基于Usage Metrics的中文学术论文用户平台偏好和兴趣偏好比较研究

研究中文学术论文用户使用模式有助于分析使用规律,为应用决策提供依据。本文以八个学科被CSSCI或CSCD收录的61本开放获取期刊发表于2014—2015年的学术论文为样本,以期刊官网和信息集成平台上的使用数据为来源,采用Usage Metrics的方法,从用户平台偏好和用户兴趣偏好两方面比较中文学术论文的用户使用模式。研究发现:①期刊官网与信息集成平台的用户平台偏好存在差异。一是从学科视角看,用户整体上倾向于使用期刊官网而不是信息集成平台获取所需论文,而社会科学的信息集成平台篇均下载次数均大于自然科学。二是从期刊视角看,社会科学用户比自然科学用户更倾向于使用信息集成平台获取所需论文;与信息集成平台相比,期刊官网的用户下载数据呈现更为明显的“两级分化”现象;期刊官网下载次数与信息集成平台下载次数整体上的相关性较低。②期刊官网与信息集成平台的用户兴趣偏好存在差异。每本期刊官网和信息集成平台下载次数前20%的学术论文的Jaccard相似系数较低;在所列举的图书馆、情报与文献学中,期刊官网与信息集成平台的用户关注主题不同。图7。表5。参考文献37。     

Health science libraries in Sweden: new directions,expanding roles

Librarians in Sweden are facing huge challenges in meeting the demands of their organisations and users. This article looks at four key areas: coping with open science/open access initiatives; increasing demands from researchers for support doing systematic reviews; understanding user experiences in Swedish health science libraries; and the consequences of expanding roles for recruitment and continuing professional development. With regard to changing roles, there is an increasing shift from the generalist towards the expert role. The authors raise the issue as to how to prepare those new to the profession to the changing environment of health science libraries.     

Trends of infodemiology studies: a scoping review

Introduction

The health care industry is rich in data and information. Web technologies, such as search engines and social media, have provided an opportunity for the management of user generated data in real time in the form of infodemiology studies. The aim of this study was to investigate infodemiology studies conducted during 2002–2016, and compare them based on developed, developing and in transition countries.

Methods

This scoping review was conducted in 2017 with the help of the PRISMA guidelines. PubMed, Scopus, Science Direct, Web of Knowledge, Google Scholar, Wiley and Springer databases were searched between the years 2002 and 2016. Finally, 56 articles were included in the review and analysed.

Results

The initial infodemiology studies pertain to the quality assessment of the hospital's websites. Most of the studies were on developed countries, based on flu, and published in the Journal of Medical Internet Research.

Conclusion

The infodemiology approach provides unmatched opportunities for the management of health data and information generated by the users. Using this potential will provide unique opportunities for the health information need assessment in real time by health librarians and thereby provide evidence based health information to the people.

     

Spatial Discovery of Linked Research Datasets and Documents at a Spatially Enabled Research Library

Current publishing practices in academia tend to result in datasets that are difficult to discover. This is because datasets are not well-integrated across academic domains and they are often not linked to the documents that reference them. For these reasons, discovering datasets across domains can be challenging; for example, discovering archeological observations and biological specimens using the same search is not widely supported, even if both datasets share a similar spatial extent, like Mesoamerica. It is also challenging to retrieve relevant documents that reference datasets; for example, retrieving a series of field reports that reference archeological observations is typically not supported. Our work develops an extensible method for: (1) geographically integrating collections across disciplinary repositories and (2) connecting datasets to related documents. We describe a collection of spatially-referenced researcher datasets, capturing their metadata elements and encoding them as linked open data. We then leverage existing library services to formalize links from datasets to documents. The system described in this work has been deployed, resulting in an experimental open data site for the UCSB campus. Results indicate that this system can be scaled-up with support from an institutional repository in the near future.     

An impulse to exploit: the behavioral turn in data-driven marketing

Industry advocates argue that by tailoring services and commercial solicitations to match media users’ personal interests, data-driven marketing benefits both consumers and businesses. This article shows, however, that advertisers and marketers who are taking up ideas and techniques from behavioral economics tell their clients a very different story about the aims and use of digital marketing and consumer surveillance. Listening in on this discourse demonstrates that some digital marketers conceptualize their own practices as forms of social control, appropriating concepts from behavioral economics to identify consumers’ cognitive and affective biases and target their vulnerabilities. Behavioral economics recognizes that economic decisions are not simply dictated by rational self-interest; rather, such choices depend on cognitive heuristics and habits, and can be manipulated through the design of “choice architecture.” This article discusses implications of the behavioral turn in data-driven marketing for critical advertising scholars, public advocates, and regulators.     

废蚕丝中提取丝胶工艺研究

通过对透析法、酸析法和冰冻法提取丝胶效果的比较,得出冰冻法是提取丝胶的较好的方法,其最佳的提取条件是:pH=4,-20℃,冰冻时间为13 h,丝胶液浓度为32.8%。     

小学四年级学生对平均数概念理解的发展过程

利用Pirie和Kieren提出的数学理解发展模型,分析了3名小学四年级学生对平均数概念理解的发展过程.结果表明:学生对平均数概念的理解经历了初步了解、产生表象、形成表象、关注性质和形式化等5个水平.在理解发展过程中,当学生发现他的思想和行动与自己所面临的问题不一致时,他就要折返回内层水平来扩展自己目前的活动能力和活动空间.而教师的干预则激发了学生的折返,为学生提供了独立建构或修正个人表象的机会.     

Multimodal data as a means to understand the learning experience

Most work in the design of learning technology uses click-streams as their primary data source for modelling & predicting learning behaviour. In this paper we set out to quantify what, if any, advantages do physiological sensing techniques provide for the design of learning technologies. We conducted a lab study with 251 game sessions and 17 users focusing on skill development (i.e., user's ability to master complex tasks). We collected click-stream data, as well as eye-tracking, electroencephalography (EEG), video, and wristband data during the experiment. Our analysis shows that traditional click-stream models achieve 39% error rate in predicting learning performance (and 18% when we perform feature selection), while for fused multimodal the error drops up to 6%. Our work highlights the limitations of standalone click-stream models, and quantifies the expected benefits of using a variety of multimodal data coming from physiological sensing. Our findings help shape the future of learning technology research by pointing out the substantial benefits of physiological sensing.