1,720,974 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
Online Bayesian Non-parametrics for Social Group Detection
No full textGroup detection
represents an emerging Computer Vision research topic, motivated by the increasing interest
in the modelling of the social behaviour of people. This paper presents an unsupervised method
for group detection
which is based on an on-line inference process over Dirichlet Process Mixture Models.
Formally, groups are modelled as components of an infinite mixture and individuals are seen as observations
generated from them. A sequential variational framework
allows to perform the inference in real-time, while social psychology constraints of proxemics ensure the production
of proper group hypotheses, consistent with the human perception.
The results obtained on different
compare favorably with state-of-the-art approaches, setting the best performance in some of them
Modelling Retinal Activity with Restricted Boltzmann Machines: a Study on the Inhibitory Circuitry
No full textBeing the first stage of the visual system, the retina performs an extremely important task: encoding visual information and making it available to higher visual areas. In order to be effective, the encoding should be rich enough to capture the information of different stimuli, and stable enough to show small variations across repeated presentations of the same stimulus. This should arguably be achieved as a collective behaviour, capable of subduing the variability in the response of single Retinal Ganglion Cells (RGCs). In this work we study the statistical structure of the signal produced by a large population of RGCs, looking for prototypical activation modes of the retina subject to photostimulation. RGCs are modelled as logGaussian Cox Processes and a mean covariance Restricted Boltzmann Machine (mcRBM) is used to model the joint distribution of the firing rates of all the neurons in the recorded population. Due to its formulation, the mcRBM allows to infer a set of activation modes of the retina defined by the configuration of the model's latent variables. These activation modes are obtained in a fully unsupervised way using no information about the input and thus reflect the regularities of RGCs signal. In our work we show that the activity modes found through the mcRBM map reliably to different visual stimuli. Moreover, we show that the inferred modes can be used to evaluate the information content of the retinal signal. As a case study, we evaluate the information carried by the concurrent firing rates of RGCs of a retina in normal conditions and after pharmacologically blocking GABAC, at first, and then GABAC plus GABAA and GABAB receptors. As expected from physiology, blocking the inhibitory circuitry disrupts the spatiotemporal precision of retinal encoding, resulting in a reduced Mutual Information between the inferred activation modes and the presented visual stimuli
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
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