1,721,064 research outputs found
Proceedings of the LREC 2020 workshop on Resources and Techniques for User and Author Profiling in Abusive Language (ResT-UP 2020)
No full textThis volume documents the Proceedings of the 1st Workshop on Resources and Techniques for User and Author Profiling in Abusive Language (ResT-UP), held online on 12 May 2020 as part of the LREC 2020 conference (International Conference on Language Resources and Evaluation).
The workshop aimed at bringing together researchers and scholars working on author profiling and automatic detection of abusive language on the Web, e.g., cyberbullying or hate speech, with a twofold objective: improving the existing LRs, e.g., datasets, corpora, lexicons, and sharing ideas on stylometry techniques and features needed for profile information extraction and classification. ResT-UP targeted Profiling scholars and research groups, experts in Statistic and Stylistic Analysis of texts as well as computational linguists who investigate author profile and personality both in short texts (social media posts, blog texts and email) and in long texts (such as pamphlets, (fake) news and political documents). ReST-UP represented an opportunity to share profiling experiments with the scientific community and to show automatic detection techniques of abusive language on the Web. Despite the cancellation of LREC 2020 due to the COVID-19 international emergency, ResT-UP was organized online on Microsoft Teams on May 12th 2020 and the programme included three oral presentations and featured an invited talk by Paolo Rosso. ResT-UP was attended by about fifty representatives of academic and industrial organisations
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
Investigating topic-agnostic features for authorship tasks in Spanish political speeches
No full textAuthorship Identification is the branch of authorship analysis concerned with uncovering the author of a written document. Methods devised for Authorship Identification typically employ stylometry (the analysis of unconscious traits that authors exhibit while writing), and are expected not to make inferences grounded on the topics the
authors usually write about (as reflected in their past production). In this paper, we present a series of experiments evaluating the use of feature sets based on rhythmic and psycholinguistic patterns for Authorship Verification and Attribution in Spanish political language, via different approaches of text distortion used to actively mask the underlying topic. We feed these feature sets to a SVM learner, and show that they lead to results that are comparable to those obtained by the BETO transformer when the latter is trained on the original text, i.e., when potentially learning from topical informatio
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
Cross Attention for Selection-based Question Answering
No full textAnswer Sentence Selection (ASS) is one of the steps typically involved in Question Answering, a hard task for natural language
processing since full solutions would require both natural language understanding and world knowledge. We present a new approach to tackle
ASS, based on a Cross-Attentive Convolutional Neural Network. The
approach was designed for competing in the Fujitsu AI-NLP challenge
Fujitsu [4], which evaluates systems on their performance on the SelQA[7]
dataset. This dataset was created on purpose as a benchmark to stress
the ability of systems to go beyond simple word co-occurrence criteria.
Our submission achieved the top score in the challenge
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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