User comments allow 'annotative reporting' by embedding users' viewpoints within an article's context, providing readers with additional information to form opinions, which can potentially enhance ...deliberative processes. But are these the only reasons why people comment on online news and read these comments? This study examines factors that motivate, or demotivate and constrict, such participation by surveying nearly 650 commenters, lurkers, and non-users in Germany. From a normative perspective, the results are ambivalent. The results show that commenters are driven by social-interactive motives to participate in journalism, and to discuss with other users. However, the data suggest that commenters do not obtain cognitive gratifications to the desired extent. Presumably, their exchange is socially and not deliberatively motivated. Reading comments is fuelled by both cognitive and entertainment motives, but regression analyses show that the entertainment dimension − a dimension that is not usually considered to be linked to deliberation processes − is the more stable one. A low standard of discussions not only increases the frequency at which comments are read, but also reduces lurkers' satisfaction. Similarly, non-users are even more frustrated by the low quality of discussions. They consider such participation activities to be a waste of time, and are not willing to register.
User-based evaluation by end users is an essential step in designing useful interfaces. Inspection methods can offer an alternate approach when end-user recruitment is problematic. A Learning ...Designers' usability scholarship could offer usability evaluation expertise adjunct to multidisciplinary teams in academic settings. The feasibility of Learning Designers as 'expert evaluators' is assessed within this study. Two groups, healthcare professionals and Learning Designers, applied a hybrid evaluation method to generate usability feedback from a palliative care toolkit prototype. Expert data were compared to end-user errors detected from usability testing. Interface errors were categorised, meta-aggregated and severity calculated. The analysis found that reviewers detected
= 333 errors, with
= 167 uniquely occurring within the interface. Learning Designers identified errors at greater frequencies (60.66% total interface errors, mean (M) = 28.86 per expert) than other evaluator groups (healthcare professionals 23.12%, M = 19.25 and end users 16.22%, M = 9.0). Patterns in severity and error types were also observed between reviewer groups. The findings suggest that Learning Designers are skilled in detecting interface errors, which benefits developers assessing usability when access to end users is limited. Whilst not offering rich narrative feedback generated by user-based evaluations, Learning Designers complement healthcare professionals' content-specific knowledge as a 'composite expert reviewer' with the ability to generate meaningful feedback to shape digital health interfaces.
•Explores perceived safety of AVs in the public as they might share the road with AVs.•Stated preference data collected from Phoenix, Arizona, United States.•Cycling near AVs perceived as least safe, ...followed by walking and driving near AVs.•Experience and familiarity with AV tests positively correlated with perceived safety.•Those aware of crashes and other safety-related incidents felt less safe about AVs.
Introduction: While improved safety is a highly cited potential benefit of autonomous vehicles (AVs), at the same time a frequently cited concern is the new safety challenges that AVs introduce. The literature lacks a rigorous exploration of the safety perceptions of road users who will interact with AVs, including vulnerable road users. Addressing this gap is essential because the successful integration of AVs into transportation systems hinges on an understanding of how all road users will react to their presence. Methods: A stated preference survey of the Phoenix, Arizona, metropolitan statistical area (Phoenix MSA) was conducted in July 2018. A series of ordered probit models was estimated to analyze the survey responses and identify differences between various population groups with respect to the perceived safety of driving, cycling, and walking near AVs. Results: Greater exposure to and awareness of AVs are not uniformly associated with increases in perceived safety. Various attitudinal factors, level of AV automation, and other intrinsic and extrinsic factors are related to safety perceptions of driving, walking, and cycling near AVs. Socioeconomic and demographic characteristics, such as gender, age, income, employment, and automobile usage and ownership, have various relationships with perceived safety. Conclusions: Cycling near an AV was perceived as the least safe activity, followed by walking and then driving near an AV. Both similarities and differences were observed among the factors associated with the perceived safety of different travel alternatives. Practical Applications: Public perception will guide the development and adoption of AVs directly and indirectly. To help maintain control of public perception, transportation planners, decision makers, and other stakeholders should consider more deliberate and targeted messaging to address the concerns of different road users. In addition, more careful pilot testing and more direct attention to vulnerable road users may help avoid a backlash that could delay the rollout of this technology.
•We first analyze the shortages of the existing similarity measures in collaborative filtering.•And second, we propose a new user similarity model to overcome these drawbacks.•We compare the new ...model with many other similarity measures on two real data sets.•Experiments show that the new model can reach better performance than many existing similarity measures.
Collaborative filtering has become one of the most used approaches to provide personalized services for users. The key of this approach is to find similar users or items using user-item rating matrix so that the system can show recommendations for users. However, most approaches related to this approach are based on similarity algorithms, such as cosine, Pearson correlation coefficient, and mean squared difference. These methods are not much effective, especially in the cold user conditions. This paper presents a new user similarity model to improve the recommendation performance when only few ratings are available to calculate the similarities for each user. The model not only considers the local context information of user ratings, but also the global preference of user behavior. Experiments on three real data sets are implemented and compared with many state-of-the-art similarity measures. The results show the superiority of the new similarity model in recommended performance.
PurposeThe purpose of this study is to analyse and discuss the influencing factors of user experience in university mobile libraries and the improvement path of user experience in the context of ...mobile learning.Design/methodology/approachThe study adopted the grounded theory research method, and the sample included 28 students from five universities, with mobile libraries as the research objects and semi-structured interview as data acquisition method. A step-by-step coding analysis of the original interview materials was conducted, which comprehensively identified the main concerns and problems encountered by users of the university mobile library apps especially in the mobile learning behaviour mode, and then a theoretical model of the influencing factors of the app user experience of the university mobile library was constructed.FindingsA theoretical model of influencing factors was constructed, which determined that system quality, interaction quality, content quality, interface quality and function quality were the key elements of mobile library user experiences. Furthermore, based on the research results and user feedback obtained in the research process, the content and key points relating to the user experience can be elaborated in detail. In addition, this study was able to determine users' perspectives and their behavioural characteristics when engaging in mobile learning.Originality/valueThis study establishes a theoretical model of the factors influencing of the user experience of university mobile libraries based on mobile learning, which could provide a valuable reference for the design of other programs and strategies to promote user learning experiences of mobile library app in colleges and universities.
Purpose
To describe a process of creating eHealth components for an integrated care model using an agile software development approach, user‐centered design and, via the Behavior Change Wheel, ...behavior theory‐guided content development. Following the principles of implementation science and using the SMILe project (integrated care model for allogeneic stem cell transplantation facilitated by eHealth) as an example, this study demonstrates how to narrow the research‐to‐practice gap often encountered in eHealth projects.
Methods
We followed a four‐step process: (a) formation of an interdisciplinary team; (b) a contextual analysis to drive the development process via behavioral theory; (c) transfer of content to software following agile software development principles; and (d) frequent stakeholder and end user involvement following user‐centered design principles.
Findings
Our newly developed comprehensive development approach allowed us to create a running eHealth component and embed it in an integrated care model. An interdisciplinary team’s collaboration at specified interaction points supported clear, timely communication and interactions between the specialists. Because behavioral theory drove the content development process, we formulated user stories to define the software features, which were prioritized and iteratively developed using agile software development principles. A prototype intervention module has now been developed and received high ratings on the System Usability Scale after two rounds of usability testing.
Conclusions
Following an agile software development process, structured collaboration between nursing scientists and software specialists allowed our interdisciplinary team to develop meaningful, theory‐based eHealth components adapted to context‐specific needs.
Clinical Relevance
The creation of high‐quality, accurately fitting eHealth components specifically to be embedded in integrated care models should increase the chances of uptake, adoption, and sustainable implementation in clinical practice.
Background
HIV mobile health (mHealth) interventions often incorporate interactive peer-to-peer features. The user-generated content (UGC) created by these features can offer valuable design insights ...by revealing what topics and life events are most salient for participants, which can serve as targets for subsequent interventions. However, unstructured, textual UGC can be difficult to analyze. Interpretive thematic analyses can preserve rich narratives and latent themes but are labor-intensive and therefore scale poorly. Natural language processing (NLP) methods scale more readily but often produce only coarse descriptive results. Recent calls to advance the field have emphasized the untapped potential of combined NLP and qualitative analyses toward advancing user attunement in next-generation mHealth.
Objective
In this proof-of-concept analysis, we gain human-centered design insights by applying hybrid consecutive NLP-qualitative methods to UGC from an HIV mHealth forum.
Methods
UGC was extracted from Thrive With Me, a web app intervention for men living with HIV that includes an unstructured peer-to-peer support forum. In Python, topics were modeled by latent Dirichlet allocation. Rule-based sentiment analysis scored interactions by emotional valence. Using a novel ranking standard, the experientially richest and most emotionally polarized segments of UGC were condensed and then analyzed thematically in Dedoose. Design insights were then distilled from these themes.
Results
The refined topic model detected K=3 topics: A: disease coping; B: social adversities; C: salutations and check-ins. Strong intratopic themes included HIV medication adherence, survivorship, and relationship challenges. Negative UGC often involved strong negative reactions to external media events. Positive UGC often focused on gratitude for survival, well-being, and fellow users’ support.
Conclusions
With routinization, hybrid NLP-qualitative methods may be viable to rapidly characterize UGC in mHealth environments. Design principles point toward opportunities to align mHealth intervention features with the organically occurring uses captured in these analyses, for example, by foregrounding inspiring personal narratives and expressions of gratitude, or de-emphasizing anger-inducing media.
What is online risk? How can we best protect children from it? Who should be responsible for this protection? Is all protection good? Can Internet users trust the industry? These and other ...fundamental questions are discussed in this book. Beginning with the premise that the political and democratic processes in a society are affected by the way in which that society defines and perceives risks, Children in the Online World offers insights into the contemporary regulation of online risk for children (including teens), examining the questions of whether such regulation is legitimate and whether it does in fact result in the sacrifice of certain fundamental human rights. The book draws on representative studies with European children concerning their actual online risk experiences as well as an extensive review of regulatory rationales in the European Union, to contend that the institutions of the western European welfare states charged with protecting children have changed fundamentally, at the cost of the level of security that they provide. In consequence, children at once have more rights with regard to their personal decision making as digital consumers, yet fewer democratic rights to participation and protection as ’digital citizens’. A theoretically informed, yet empirically grounded study of the relationship between core democratic values and the duty to protect young people in the media-sphere, Children in the Online World will appeal to scholars and students across the social sciences with interests in new technologies, risk and the sociology of childhood and youth. Book: The Open Access version of this book, available at http://www.taylorfrancis.com, has been made available under a Creative Commons Attribution-Non Commercial-No Derivatives (CC-BY-NC-ND) 4.0 license.
The paper mentions that a hybrid recommender systems framework creates user-profile groups before applying a collaborative-filtering algorithm by incorporating techniques from the multiple-criteria ...decision-analysis (MCDA) field.
User satisfaction depicts the effectiveness of a system from the user’s perspective. Understanding and predicting user satisfaction is vital for the design of user-oriented evaluation methods for ...conversational recommender systems (CRSs). Current approaches rely on turn-level satisfaction ratings to predict a user’s overall satisfaction with CRS. These methods assume that all users perceive satisfaction similarly, failing to capture the broader dialogue aspects that influence overall user satisfaction.We investigate the effect of several dialogue aspects on user satisfaction when interacting with a CRS. To this end, we annotate dialogues based on six aspects (i.e., relevance, interestingness, understanding, task-completion, interest-arousal, and efficiency) at the turn and dialogue levels. We find that the concept of satisfaction varies per user. At the turn level, a system’s ability to make relevant recommendations is a significant factor in satisfaction. We adopt these aspects as features for predicting response quality and user satisfaction. We achieve an F1-score of 0.80 in classifying dissatisfactory dialogues, and a Pearson’s r of 0.73 for turn-level response quality estimation, demonstrating the effectiveness of the proposed dialogue aspects in predicting user satisfaction and being able to identify dialogues where the system is failing.With this article, we release our annotated data.1
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