Information exchange on an academic social networking site: A multidiscipline comparison on researchgate Q&A

The increasing popularity of academic social networking sites (ASNSs) requires studies on the usage of ASNSs among scholars and evaluations of the effectiveness of these ASNSs. However, it is unclear whether current ASNSs have fulfilled their design goal, as scholars' actual online interactions on these platforms remain unexplored. To fill the gap, this article presents a study based on data collected from ResearchGate. Adopting a mixed-method design by conducting qualitative content analysis and statistical analysis on 1,128 posts collected from ResearchGate Q&A, we examine how scholars exchange information and resources, and how their practices vary across three distinct disciplines: library and information services, history of art, and astrophysics. Our results show that the effect of a questioner's intention (i.e., seeking information or discussion) is greater than disciplinary factors in some circumstances. Across the three disciplines, responses to questions provide various resources, including experts' contact details, citations, links to Wikipedia, images, and so on. We further discuss several implications of the understanding of scholarly information exchange and the design of better academic social networking interfaces, which should stimulate scholarly interactions by minimizing confusion, improving the clarity of questions, and promoting scholarly content management

Budgeting for Nebraska Local Governments

Budgeting is a complex set of activities. To those unfamiliar with its details, it is a mysterious rite conducted annually, and even those familiar with the process give a multitude of definitions. The simplest definition is that budgeting involves the acquisition and allocation of resources

FACTORS INFLUENCING USER’S CONTINUANCE INTENTION ON PAID QUESTION AND ANSWER SERVICE ----A STUDY ON WEIBO IN CHINA

This thesis addresses the research question “Why do users continue to use paid Q&A in China” by means showed below: First, this research introduces research background of paid Q&A in China and raises corresponding research question and highlights the research significance of this thesis topic; Second, the author concludes previous research on paid Q&A in aspects of Q&A system, paid subscription and sharing economy, and finds that most of prior research focuses on exploring the influence of usefulness but not enjoyment on the users’ willingness of continuing using a paid Q&A system; Third, the thesis introduces the VAM theory and build a modified model based on it, this modified model highlights the importance of pleasure on users’ continuance intention in using paid Q&A; Finally, the empirical study combining an Exploratory Factor Analysis and a Confirmatory Factor Analysis proves that, after integrating factors extracted from previous research and the proposed model, the research is tested to be explanatorily capable and hypotheses related to the model are mostly proved to be supported. As a conclusion, this study conducts an investigation on the constructs and related theories that influence users’ continuance intention to use paid Q&A, from a hedonic perspective. In this thesis, VAM theory is selected as the prototype of proposed research model which reveals factors affecting users’ continuance intention to use a Chinese paid Q&A product named Weibo Paid Q&A. In this thesis, the proposed model makes predictions that the constructs perceived fee and community atmosphere along with perceived enjoyment construct have critical effect on users’ continuance willingness in using Weibo Paid Q&A in China. With the assistance of PLS–SEM, this study analyzes data collected from users in WPQA, the empirical study verifies that users' continuance intention is assuredly dependent on perceived fee and community atmosphere along with perceived enjoyment. The study also reveals that quality of answerers and quality of answer positively exert significant influences on perceived enjoyment

"I am pregnant and my husband has diabetes. Is there a risk for my child?" A qualitative study of questions asked by email about the role of genetic susceptibility to diabetes

<p>Abstract</p> <p>Background</p> <p>Diabetes Mellitus is a global health problem. Scientific knowledge on the genetics of diabetes is expanding and is more and more utilised in clinical practice and primary prevention strategies. Health consumers have become increasingly interested in genetic information. In the Netherlands, the <it>National Genetic Research and Information Center </it>provides online information about the genetics of diabetes and thereby offers website visitors the opportunity to ask a question per email. The current study aims at exploring people's need of (additional) information about the role of inheritance in diabetes. Results may help to tailor existing clinical and public (online) genetic information to the needs of an increasing population at risk for diabetes.</p> <p>Methods</p> <p>A data base with emailed questions about diabetes and inheritance (n = 172) is used in a secondary content analysis. Questions are posted in 2005-2009 via a website providing information about more than 600 inheritable disorders, including all diabetes subtypes. Queries submitted were classified by contents as well as persons' demographic profiles.</p> <p>Results</p> <p>Questions were received by diabetes patients (49%), relatives (30%), and partners (21%). Questioners were relatively young (54.8% ≤ 30 years) and predominantly female (83%). Most queries related to type 1 diabetes and concerned topics related to (future) pregnancy and family planning. Questioners mainly asked for risk estimation, but also clarifying information (about genetics of diabetes in general) and advice (mostly related to family planning) was requested. Preventive advice to reduce own diabetes risk was hardly sought.</p> <p>Conclusions</p> <p>Genetic information on diabetes provided by professionals or public health initiatives should address patients, as well as relatives and partners. In particular women are receptive to genetic information; they worry about the diabetes related health of (future) offspring. It seems important that information on the contribution of genetics to type 1 diabetes is more readily available. Considering the high prevalence of type 2 diabetes with strong evidence for a genetic predisposition, more effort seems needed to promote awareness around familial clustering and primary prevention.</p

Social Roles, Interactions and Community Sustainability in Social Q&A Sites: A Resource-based Perspective

Online tech support communities have become valuable channels for users to seek and provide solutions to specific problems. From the resource exchange perspective, the sustainability of a social system is contingent upon the size of its members as well as their communication activities. To further extend the resource-based model, the current research identifies a variety of social roles in a large tech support Q&A forum and examines longitudinal changes in the community’s structure based on the identification. Moreover, this study also investigates the relationship between the community’s functionality and its traffic. Results suggest that the proportion of unsolved questions negatively impacts the number of future incoming questions and the outcome of a given question is not only dependent on users’ interactions within the discussion, but also on the community activities preceding the question. These observations can help community managers to improve system design and task allocation

Chatting Makes Perfect -- Chat-based Image Retrieval

Chats emerge as an effective user-friendly approach for information retrieval, and are successfully employed in many domains, such as customer service, healthcare, and finance. However, existing image retrieval approaches typically address the case of a single query-to-image round, and the use of chats for image retrieval has been mostly overlooked. In this work, we introduce ChatIR: a chat-based image retrieval system that engages in a conversation with the user to elicit information, in addition to an initial query, in order to clarify the user's search intent. Motivated by the capabilities of today's foundation models, we leverage Large Language Models to generate follow-up questions to an initial image description. These questions form a dialog with the user in order to retrieve the desired image from a large corpus. In this study, we explore the capabilities of such a system tested on a large dataset and reveal that engaging in a dialog yields significant gains in image retrieval. We start by building an evaluation pipeline from an existing manually generated dataset and explore different modules and training strategies for ChatIR. Our comparison includes strong baselines derived from related applications trained with Reinforcement Learning. Our system is capable of retrieving the target image from a pool of 50K images with over 78% success rate after 5 dialogue rounds, compared to 75% when questions are asked by humans, and 64% for a single shot text-to-image retrieval. Extensive evaluations reveal the strong capabilities and examine the limitations of CharIR under different settings

Questioning Prime Ministers: Procedures, Practices and Functions in Parliamentary Democracies

This thesis investigates parliamentary oral questioning mechanisms that involve prime ministers in parliamentary democracies. Considering the fact that prime ministers are powerful and visible actors in parliamentary democracies, and that accountability is a key component of democratic politics, it maps the mechanisms through which parliamentarians may question prime ministers in different countries, and explores the extent to which these mechanisms contribute to accountability, and the extent to which they perform other functions. The first research component is a survey of procedural rules regarding mechanisms through which parliamentarians may question prime ministers in 31 parliamentary democracies. It draws on an indepth examination of parliamentary rules of procedure, followed by a consultation with practitioners and officials in each country to uncover aspects of convention and practice. Subsequently, questioning mechanisms are classified based on dimensions such as their collective or individualised nature, the extent to which procedures allow more open or closed participation, as well as the degree of questioning exposure to which prime ministers are subjected. It then discusses how these dimensions might affect the practice of questioning. Drawing on these classifications, the second research component investigates the practice of questioning prime ministers in four countries: two using collective questioning mechanisms, where prime ministers are questioned together with ministers (Question Period in Canada, Question Time in Australia); and two using individualised mechanisms, where prime ministers are questioned alone (Prime Minister’s Questions in the UK, Oral Questions to the Taoiseach in Ireland). This second component relies on quantitative and qualitative content analysis of transcripts of parliamentary debates for each case study country. Departing from the assumption that parliamentary questioning mechanisms are designed to facilitate accountability, it investigates the degree to which they do so, and the degree to which they perform other functions, such as facilitating the expression of conflict, support, or territorial representation

Answering Twitter Questions: a Model for Recommending Answerers through Social Collaboration

International audienceIn this paper, we specifically consider the challenging task of solving a question posted on Twitter. The latter generally remains unanswered and most of the replies, if any, are only from members of the questioner's neighborhood. As outlined in previous work related to community Q&A, we believe that question-answering is a collaborative process and that the relevant answer to a question post is an aggregation of answer nuggets posted by a group of relevant users. Thus, the problem of identifying the relevant answer turns into the problem of identifying the right group of users who would provide useful answers and would possibly be willing to collaborate together in the long-term. Accordingly, we present a novel method, called CRAQ, that is built on the collaboration paradigm and formulated as a group entropy optimization problem. To optimize the quality of the group, an information gain measure is used to select the most likely " informative " users according to topical and collaboration likelihood predictive features. Crowd-based experiments performed on two crisis-related Twitter datasets demonstrate the effectiveness of our collaborative-based answering approach