1,720,964 research outputs found
How relevant is part-of-speech information to compute similarity between Greek verses in a graph database?
No full textThis paper presents the automatic linguistic analysis of the Database of Byzantine Book Epigrams (DBBE) on the one hand, and its representation and integration in a graph database on the other hand. Firstly, we provide a comprehensive description of the DBBE data we want to provide with a complete morphological analysis. The presented methodology explores the possibilities of fine-tuning the DBBErt transformer-based language model, which was trained on pre-Modern and Modern Greek. Secondly, the automatically annotated epigrams are integrated in a graph database, a new way to represent the relatedness of this entangled corpus. With the graph database, we can compute similarity between words, verses and epigrams. Given the scope of this paper, we computed a complete orthographic similarity between the verses, a similarity based on the automatically assigned part-of-speech information and a final similarity measure that combines both orthography and part-of-speech information. The results of these similarity measures provide scholars with new visual representations of relations between (parts of) texts, which is beneficial for new critical editions and commentaries
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
Decoding Byzantine book epigrams : an exploration of machine-assisted extraction of formulaic material
No full textThis paper proposes a machine-assisted methodology for identifying and extracting formulaic sequences from a subset of the Database of Byzantine Book Epigrams (DBBE). The methodology involves conceptualising formulaicity within the DBBE corpus, pre-processing and extracting n-grams from textual data, followed by refinement before delving into the interpretation of the results. Through systematic application of this methodology, some initial insights into the characteristics of formulaic language within the Byzantine book epigram tradition are gained. Representative findings illustrate the nature of recurring patterns, cases of creative elaboration, and their content. This initial exploration aims to facilitate a deeper understanding of the concept of formulaicity in Byzantine book epigrams; while computational analysis provides a quantitative perspective, linguistic and philological research is necessary for a more nuanced understanding. Future research directions include refining the methodology and expanding the scope of analysis beyond the current subset of the DBBE. Overall, this study lays the groundwork for further research on this rich book epigram tradition
Viability of Automatic Lexical Semantic Change Detection on a Diachronic Corpus of Literary Ancient Greek
Full text linkWe apply two measures of lexical semantic change detection to Word2Vec embeddings trained on a diachronic corpus of literary Ancient Greek texts. The two measures are the Vector Coherence, based on the comparison between vectors of the same word in different time periods, and the J, based on the Jaccard coefficient, which quantifies the overlap between the k nearest neighbours in each possible combination of time slices. Through the analysis of the most stable and unstable words detected with both measures, we show that the two measures are effective at finding non-changed words, while Vector Coherence seems to be more reliable than J at detecting changed words. Still, low J could indicate a real semantic change when the same word also has a low Vector Coherence. For both measures, the detection of changed words is hampered by the presence of lemmatization errors in the training corpus
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
Viability of Automatic Lexical Semantic Change Detection on a Diachronic Corpus of Literary Ancient Greek
Full text linkWe apply two measures of lexical semantic change detection to Word2Vec embeddings trained on a diachronic corpus of literary Ancient Greek texts. The two measures are the Vector Coherence, based on the comparison between vectors of the same word in different time periods, and the J, based on the Jaccard coefficient, which quantifies the overlap between the k nearest neighbours in each possible combination of time slices. Through the analysis of the most stable and unstable words detected with both measures, we show that the two measures are effective at finding non-changed words, while Vector Coherence seems to be more reliable than J at detecting changed words. Still, low J could indicate a real semantic change when the same word also has a low Vector Coherence. For both measures, the detection of changed words is hampered by the presence of lemmatization errors in the training corpus
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