1,721,026 research outputs found
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
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
Investigating new sources of information and nonlinearities on financial markets
Get PDFThis doctoral thesis is concerned with two separate but intertwined topics in the field of financial econometrics: (i) the measurement and relevance of new sources of information on financial markets in the form of online investor sentiment and attention and (ii) nonlinearities in financial time series in the form of structural breaks. According to classical finance theory, competition among rational investors, often called arbitrageurs, leads to an equilibrium in which prices on capital markets equal the present value of expected future cash flows. Under this theoretical lens, the trading decisions of irrational investors have no significant impact on prices since their demands are offset by rational investors. However, the classical finance theory fails to fit the extreme levels of and changes in stock prices corresponding to events such as the Great Crash of 1929 or the Dot.com bubble of the 1990s, which are difficult to align with any rational explanation.Akin to the notion of "animal spirit" first coined by Keynes (1936), behavioral finance theory sets out to augment the classical model by explicitly taking into account two assumptions: Firstly, trading activities of investors are thought of to be partially influenced by subjective beliefs about investment risks and future cash flows, generally referred to as investor sentiment. Secondly, there are limits to arbitrage in the sense that betting against sentiment-driven investors is associated with higher risks and costs. Thus, inconsistent with predictions of the classical finance theory, arbitrageurs do not aggressively force prices to fundamentals. On this basis, irrational (collective) investor behavior has moved into the focus of modern finance theory and corresponding empirical applications. The widespread internet access and usage of social media platforms in recent years have led to new sources of information - and with them new sources and types of data that can be used by researchers and practitioners alike - pertaining to this collective investor behavior and corresponding financial market outcome: Short messages published on social media platforms such as Twitter or StockTwits on the one hand and online search queries on the other. The first part of this thesis makes use of such data in empirical financial applications, also from a high-frequency intraday perspective, in order to assess its impact on predictions of financial variables and to unravel new relationships. In general, it is reasonable to assume that many relationships in economics and finance are nonlinear. Thus, several kinds of nonlinearities can arise when considering financial markets and time series of financial variables that are not necessarily approximated well by simple linear models. Relating to the behavioral finance literature, the model of De Long et al. (1990) proposes that in the presence of sentiment-prone noise traders the price of a risky asset evolves as a nonlinear function of these noise traders' average bullishness (i.e., their mean misperception of the expected price) and its variance. Though being of a different philosophical nature than sentiment-induced noise trader theories, some other models of trade based on noninformational reasons, such as changes in risk aversion or liquidity needs, also involve nonlinear relations.The second part of the thesis focuses on one often overlooked kind of nonlinearity that entails potentially more severe implications, namely structural breaks in financial time series. Structural breaks, also referred to as change-points, in the data generating process underlying a given univariate time series do not only constitute a source of nonlinearity that can be modeled but also a more subtle source of nonstationarity. Given that endeavors of time series model building and prediction usually demand some stationarity assumption to be made, the latter poses a common problem in the analysis of univariate economic and financial time series. Matters are complicated by the fact that the exact number and timing of structural breaks are usually unknown ex-ante. Therefore, the consistent estimation of structural breaks, or change-points, has been studied extensively in the related literature. This thesis adds to the ongoing discussion by proposing a two-step model selection procedure for the detection and timing of change-points in structural break autoregressive models. A similar methodology is then used to investigate the effect of Box-Cox transforms on the estimation of structural breaks in realized volatility time series
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
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