1,720,954 research outputs found
Why are Women Unhappy with Dating Apps? Exploring the Reasons behind Women Dissatisfaction
No full textDating apps have revolutionised the way people meet and interact in the modern dating landscape. However, there is a growing concern that women are increasingly dissatisfied with their experiences on these platforms. This research aims to explore and analyse the factors contributing to women\u27s dissatisfaction with dating apps. Through interviews with women who have used dating apps and expressed dissatisfaction, this research seeks to uncover the main reasons behind their unhappiness. The study hypothesises that inadequate safety measures, shallow interactions, and unrealistic expectations are among the key factors causing women\u27s dissatisfaction. By shedding light on these issues, this research hopes to provide valuable insights that can help understand the reasons behind the use of dating apps
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe 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
Get PDF“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
Get PDFWe 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
Get PDFWe 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
ChatGPT and Academic Writing Self-Efficacy: Unveiling Correlations and Technological Dependency among Postgraduate Students
No full textThis study investigates the impact of ChatGPT usage on academic writing self-efficacy among 148 postgraduate students from Dhar EL Mahraz in Fez and Moulay Smail in Meknes, Morocco. It aims to illuminate the dynamics between ChatGPT usage and self-efficacy in academic writing. The study employed statistical analyses such as independent-sample t-tests and ordinal logistic regressions within a cross-sectional framework to explore the dynamics between ChatGPT use, reliance, and self-efficacy in scholarly writing. Results reveal that ChatGPT users reported higher self-efficacy scores (M=3.96, SD=0.61) compared to non-users (M=3.44, SD=1.38), suggesting the potential of ChatGPT in enhancing writing self-efficacy by providing continuous feedback and fostering a sense of accomplishment. Further analyses indicate that writing self-efficacy significantly predicts the duration of ChatGPT usage (Estimate = .692, p = .011), suggesting a positive correlation between self-efficacy and prolonged ChatGPT engagement. Furthermore, the frequency of ChatGPT use was found to predict reliance on the tool (β = .619, p < .001), underscoring a habituation effect. These findings contribute to the growing discourse on the role of AI in academic writing, emphasizing the benefits of ChatGPT in fostering writing self-efficacy while cautioning against over-reliance. Recommendations include longitudinal studies to assess the evolution of writing self-efficacy with continued ChatGPT use and broader research encompassing various AI tools and academic levels. This study sheds light on the advantages of AI in education and draws attention to the need for a balanced integration of technology in academic practices
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
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
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