1,720,992 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
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
Personality assessment based on biosignals during a decision-making task
Full text linkDue to the emergence of novel acquisition devices and signal processing techniques,
the study of electrophysiology and its applications has assumed an important role on
the Biomedical Engineering community. Recently, research on this area has expanded to several domains, with the psychophysiology being a proeminent one, more specifically in the field of personality psychology.
In this thesis, participants were asked to perform a wildly known decision-making
task, the Iowa Gambling Task (IGT), and their biosignals were recorded during this performance with the objective of determining whether changes in biosignals could be related to personality. This project was composed by 71 participants and their biosignals were used to extract meaningful features that together could create a predictive model of personality.
For this, all biosignals were processed prior to the feature extraction step and
the features were extracted from the entire signals, recorded during the performance
of the IGT, and also dividing the task in five blocks. After the extraction, a machine
learning algorithm was used to compute the best predictive models for the Five Factor
Model (FFM) personality dimensions and for the Maximization and Regret scales, using
each biosignal individually and in the end all features from all biosignals.
The results showed that the predictive models which use features from all biosignals
perform better than the models which use only one biosignal. The Openness to Experience, Agreeableness and Maximization scales are well predicted with features from Electrocardiogram (ECG), the Agreeableness, Maximization and Extraversion scales with Electrodermal Activity (EDA) features and the Extraversion and Openness to Experience scales with features from Blood Volume Pulse (BVP). The hypothesis that personality traits is more expressed in the start of IGT was confirmed since the highest number of features is extracted from the Block 1 of the IGT. The results should be further validated for other populations
Personality Assessment Using Biosignals and Human Computer Interaction applied to Medical Decision Making
Full text linkClinical decision-making for patients with multiple acute or chronic diseases (i.e. multimorbidity)
is complex. There is often no ’right’ or optimal treatment due to the potentially
harmful effects of multiple interactions between drugs and diseases. This makes
it necessary to establish trade-offs between the benefits and risks of different treatment
strategies. This means also that there may be high levels of risk and uncertainty when
making decisions. One factor that can influence how decisions are made under conditions
of risk and uncertainty is the decision maker’s personality. The studies of this dissertation
used biosignals and eye-tracking methods and developed pointer tracking techniques to
monitor human computer interaction to assess, using machine learning techniques, the
individual personality of decision makers.
Data acquisition systems were designed and prepared to collect and synchronize: 1)
physiological data - electrocardiogram, blood volume pulse and electrodermal activity;
2) human-computer interaction data - pointer movements, eye tracking and pupil diameter;
3) decision-making task data; and 4) personality questionnaire’ results. A set
of processing tools was developed to ensure the correct extraction of psychophysiologyrelated
features that could manifest personality. These features were combined by several
machine learning algorithms to predict the Big-Five personality traits: Openness, Conscientiousness,
Extraversion, Agreeableness and Conscientiousness.
The five personality traits were well modelled by, at least, one of the sets of features
extracted. With a sample of 88 students, features from the pointer movements in online
surveys predicted four personality traits with a mean squared error (MSE)<0.46. The
blood volume pulse responses in a decision-making task trained in a distinct sample of
79 students predicted four personality traits with a MSE<0.49. The application of the
personality models based on the pointer movements in the personality questionnaire in
a sample of 12 medical doctors achieved a MSE<0.40 for three personality traits. These
were the best results achieved in each context of this thesis.
The outcomes of this work demonstrate the huge potential of broader models that
predict personality through human behaviour, with possible application in a wide variety
of fields, such as human resources, medical research studies or machine learning
approaches
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
Prediction of uncertainty events using human-computer interaction
Full text linkThe practice of medicine is characterized by complex situations that evoke uncertainty.
Uncertainty has implications for the quality and costs of health care, thus emphasizing
the importance of identifying its the main causes.
Uncertainty can be manifested through human behaviour. Accordingly, in this dissertation,
a machine learning model that detects events of uncertainty based on mouse
cursor movements was created. To do so, 79 participants answered an online survey while
the mouse data was being tracked. This data was used to extract meaningful features that
allowed model testing and training after a feature selection stage. With the implementation
of a Logistic Regression, and applying a k-fold cross-validation method, the model
achieved an estimated performance of 81%.
It was found that, during moments of uncertainty, the number of horizontal direction
inversions increases and the mouse cursor travels higher distances. Moreover, items that
evoke uncertainty are associated to longer interaction times and a higher number of visits.
Subsequently, the model was applied to a medical decision making task performed
by 8 physicians, in order to understand whether it might be applied in different contexts
or not. The results were consistent with the task design.
To better understand the nature of uncertainty, its relationship with personality was
explored. Regarding the clinical task, it was found a slight tendency of uncertainty to
increase with Neuroticism.
In the future, the created model may be used to help physicians understand their
main difficulties
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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