trustworthiness is assessed as well as the factors that influence these judgements. The proposed model is tested in a large-scale survey using a trust inventory with factor analysis to explore the constructs of trust formation. Structural equation modelling is used to explore the relationship among the identified criteria and their influencing factors. The resulting framework contributes to the understanding of trust formation in digital information contexts on the criteria of usefulness and credibility and further research into the influencing factors is recommended

Students' trust judgements in online health information seeking

As one of the most active groups of Internet users, students and other young people are active users of digital health information. Yet, research into young people’s evaluation of health information is limited, and no previous studies have focused on trust formation. In addition, prior studies on adults’ use of digital information do not reach a consensus regarding the key factors in trust formation. This study seeks to address this gap. A questionnaire-based survey was used to collect data from undergraduate students studying a variety of disciplines in one UK university. The Trust in Online Health Information Scale is proposed, and it includes the following dimensions: authority, style, content, usefulness, brand, ease of use, recommendation, credibility, and verification. In addition, inspection of responses to specific items/questions provides further insights into aspects of the information that were of specific importance in influencing trust judgements

Computational fact checking from knowledge networks

Traditional fact checking by expert journalists cannot keep up with the enormous volume of information that is now generated online. Computational fact checking may significantly enhance our ability to evaluate the veracity of dubious information. Here we show that the complexities of human fact checking can be approximated quite well by finding the shortest path between concept nodes under properly defined semantic proximity metrics on knowledge graphs. Framed as a network problem this approach is feasible with efficient computational techniques. We evaluate this approach by examining tens of thousands of claims related to history, entertainment, geography, and biographical information using a public knowledge graph extracted from Wikipedia. Statements independently known to be true consistently receive higher support via our method than do false ones. These findings represent a significant step toward scalable computational fact-checking methods that may one day mitigate the spread of harmful misinformation

Mapping recent information behavior research: an analysis of co-authorship and cocitation networks

There has been an increase in research published on information behavior in recent years, and this has been accompanied by an increase in its diversity and interaction with other fields, particularly information retrieval (HR). The aims of this study are to determine which researchers have contributed to producing the current body of knowledge on this subject, and to describe its intellectual basis. A bibliometric and network analysis was applied to authorship and co-authorship as well as citation and co-citation. According to these analyses, there is a small number of authors who can be considered to be the most productive and who publish regularly, and a large number of transient ones. Other findings reveal a marked predominance of theoretical works, some examples of qualitative methodology that originate in other areas of social science, and a high incidence of research focused on the user interaction with information retrieval systems and the information behavior of doctors

Inaugural issue perspectives on Information and Learning Sciences as an integral scholarly Nexus

© 2019, Emerald Publishing Limited. Purpose: The new journal, Information and Learning Sciences, aims to advance the understanding of human inquiry, learning and knowledge building in human design and uses of information systems, e-learning systems and socio-technical system contexts. Design/methodology/approach: Under the new editorial team, advisory board, and reviewer community, the authors aim to develop and provide an established and rigorous space for scholarly development that explores phenomena at the intersections of these two fields of inquiry. The editorial advisory board brings together over 70 leading international scholars who are evenly divided between and across these two disciplines. Findings: To chart the course for the journal’s scope and mission and set a standard for quality, the editorial team decided to launch with an inaugural issue of eight articles comprising mainly of theoretical syntheses and editorial essays, alongside three works that report empirical study research findings as exemplars. Authors were chosen by the editorial team based on their known thought leadership at this intersection, and the articles underwent a single-blind review process with a period of revisions. All articles and issues moving forward will be double-blind peer reviewed under both fields’ expected norms and standards of rigorous editorial excellence. The authors invite all interested experts and experts-in-development in our two disciplines, to submit work and volunteer as reviewers in these pursuits. The authors present a brief summary narrative discussing a selection of four recent areas of interdisciplinary research out of which the journal has emerged. The authors then describe each of the special issue articles contributed by our generous invited authors. Originality/value: The authors enthusiastically and warmly invite continued engagement along these lines in the journal’s pages, and also welcome related, and wholly contrary points of view, and points of departure that may build upon or debate some of the themes we raise in this introduction and inaugural issue

What Can Task Teach Us About Query Reformulations?

International audienceA significant amount of prior research has been devoted to understanding query reformulations. The majority of these works rely on time-based sessions which are sequences of contiguous queries segmented using time threshold on users’ activities. However, queries are generally issued by users having in mind a particular task, and time-based sessions unfortunately fail in revealing such tasks. In this paper, we are interested in revealing in which extent time-based sessions vs. task-based sessions represent significantly different background contexts to be used in the perspective of better understanding users’ query reformulations. Using insights from large-scale search logs, our findings clearly show that task is an additional relevant search unit that helps better understanding user’s query reformulation patterns and predicting the next user’s query. The findings from our analyses provide potential implications for model design of task-based search engines