1,720,984 research outputs found
Advancing models of semantic representation: empirical study designs, network analysis methods, and computational tools
Full text linkPeople learn an astonishing amount of things about the world throughout life. This knowledge is retained in semantic representations, the cognitive manifestation of factual information in memory. Modeling semantic representations is an important ingredient to understanding how people acquire knowledge from their environment, how this knowledge is organized in memory, and how it affects behavior. Given the wide-ranging implications of semantic representations, research questions address multiple aspects, including their structure and content. Various methodological approaches have been used to successfully model semantic representations from text and behavioral data. However, much is still unknown about the optimal ways to model semantic representations, particularly regarding structural differences of representations among people. In addition, further investigation is needed to connect the structure of semantic representations to environments and behavior, as well as to map the content of individual concepts’ semantic representations. This dissertation aims to improve the methods and tools used for modeling semantic representations across various applications while also establishing links between semantic representation and cognitive performance. The first two manuscripts explore the relationships between environment and semantic representation as well as between semantic representation and cognitive performance of younger and older adults in a proof-of-concept study. The third manuscript presents a comprehensive recovery simulation study that evaluates which empirical study designs yield accurate individual-level semantic networks based on free associations and relatedness judgments. The fourth manuscript introduces the R package associatoR and includes a tutorial on how to use it to map the content of semantic representation. Together, this dissertation contributes to the understanding of individual differences in semantic representation by linking it to cognitive performance, guiding study design for assessing individual semantic networks, and facilitating the analysis of free association based models of semantic representation
Multi-publication data set on experienced-based and description-based risky choice
No full textThe data of 28 publications studying the description-experience gap, involving experience- and description-based risky choices, that served as the basis for the meta analysis reported in Wulff, D. U., Mergenthaler-Canseco, M., & Hertwig, R. (2018). A meta-analytic review of two modes of learning and the description-experience gap. Psychological Bulletin, 144(2), 140-176.</p
memnet: Network Tools for Memory Research
No full textEfficient implementations of network science tools to facilitate research into human (semantic) memory. In its current version, the package contains several methods to infer networks from verbal fluency data, various network growth models, diverse (switcher-) random walk processes, and tools to analyze and visualize networks. To deliver maximum performance the majority of the code is written in C++. For an application see: Wulff, D. U., Hills, T., & Mata, R. (2018) doi:10.31234/osf.io/s73dp>.</p
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
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
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
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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