Abstract Many studies have investigated the linguistic characteristics of television and have found important differences between categories of TV programs. Yet, little is known specifically about the lexical profiles of different genres of television discourse. The present study sought to address this gap by exploring the lexical diversity of 714 episodes representing four TV genres. The lexical diversity of each episode was measured using a six-dimensional model of lexical diversity. Multinomial logistic regression was used to determine whether the four TV genres in the present study have unique lexical diversity profiles and whether the genres of individual TV episodes can be predicted based on the adopted model. The results indicated that the four genres do indeed exhibit unique lexical diversity profiles; it was also found that the genres of individual TV episodes can be predicted with approximately 91% accuracy based on this model. These findings were interpreted as underscoring the relevance of lexical diversity to genre analysis of TV shows and the importance of using a theoretically grounded multivariate model of this construct.
{"title":"Lexical diversity as a predictor of genre in TV shows","authors":"Mary Akbary, Scott Jarvis","doi":"10.1093/llc/fqad004","DOIUrl":"https://doi.org/10.1093/llc/fqad004","url":null,"abstract":"Abstract Many studies have investigated the linguistic characteristics of television and have found important differences between categories of TV programs. Yet, little is known specifically about the lexical profiles of different genres of television discourse. The present study sought to address this gap by exploring the lexical diversity of 714 episodes representing four TV genres. The lexical diversity of each episode was measured using a six-dimensional model of lexical diversity. Multinomial logistic regression was used to determine whether the four TV genres in the present study have unique lexical diversity profiles and whether the genres of individual TV episodes can be predicted based on the adopted model. The results indicated that the four genres do indeed exhibit unique lexical diversity profiles; it was also found that the genres of individual TV episodes can be predicted with approximately 91% accuracy based on this model. These findings were interpreted as underscoring the relevance of lexical diversity to genre analysis of TV shows and the importance of using a theoretically grounded multivariate model of this construct.","PeriodicalId":45315,"journal":{"name":"Digital Scholarship in the Humanities","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136001963","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"文学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
With the advancement in technology and digitalization of resources, computation of humanities problems is no exception to remain untouched. Automatic poetry classification is now a well-defined problem which can be solved using various approaches. Mood-based poetry classification is one of the popular ones. We propose a learning approach towards metre-based classification of Hindi metrical poetry. The state of art model for the metre-based poetry classification uses the rule-based approach whereas the proposed system uses learning models to perform classification. Feature extraction and classification are the two main components of text classification in natural language processing. Text is transformed into machine-readable numbers through the process of feature extraction, which is subsequently submitted to classification models. Poems, in their most natural formulation, are unfit to any learning-based algorithms. However, transforming the data into certain form and selecting a fixed number of features out of it (feature extraction) made the classification possible using machine learning approach which was yet untouched and can act as benchmark for the concerned area of research. The article deals with six popular and similar types of Hindi poems. The dataset is collected and processed to form an early dataset that undergoes two levels of data transformation and feature engineering, resulting in the pre-processed dataset. The pre-processed dataset is then fed as input to selected machine learning models (Bernoulli Naïve Bayes, k-nearest neighbour, random forest, and support vector machine) producing classification result with best accuracy of 99%, that further undergoes a post-processing step based on observed misclassifications.
{"title":"A learning approach towards metre-based classification of similar Hindi poems using proposed two-level data transformation","authors":"Komal Naaz, Niraj Kumar Singh","doi":"10.1093/llc/fqad011","DOIUrl":"https://doi.org/10.1093/llc/fqad011","url":null,"abstract":"\u0000 With the advancement in technology and digitalization of resources, computation of humanities problems is no exception to remain untouched. Automatic poetry classification is now a well-defined problem which can be solved using various approaches. Mood-based poetry classification is one of the popular ones. We propose a learning approach towards metre-based classification of Hindi metrical poetry. The state of art model for the metre-based poetry classification uses the rule-based approach whereas the proposed system uses learning models to perform classification. Feature extraction and classification are the two main components of text classification in natural language processing. Text is transformed into machine-readable numbers through the process of feature extraction, which is subsequently submitted to classification models. Poems, in their most natural formulation, are unfit to any learning-based algorithms. However, transforming the data into certain form and selecting a fixed number of features out of it (feature extraction) made the classification possible using machine learning approach which was yet untouched and can act as benchmark for the concerned area of research. The article deals with six popular and similar types of Hindi poems. The dataset is collected and processed to form an early dataset that undergoes two levels of data transformation and feature engineering, resulting in the pre-processed dataset. The pre-processed dataset is then fed as input to selected machine learning models (Bernoulli Naïve Bayes, k-nearest neighbour, random forest, and support vector machine) producing classification result with best accuracy of 99%, that further undergoes a post-processing step based on observed misclassifications.","PeriodicalId":45315,"journal":{"name":"Digital Scholarship in the Humanities","volume":" ","pages":""},"PeriodicalIF":0.8,"publicationDate":"2023-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44976845","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"文学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The average word length of the verse sections of Henry V is greater than that of the prose sections. Contrary to the assumption that word length primarily reflects literary medium (prose–verse), a more extended examination reveals that differences in word length can also reflect differences in authorship. Since 1998, a variety of stylistic analyses have pointed in the same direction: the verse of Henry V is not generally by Shakespeare who wrote the play’s prose.
{"title":"Is it time to reconsider Henry V?","authors":"T. Merriam","doi":"10.1093/llc/fqad015","DOIUrl":"https://doi.org/10.1093/llc/fqad015","url":null,"abstract":"\u0000 The average word length of the verse sections of Henry V is greater than that of the prose sections. Contrary to the assumption that word length primarily reflects literary medium (prose–verse), a more extended examination reveals that differences in word length can also reflect differences in authorship. Since 1998, a variety of stylistic analyses have pointed in the same direction: the verse of Henry V is not generally by Shakespeare who wrote the play’s prose.","PeriodicalId":45315,"journal":{"name":"Digital Scholarship in the Humanities","volume":" ","pages":""},"PeriodicalIF":0.8,"publicationDate":"2023-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43114162","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"文学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Until recently, most research in the Digital Humanities (DH) was monomodal, meaning that the object of analysis was either textual or visual. Seeking to integrate multimodality theory into the DH, this article demonstrates that recently developed multimodal deep learning models, such as Contrastive Language Image Pre-training (CLIP), offer new possibilities to explore and analyze image–text combinations at scale. These models, which are trained on image and text pairs, can be applied to a wide range of text-to-image, image-to-image, and image-to-text prediction tasks. Moreover, multimodal models show high accuracy in zero-shot classification, i.e. predicting unseen categories across heterogeneous datasets. Based on three exploratory case studies, we argue that this zero-shot capability opens up the way for a multimodal turn in DH research. Moreover, multimodal models allow scholars to move past the artificial separation of text and images that was dominant in the field and analyze multimodal meaning at scale. However, we also need to be aware of the specific (historical) bias of multimodal deep learning that stems from biases in the training data used to train these models.
{"title":"A multimodal turn in Digital Humanities. Using contrastive machine learning models to explore, enrich, and analyze digital visual historical collections","authors":"T. Smits, M. Wevers","doi":"10.1093/llc/fqad008","DOIUrl":"https://doi.org/10.1093/llc/fqad008","url":null,"abstract":"\u0000 Until recently, most research in the Digital Humanities (DH) was monomodal, meaning that the object of analysis was either textual or visual. Seeking to integrate multimodality theory into the DH, this article demonstrates that recently developed multimodal deep learning models, such as Contrastive Language Image Pre-training (CLIP), offer new possibilities to explore and analyze image–text combinations at scale. These models, which are trained on image and text pairs, can be applied to a wide range of text-to-image, image-to-image, and image-to-text prediction tasks. Moreover, multimodal models show high accuracy in zero-shot classification, i.e. predicting unseen categories across heterogeneous datasets. Based on three exploratory case studies, we argue that this zero-shot capability opens up the way for a multimodal turn in DH research. Moreover, multimodal models allow scholars to move past the artificial separation of text and images that was dominant in the field and analyze multimodal meaning at scale. However, we also need to be aware of the specific (historical) bias of multimodal deep learning that stems from biases in the training data used to train these models.","PeriodicalId":45315,"journal":{"name":"Digital Scholarship in the Humanities","volume":" ","pages":""},"PeriodicalIF":0.8,"publicationDate":"2023-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46328559","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"文学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Retraction of: Statistical approaches in literature: Comparing and clustering the alternatives of love in <i>Divan of Hafiz</i>","authors":"","doi":"10.1093/llc/fqad002","DOIUrl":"https://doi.org/10.1093/llc/fqad002","url":null,"abstract":"","PeriodicalId":45315,"journal":{"name":"Digital Scholarship in the Humanities","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135597890","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"文学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Since its final destruction in antiquity, the memory of the temple in Jerusalem has served as the nexus of Jewish liturgy and messianic worldview. This article has sought to examine the ideological and cultural roles played by the image of the Jewish temple in the Hebrew literature of 1848–1948. Toward this end, I formulated a broad corpus comprised of homogeneous genres and authors, namely those which situate the temple as their main focus. The evidence arising from this corpus suggests that the conceptual role of the temple underwent no dramatic transformations; the temple in this literature, taken as a whole, is mostly indistinguishable from the historical, religious, and nationalistic symbol that featured in the Jewish tradition over nearly 2,000 years. The bulk of the present corpus places the temple in conceptual and historical contexts that are familiar and very similar to those of the historical temple in all its contexts, without removing it from the domains of Jewish nationalism or classical religiosity. These findings contravene my initial presupposition that the discourse of the temple had undergone a metamorphosis in the 19th and 20th centuries, the image of the temple had changed into an abstract symbol for world peace, moral perfection, and intellectual and scientific excellence.
{"title":"The status of the Jewish temple in modern Hebrew literature (1848–1948): a big-data analysis","authors":"Isaac Hershkowitz","doi":"10.1093/llc/fqad010","DOIUrl":"https://doi.org/10.1093/llc/fqad010","url":null,"abstract":"\u0000 Since its final destruction in antiquity, the memory of the temple in Jerusalem has served as the nexus of Jewish liturgy and messianic worldview. This article has sought to examine the ideological and cultural roles played by the image of the Jewish temple in the Hebrew literature of 1848–1948. Toward this end, I formulated a broad corpus comprised of homogeneous genres and authors, namely those which situate the temple as their main focus. The evidence arising from this corpus suggests that the conceptual role of the temple underwent no dramatic transformations; the temple in this literature, taken as a whole, is mostly indistinguishable from the historical, religious, and nationalistic symbol that featured in the Jewish tradition over nearly 2,000 years. The bulk of the present corpus places the temple in conceptual and historical contexts that are familiar and very similar to those of the historical temple in all its contexts, without removing it from the domains of Jewish nationalism or classical religiosity. These findings contravene my initial presupposition that the discourse of the temple had undergone a metamorphosis in the 19th and 20th centuries, the image of the temple had changed into an abstract symbol for world peace, moral perfection, and intellectual and scientific excellence.","PeriodicalId":45315,"journal":{"name":"Digital Scholarship in the Humanities","volume":" ","pages":""},"PeriodicalIF":0.8,"publicationDate":"2023-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49141301","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"文学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The great potential brought by large-scale data in the humanities is still hindered by the time and technicality required for making documents digitally intelligible. Within urban studies, historical cadasters have been hitherto largely under-explored despite their informative value. Powerful and generic technologies, based on neural networks, to automate the vectorization of historical maps have recently become available. However, the transfer of these technologies is hampered by the scarcity of interdisciplinary exchanges and a lack of practical literature destinated to humanities scholars, especially on the key step of the pipeline: the annotation. In this article, we propose a set of practical recommendations based on empirical findings on document annotation and automatic vectorization, focusing on the example case of historical cadasters. Our recommendations are generic and easily applicable, based on a solid experience on concrete and diverse projects.
{"title":"Effective annotation for the automatic vectorization of cadastral maps","authors":"Rémi Petitpierre, Paul Guhennec","doi":"10.1093/llc/fqad006","DOIUrl":"https://doi.org/10.1093/llc/fqad006","url":null,"abstract":"\u0000 The great potential brought by large-scale data in the humanities is still hindered by the time and technicality required for making documents digitally intelligible. Within urban studies, historical cadasters have been hitherto largely under-explored despite their informative value. Powerful and generic technologies, based on neural networks, to automate the vectorization of historical maps have recently become available. However, the transfer of these technologies is hampered by the scarcity of interdisciplinary exchanges and a lack of practical literature destinated to humanities scholars, especially on the key step of the pipeline: the annotation. In this article, we propose a set of practical recommendations based on empirical findings on document annotation and automatic vectorization, focusing on the example case of historical cadasters. Our recommendations are generic and easily applicable, based on a solid experience on concrete and diverse projects.","PeriodicalId":45315,"journal":{"name":"Digital Scholarship in the Humanities","volume":"1 1","pages":""},"PeriodicalIF":0.8,"publicationDate":"2023-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42744553","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"文学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Digital remediation increasingly plays a pivotal role in delivering political messages. This study examines postings of corporeally mediated tattoos in a China-based blog, focusing on in what sense blogs can provide a breathing or even emancipating space for Chinese tattoo wearers and enthusiasts to control the viewer’s perceptions of tattooing and negotiate long-standing stigmatized associations of tattoos there. The study analyzes 305 postings collected from the blog covering a period between 24 April 2020 and 3 May 2021, taking a quantitative approach. Methodologically, it first analyses the distribution of the signs across body parts as displayed. By applying multimodal perspectives, this study also investigates photographic techniques such as distance, angle, gaze, and modality harnessed and exploited for visual manipulation during digital remediation of turning body narratives into digital narratives. Findings of the study suggest that digital remediation facilitates personal expression of tattoo wearers and photographic techniques play a critical role in introducing ready alignment of the viewer with the postings. The study thus adds quantitative inquiries to existing, mostly qualitative, studies of tattoos which usually rest on interviews with tattoo wearers, enthusiasts, and artists for an account of tattoo narratives in connection to personal expression and self-definition. Its findings would be inspiring to socially stigmatized and marginalized groups to circumvent social, cultural, and political barriers to communicate and make their stories heard to more people.
{"title":"Digital remediation and visual manipulation: Blogs as breathing spaces for Chinese tattoo wearers and enthusiasts","authors":"Songqing Li","doi":"10.1093/llc/fqad005","DOIUrl":"https://doi.org/10.1093/llc/fqad005","url":null,"abstract":"\u0000 Digital remediation increasingly plays a pivotal role in delivering political messages. This study examines postings of corporeally mediated tattoos in a China-based blog, focusing on in what sense blogs can provide a breathing or even emancipating space for Chinese tattoo wearers and enthusiasts to control the viewer’s perceptions of tattooing and negotiate long-standing stigmatized associations of tattoos there. The study analyzes 305 postings collected from the blog covering a period between 24 April 2020 and 3 May 2021, taking a quantitative approach. Methodologically, it first analyses the distribution of the signs across body parts as displayed. By applying multimodal perspectives, this study also investigates photographic techniques such as distance, angle, gaze, and modality harnessed and exploited for visual manipulation during digital remediation of turning body narratives into digital narratives. Findings of the study suggest that digital remediation facilitates personal expression of tattoo wearers and photographic techniques play a critical role in introducing ready alignment of the viewer with the postings. The study thus adds quantitative inquiries to existing, mostly qualitative, studies of tattoos which usually rest on interviews with tattoo wearers, enthusiasts, and artists for an account of tattoo narratives in connection to personal expression and self-definition. Its findings would be inspiring to socially stigmatized and marginalized groups to circumvent social, cultural, and political barriers to communicate and make their stories heard to more people.","PeriodicalId":45315,"journal":{"name":"Digital Scholarship in the Humanities","volume":" ","pages":""},"PeriodicalIF":0.8,"publicationDate":"2023-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48952364","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"文学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Love and Intrigue is an outstanding work by the German dramatist Friedrich Schiller. This work was initially titled Louise Millerin, which was changed to Love and Intrigue before its premiere. The title Louise Millerin indicates the importance of the female character Louise in the drama. However, is Louise the real protagonist of the drama? Existing research provided no definitive answer to this question. Scholars have not agreed on who the protagonist is in the drama and how to quantify the prominence of the character. To address these issues, this study adopts Social Network Analysis (SNA) to visualize the character network, quantify the centrality of the characters, and perform cluster analysis of the characters in Love and Intrigue. The results indicate that Ferdinand displays the highest prominence and has higher stability regarding centrality than Louise. We explore possible reasons behind the findings. First, the highlighting of the male character Ferdinand may reflect male dominance in the eighteenth-century Germany. Second, Schiller incorporated his personal experiences and emotional preferences into the writing of the drama, leading to his favor of Ferdinand. Third, Schiller may have also been influenced by the style of previous German playwrights. By applying SNA to literary research, this study presents a comprehensive and in-depth analysis of the characters in Love and Intrigue and contributes to the research on Schiller’s works.
{"title":"Louise or Ferdinand? Exploring the protagonists of Love and Intrigue using social network analysis","authors":"Nana Pang, Meng Sun, Haoran Zhu","doi":"10.1093/llc/fqad007","DOIUrl":"https://doi.org/10.1093/llc/fqad007","url":null,"abstract":"\u0000 Love and Intrigue is an outstanding work by the German dramatist Friedrich Schiller. This work was initially titled Louise Millerin, which was changed to Love and Intrigue before its premiere. The title Louise Millerin indicates the importance of the female character Louise in the drama. However, is Louise the real protagonist of the drama? Existing research provided no definitive answer to this question. Scholars have not agreed on who the protagonist is in the drama and how to quantify the prominence of the character. To address these issues, this study adopts Social Network Analysis (SNA) to visualize the character network, quantify the centrality of the characters, and perform cluster analysis of the characters in Love and Intrigue. The results indicate that Ferdinand displays the highest prominence and has higher stability regarding centrality than Louise. We explore possible reasons behind the findings. First, the highlighting of the male character Ferdinand may reflect male dominance in the eighteenth-century Germany. Second, Schiller incorporated his personal experiences and emotional preferences into the writing of the drama, leading to his favor of Ferdinand. Third, Schiller may have also been influenced by the style of previous German playwrights. By applying SNA to literary research, this study presents a comprehensive and in-depth analysis of the characters in Love and Intrigue and contributes to the research on Schiller’s works.","PeriodicalId":45315,"journal":{"name":"Digital Scholarship in the Humanities","volume":" ","pages":""},"PeriodicalIF":0.8,"publicationDate":"2023-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47338189","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"文学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract This article presents a study of several parallel corpora of historical languages and their translations. The aligned corpora are the result of a large crowdsourcing project, named Ugarit, aimed at supporting translation alignment for ancient and historical languages: the study of the resulting translation pairs allows us to observe cross-linguistic dynamics in a range of languages, some of which have never been systematically aligned before. The corpora considered are divided into two distinct groups: English translations of ancient languages, including Greek, Latin, Persian, and Coptic; and translations of ancient Greek into other languages, including Latin, English, Georgian, Italian, and Persian. We evaluated different ratios of word matching across each language pair (one-to-one, one-to-many, many-to-one, and many-to-many), and analyzed the resulting trends across the corpus. We propose some observations on how and why different types of alignment links are established in a given language pair, and what factors affect their creation beyond the control of the user: we propose two complementary hypotheses to explain the changes, one based on structural linguistic factors and the other based on cultural difference.
{"title":"To say almost the same thing? A study on cross-linguistic variation in ancient texts and their translations","authors":"Chiara Palladino, Tariq Yousef","doi":"10.1093/llc/fqac086","DOIUrl":"https://doi.org/10.1093/llc/fqac086","url":null,"abstract":"Abstract This article presents a study of several parallel corpora of historical languages and their translations. The aligned corpora are the result of a large crowdsourcing project, named Ugarit, aimed at supporting translation alignment for ancient and historical languages: the study of the resulting translation pairs allows us to observe cross-linguistic dynamics in a range of languages, some of which have never been systematically aligned before. The corpora considered are divided into two distinct groups: English translations of ancient languages, including Greek, Latin, Persian, and Coptic; and translations of ancient Greek into other languages, including Latin, English, Georgian, Italian, and Persian. We evaluated different ratios of word matching across each language pair (one-to-one, one-to-many, many-to-one, and many-to-many), and analyzed the resulting trends across the corpus. We propose some observations on how and why different types of alignment links are established in a given language pair, and what factors affect their creation beyond the control of the user: we propose two complementary hypotheses to explain the changes, one based on structural linguistic factors and the other based on cultural difference.","PeriodicalId":45315,"journal":{"name":"Digital Scholarship in the Humanities","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136197403","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"文学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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