1,720,999 research outputs found
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Self-control and technology usage
No full textExcessive technology usage has been gaining more attention for the past decades. While empowering human productivity, digital activities are also trapping people into overly long and intensive usage especially to the younger generations (Twenge,2017). In order to moderate tech-usage and maintain good digital hygiene, one’s self-control capability plays a great role. This paper aims to explore 2 self-control strategies’ effect on people’s technology usage. A mixed methodology of semi-structured interviews and single-case experiment was conducted on 14 graduate school students who heavily rely on digital platforms for work and study. Both quantitative data of participants’ actual non-productive length ratio and qualitative data of the 28 interviews were analyzed. The non-productive ratio remained at the same level for both strategies.More in-depth discussions around the distraction sources, distracted reasons and the 2 strategies effect are provided in the qualitative affinity analysis. Possible recommendations for future improvement on moderate tech-usage are also discussed.Master of Science in Information (MSI)School of InformationUniversity of Michiganhttps://deepblue.lib.umich.edu/bitstream/2027.42/149640/1/Hou_Chuhan_20190507_Final-MTOP-Thesis.pd
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Just-In-Time Adaptive Interventions: Experiment, Inference and Online Learning
Full text linkThe use and development of mobile interventions are experiencing rapid growth. Ideally, mobile devices can be used to provide treatment/support whenever needed and to adapt treatment to the context of the user. Just-In-time Adaptive Interventions (JITAIs) are composed of decision rules that map a user’s context (e.g., user's behaviors, location, current time, social activity, stress and urges to smoke) to a treatment that is delivered to the user via the mobile device in near real-time. Advancements in mobile health engineering and technology (e.g., passive stress sensing) continue to bring us closer to being able to provide interventions in this way. However, a number of important gaps in data science must be addressed before mobile devices can be used to deliver on the promise of JITAIs. First, there is a need for experimental designs to collect data that can be used to assess the effectiveness of the sequence of treatments delivered by a mobile device on health outcomes in order to support the development of JITAIs. Second, there is a need for data-driven methods to inform the construction of efficacious JITAIs. In the vast majority of currently deployed JITAIs, the decision rules underpinning JITAIs are formulated using domain expertise and clinical experience, with very limited use of data evidence.
In this dissertation, we make several contributions by tackling the above- mentioned data science barriers to effective JITAI development in mobile health. First, we propose a micro-randomized trial (MRT) design and develop the primary analysis for assessing the proximal causal effect of treatments. In addition, we develop stratified micro-randomized trials for the setting where there is a time-varying, discrete variable, and the primary analysis focuses on how the effectiveness of interventions changes with this variable. We also develop a novel algorithm to design the randomization scheme for this setting when there is an average constraint on the number of times interventions that should be sent in a certain time interval. Second, we develop a semi-parametric model to estimate the long-term average of health outcomes that would accrue should a given JITAI be followed. We derive the rate of convergence and the asymptotic normality of the proposed estimator. Third, we develop an online learning algorithm that continuously learns and improves the JITAI as the data is collected from the user. The proposed algorithm introduces a proxy of future outcomes based on a dosage variable to capture the delayed effect of sending the interventions due to the treatment burden.PhDStatisticsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/151474/1/pengliao_1.pd
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
Using and Collecting Annotated Behavioral Trace Data For Designing and Developing Context-Aware Application.
Full text linkUbiquitous Computing has been a focus of numerous researchers hoping to create environments where users are served by heterogeneous computing devices responding to their contexts. Thanks to these researchers' research efforts, computing infrastructures, sensing devices, and intelligent systems have been developed, making the creation of context-aware systems more viable, economic, and appealing to designers and developers. This thesis aims to respond to this emerging trend by developing systems and practices supporting more effective development of context-aware applications. In particular, I focus on using a capture-and-playback approach—capturing and playing back behavioral and contextual data to prototype, test, and evaluate context-aware applications. The thesis makes five main contributions in this area. The first two contributions focus on supporting playback. In Chapter 3, I present findings and lessons learned from two case studies and a developer study involving the capture-and-playback approach and tool, of which the results inform the design space for supporting context-aware application development. Second, I present a design, development, and evaluation of a capture-and-playback toolset called CaPla, which support different activities in developing context-aware applications.
Starting from Chapter 4, 5, and 6. I present my research efforts making three contributions to data capture. First, I present findings from an empirical study investigating smartphone users’ mobile receptivity to incoming communications. The findings indicate factors to be considered when sending data capture requests to smartphone users. In Chapter 5, I present a field study investigating the effectiveness of using three different approaches for collecting personal behavioral and contextual data. The results show pros and cons of the three approaches, as well as smartphone users’ behaviors in using the approaches and how activity impacts users’ data collection behaviors. Finally, in Chapter 6, I present a configurable, flexible, and extensible mobile data collection tool called Minuku. Minuku can monitor complex contextual conditions, schedule and perform highly situated actions, and allows performing different styles of data collection approaches.
The findings of the studies and the experiences with the systems point towards the design space for a more comprehensive capture-and-playback tool and a set of practices of performing a capture-and-playback approach.PhDInformationUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/120705/1/yuchang_1.pd
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
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