Text Corpus Research Articles

Dystopian Visions and the Making of Privacy Law

This article explores the role of references to dystopian literature in the context of developing privacy laws. Drawing on a qualitative analysis of a large corpus of legislative and judicial texts from Germany and the United Kingdom, I demonstrate that references to popular dystopian works of fiction like Orwell’s 1984 have animated and shaped the legal recognition of privacy. Specifically, dystopian visions are evoked as reasons that warrant the legal protection of privacy rights. I explore lawmakers’ vision of a technologically empowered totalitarian state and discuss how these connect to historical, contemporary, and hypothetical examples of unjust regimes. I argue that literary imaginations of dystopia are often themselves built on historical experience, suggesting that the aptness for social critique is, as literary critics suggest, built into dystopia as a genre. I furthermore explore how the theme of democracy is employed as a counterpoint to fears of dystopian totalitarianism. Portraying privacy invasions as harmful to democratic ideals discursively amplifies their dangerousness—and thereby works to justify regulatory intervention. My research findings prompt us to view legal norms as a cultural artifact that reflect cultural imagination and literary narratives.

Research on Intelligent Mining Algorithm of English Translation Text Big Data Based on Deep Learning

This paper explores the translation of English texts by a deep learning algorithm, which aims to intelligently extract relevant records from a large corpus of English-translated texts, especially its shortcomings in processing difficult texts and dealing with long-term dependencies. This research integrates the modern long short-term memory (LSTM) network framework, with the aim of improving the accuracy and processing efficiency of the translation. Using a large number of experimental facts, these LSTM models are comprehensively learned and rigorously optimized. The traditional approach is to adapt the style to the language-specific properties of the translated text, and then use a bunch of evaluation metrics to evaluate the overall performance of the model across a large number of text types. The results of this study show that the method significantly speeds up the extraction and processing of information while maintaining the integrity at the translation level. In addition, the study reveals deep learning models’ ability to recognize complex contextual nuances and subtle formulations of language expression. The results of this research are multifaceted, bringing great improvements to device translation structures and facilitating the development of state-of-the-art text content analysis tools. These advances apply primarily to sectors of considerable statistical volume and complexity, including the criminal, scientific, and technological fields. Therefore, this study lays a foundation for future exploration of improving device understanding of language and automation of translation methods in various professional fields.

Konfiks Derivasi Per-/-an dalam Debat Capres-Cawapres Tahun 2024: Metode Linguistik Korpus

This research aimed to discuss the “per-/-an” confix which has undergone derivation in Indonesian. This research used the presidential and vice presidential candidate debate script number 01 as the research object studied. This research used a qualitative corpus linguistics approach. The corpus linguistic approach used in this research utilized the KORTARA (Korpus Nusantara) corpus linguistic application. The KORTARA corpus linguistic application (Korpus Nusantara) is an application that can help to collect, process and analyze linguistic data digitally. Data collection in this research utilized the affix word search feature to find specific data containing affixes. The affix word search feature was lasted by accessing the corpus menu in the KORTARA (Korpus Nusantara) application, then selecting the 2024 presidential-cawapres debate script as the object for research. Based on the research that has been carried out, 56 data were obtained on the use of the derivation confix per-/-an in the corpus of the 01 Presidential-Cawapres debate texts in 2024. The results of this research can have implications in the scientific field of morphology related to the principles of derivational development in Indonesian.

Research Topics and Trends in Gifted Education: A Structural Topic Model

Many articles have been published in gifted education in recent years. This study aims to provide a comprehensive review of the evolution of academic studies in gifted education. In this context, the structural topic modeling (STM) method was used to analyze the topics and trends in the field. STM is a machine learning technique that utilizes natural language processing techniques based on text mining. It is a valuable methodology for identifying a text corpus’s main topics and trends. The corpus used in this study is 5,127 articles from nine leading journals in giftedness without any year limitations. As a result of the analysis, five topics that prominently emerged in the literature were discovered. These are curriculum and instruction, social-emotional characteristics, thinking skills, identification and assessment tools, and equity and policies. The research topics and trends discovered due to the analysis are discussed within the literature framework, and recommendations are presented.

The anthropomorphic pursuit of AI-generated journalistic texts: limits to expressing subjectivity

Many newsrooms around the world are increasingly turning to artificial intelligence (AI) algorithms to generate journalistic content. Often, these machine-generated texts are distributed without being clearly identified as synthetic or hybrid. Since the launch of ChatGPT in late 2022, the tool’s extraordinary ability to mimic human language has been widely celebrated. Given that subjectivity is an integral part of human language, this study examines how different texts generated using AI tools are imbued with subjective features in order to anthropomorphize their linguistic content. Our aim is to gain insight into the ways in which these texts express subjectivity in order to appear anthropomorphic, as well as the limits of this expression and its implications for communication. To this end, a corpus of AI-generated journalistic texts published in various media, as well as texts created using AI tools such as ChatGPT and Gemini, is analysed to assess these tools’ capabilities. Ten criteria are used to characterize the expression of subjectivity in journalistic discourse on the surface of texts and in terms of situational appropriateness. The results show that AI tools can incorporate subjective markers on the text surface, but have important limitations when it comes to situational appropriateness, making it difficult to imitate certain features of journalistic writing. The paper also discusses the implications of asymmetrical audience interaction with machines that simulate human characteristics, and the varying degrees of opacity and transparency with which AI is used in newsrooms.

Using ChatGPT and determinologisation to enhance understanding of lung cancer information

Abstract Lung cancer is associated to high mortality rates and has a large impact on the quality of life of patients and families, who therefore need suitable information to deal with the situation. However, information provided by health services is often not adapted to lay users and retains a considerable number of technicalities that impair comprehensibility. Accessibility, a concept receiving increasing attention, not only involves physical access but also understanding relevant information when it comes to the medical setting. One of the main intralingual translation procedures used to adapt specialised text is determinologisation, which comprises strategies like using common-speech synonyms, explanations, examples, etc. Recent artificial intelligence generative models offer a promising tool to produce texts at different specialisation levels. In this study, we evaluated the capacity of ChatGPT for determinologisation of terms extracted from a corpus of patient-oriented lung-cancer texts and compared the results with reliable patient-oriented online sources. ChatGPT produced definitions and context information similar to those of the online sources in a very short amount of time. However, both the choice of suitable input prompts and the post-edition process necessary to produce quality final texts on lung-cancer information still required the supervision of human experts.

Textual studies of the era of big data and neural networks

This article analyses the emergence of new technologies for working with big data which can be highly helpful to philologists, studying the diachronic development. First of all, that applies to the study and publication of Old Russian manuscripts with traditional liturgical texts used for church service. These manuscripts existed in a huge number of folios, and in the process of copying were subjected to considerable textual unification. That makes it very difficult to study them by the laborious methods of traditional textual criticism. Now, when the full text of the monuments can be automatically processed, the creation of the Linguistic intellectual environment (LIE) has been lounged. This tool will provide new opportunities for the study of Slavonic liturgical texts from different historical periods. As a result, we will create a corpus of liturgical texts of the 11th–17th centuries, obtained using a program for automatic text recognition of manuscripts, with annotation und search module. The user of the LIE will be able to receive a complete list of variant readings for each fragment of a liturgical book of the widest range of manuscripts. In fact, we are talking of a new type of publication of traditional liturgical texts, when the user can set the parameters for the edition in accordance with his research interests.

Claiming rock art, claiming indigeneity: Spaces and scales of recognition in Khoe and San identity claims

Based on research conducted in South Africa, this work revolves around the observation that certain rock art sites (Wildebeest Kuil, Northern Cape; Game Pass Shelter, KwaZulu-Natal) are utilized within identity and political frameworks—and a question: what role do rock art sites play in the construction of Khoe and San indigeneity? Contemporary indigeneity is closely linked to issues of recognition, which are themselves related to the restitution of rights, objects, and knowledge. Acknowledging the central role of objects in identity claims, this article proposes to analyze the place of these two rock art sites in the political construction of Khoe and San indigeneity. Based on a corpus of interviews, observations, legal texts, and press articles, certain uses of rock art sites will be presented as strategic means within a broader context of claims.

Structural reading: Developing the method of Structural Collocation Analysis using a case study on parliamentary reporting

To analyze large, digitized corpora, we introduce the new approach of “structural reading”, which combines the abstraction of distant reading with the nuance of close reading. We do so by developing the method of “structural collocation analysis” (SCA) that uses metadata categories to investigate how research topics behave across texts belonging to different categories. The method combines the robustness of traditional collocation analysis with the structural dimension of structural topic modeling, bridging corpus linguistics and text mining. SCA enables us to gain novel insights from existing corpora to shed new light on long-standing historical debates. We exemplify this method through a case study on the history of parliamentary reporting, using digitized British parliamentary proceedings. We discovered that discussions on parliamentary reporting were not dominated by a particular political party, but rather by senior MPs and MPs from urban areas – two categories we call “political insiders”. Metadata-based distinctions between different types of politicians thus enabled us to provide new perspectives on the history of parliamentary reporting.

SUBDIALECTAL DISCOURSE AND PECULIARITIES OF ITS MENTAL CONTINUUM IN THE LENS OF THE MODERN LINGUISTIC PARADIGM

The article is devoted to the study of specific features of subdialectal discourse and its mental continuum, viewed through the prism of modern linguistic theories. The purpose of the research is to study and describe the functioning and structure features, as well as the specifics of the linguarium of subdialectal discourse. The object of the study is the subdialectal discourse, which covers speech practices recorded in the village of Pishchanyi Brid, Novoukrainskyi district, Kirovohrad region. The subject of the study is the mental continuum of the subdialect speakers, which includes knowledge, perceptions and assessments related to various aspects of their lives. The source of the study was the speech recordings of the native speakers, i.e. the textual corpus of the subdialect. The methods used in the study were modelling, hypothetical method, deductive and inductive methods, descriptive method, observation method, taxonomic method, and continuous sampling method. The peculiarity of the study of subdialectal speech in discourse studies lies in the analysis of the composition of usages, the specifics of the composition of the linguarium and its influence on the structure of discourse, expression of thoughts, interaction of speakers and the formation of the ethnographic identity of peasants who speak the subdialect. The discourse approach allows us to better understand the speech process in a specific socio-cultural and geographical setting, as well as the interaction of speakers within the dialect environment. It involves analysing the discourse of the language group in question, identifying specific lexical, grammatical and phonetic features that are characteristic of certain socio-cultural groups. The metalinguistic interpretation of discourse types in the linguistic paradigm presents dialectal discourse as a reflection of real language use, a set of idiolects and an indicator of changes in the language. The household, ceremonial, religious and existential knowledge contained in the dialect discourse is critical to the well-being and cultural integrity of rural communities. In particular, household knowledge encompasses practical skills in housekeeping, agriculture and crafts. Ceremonial and religious knowledge includes traditions, rituals and beliefs that support the spiritual life and cultural identity of the community, and existential knowledge is related to the understanding of life, death and moral values, helping community members navigate difficult life situations. Prospects for the study include a meta-analysis of dialectal discourse, which can be expressed in different ways in individual subdialects, the development of new methods for studying dialectal language in the digital environment, and the integration of interdisciplinary approaches for a deeper understanding of speech practices and cultural characteristics of speakers.

A comprehensive review of existing corpora and methods for creating annotated corpora for event extraction tasks

Abstract Purpose The purpose of this study is to serve as a comprehensive review of the existing annotated corpora. This review study aims to provide information on the existing annotated corpora for event extraction, which are limited but essential for training and improving the existing event extraction algorithms. In addition to the primary goal of this study, it provides guidelines for preparing an annotated corpus and suggests suitable tools for the annotation task. Design/methodology/approach This study employs an analytical approach to examine available corpus that is suitable for event extraction tasks. It offers an in-depth analysis of existing event extraction corpora and provides systematic guidelines for researchers to develop accurate, high-quality corpora. This ensures the reliability of the created corpus and its suitability for training machine learning algorithms. Findings Our exploration reveals a scarcity of annotated corpora for event extraction tasks. In particular, the English corpora are mainly focused on the biomedical and general domains. Despite the issue of annotated corpora scarcity, there are several high-quality corpora available and widely used as benchmark datasets. However, access to some of these corpora might be limited owing to closed-access policies or discontinued maintenance after being initially released, rendering them inaccessible owing to broken links. Therefore, this study documents the available corpora for event extraction tasks. Research limitations Our study focuses only on well-known corpora available in English and Chinese. Nevertheless, this study places a strong emphasis on the English corpora due to its status as a global lingua franca, making it widely understood compared to other languages. Practical implications We genuinely believe that this study provides valuable knowledge that can serve as a guiding framework for preparing and accurately annotating events from text corpora. It provides comprehensive guidelines for researchers to improve the quality of corpus annotations, especially for event extraction tasks across various domains. Originality/value This study comprehensively compiled information on the existing annotated corpora for event extraction tasks and provided preparation guidelines.

Characterizing pituitary adenomas in clinical notes: Corpus construction and its application in LLMs.

Objective: Faced with the challenges of differential diagnosis caused by the complex clinical manifestations and high pathological heterogeneity of pituitary adenomas, this study aims to construct a high-quality annotated corpus to characterize pituitary adenomas in clinical notes containing rich diagnosis and treatment information. Methods: A dataset from a pituitary adenomas neurosurgery treatment center of a tertiary first-class hospital in China was retrospectively collected. A semi-automatic corpus construction framework was designed. A total of 2000 documents containing 9430 sentences and 524,232 words were annotated, and the text corpus of pituitary adenomas (TCPA) was constructed and analyzed. Its potential application in large language models (LLMs) was explored through fine-tuning and prompting experiments. Results: TCPA had 4782 medical entities and 28,998 tokens, achieving good quality with the inter-annotator agreement value of 0.862-0.986. The LLMs experiments showed that TCPA can be used to automatically identify clinical information from free texts, and introducing instances with clinical characteristics can effectively reduce the need for training data, thereby reducing labor costs. Conclusion: This study characterized pituitary adenomas in clinical notes, and the proposed method were able to serve as references for relevant research in medical natural language scenarios with highly specialized language structure and terminology.

Adoption of Life Cycle Thinking: Impact-driven comparative assessment of Japanese construction corporations’ trends in practices

Although life cycle thinking offers a well-founded set of concepts, methods, and tools for organizational contexts, only little is known about its relevance in the construction sector. In this sector, construction corporations are key players. In this work, a novel impact-driven method to assess the adoption of life cycle thinking by construction corporations is introduced. Japan, as a high-income country with a relatively long history of environmental policies informed by material flow analysis, is chosen as the context. Five Japanese construction corporations and respective reporting are used as case studies. Trends in environmental impacts over time of the case study corporations are assessed using two indicators: resource and carbon productivity. In comparison, an automated text corpus analysis workflow is presented to explore the corporate report’s life cycle thinking-related content in a meaningful way. Comparing the period of 2014–2018 and 2019–2023, an overall relative increase in framework adoptions (77%) and their integration in corporate categories (85%) in corporate reports indicates its increased procedural relevance among Japanese construction contractors. Findings show how the carbon indicator is embedded in various frameworks and, for instance, reveal an increased relevance of Scope 3 emissions as a framework on a low level. However, Scope 3 is also utilized as a performance indicator. To this end, considerable temporal differences in adoption practices are observed. Finally, a potentially effective corporate adoption model is identified through the comparative research design. The proposed method can be applied to other construction corporations and regional contexts.

Produktverpackungen als alltägliche Manifestationen des Umweltdiskurses

The article outlines the technical, semiotic and discourse-linguistic challenges that arise in the data collection, the data processing and the data analysis of a quite small corpus of current product packaging texts (food/beverages, cleaning agents and hygiene products) of a running DFG-project. These three types of problems are due to the materiality, multimodality and multithematicity of the material analysed. The project which is focused on the German environmental discourse 1990-2020 and which is investigating the tension between individual freedom and social norms expressed in it, thus deliberately leaves the big data level of the originally project context within a bigger research group and switches to the level of hermeneutic-qualitative analyses of selected key texts. The hypothesis underlying this decision is that the environmental discourse is reflected in a condensed form in texts that are committed to corporate sustainability communication and are influencing the discourse space of everyday life in everyone’s household. Initial insights into the material and multimodal nature of the corpus are provided and the first results of the discourse linguistic analysis are offered, whereby the material is always discussed in its special significance "beyond big data". The preliminary results show that the everyday products analysed here are discursive mediators between companies, consumers and the environment, in that responsibility is shifted and displaced several times so that in the end it can to be concluded on all sides: Good for you and good for the planet.

Harvesting Ancient Wisdom: Mathematical Modeling of Agricultural Technology in Sangam Literature and its Comparative Study with Modern Techniques

Agriculture has been the backbone of human civilization since its inception. While modern technology has revolutionized agricultural practices, the ancient texts of the Tamil literary corpus, particularly the Sangam literature, offer invaluable insights into the agricultural techniques and wisdom of the past. This essay delves into the agricultural practices detailed in the Sangam texts, namely Naṟṟiṇai, Kuṟuntokai, Aingurunūṟu, Patiṟṟuppattu, Paripāṭal, Kalittokai, Akanāṉūṟu, and Puranāṉūṟu, and uses mathematical modeling, specifically simplex methods, to analyze and compare these techniques with contemporary agricultural technology.

Do discurso à ação política: análise de acontecimentos extremistas que violam uma ética discursiva

In this article, we reflect on aspects of the relationships between discourse, action, and ethics in the Brazilian political arena. These relationships were examined from theoretical perspectives based on the integration of discursive, phenomenological, and cognitive studies. We highlight the approaches of Ricoeur (1988) and Paveau (2015), particularly the notions of the discourse of action, ethically qualified action, and discursive ethics/virtue. These notions provided a conceptual and analytical framework for the analysis of two extremist events from protests against the outcome of the 2022 presidential elections, illustrating our political context characterized by the rise of the far-right and attacks against the Democratic Rule of Law. Methodologically, we selected a corpus of texts (such as memes, cartoons, photographs, statements, communications and a petition), which address and problematize these two events, shaping forms of metadiscourses with moral axiological nature. These metadiscursive statements were qualitatively analyzed based on their description and interpretation in light of the aforementioned notions.

Development of an Automated Label Data Entry System from Herbarium Specimen Images at Hyogo Herbarium (HYO)

We would like to introduce our recently developed systems for taking images of herbarium specimens and for the automatic extraction of data from specimen labels at the Herbarium of the Museum of Nature and Human Activities, Hyogo, Japan (HYO). Firstly, we designed a low-cost, but high-quality specimen imaging system for non-professional photographers to obtain images rapidly (Takano et al. 2019). Our system uses a mass-produced, mirrorless single-lens reflex (SLR) camera (SONY ILCE6300) with a zoom lens (Samyang Optics SYIO35AF-E35 mm F/2.8). We made a photo stand by ourselves to reduce costs. In addition, we have adopted an LED (light-emitting diode) lighting system with high color rendering. This imaging system has been introduced, with some improvements or adjustments for available space, to various herbaria in Japan (e.g., University of Tokyo (TI), Kyoto University (KYO)), contributing to the digitization of herbarium specimens across Japan. Next, we developed a system to extract label information from specimen images. The specimen image was uploaded to Google OCR and data were extracted in the form of text. Uploading the whole specimen image decreased the reading accuracy of the software because the plant images behaved as OCR (Optical Character Reader) noise. Therefore, the label part was cut out from the whole specimen image by using D-Lib*1 and uploaded to tesseract OCR*2 for OCR extraction of the label information (Aoki 2019, Takano et al. 2020). When installing this system for HYO, we designed it as an application accessible externally via the internet, which proved very useful during the coronavirus pandemic: part-time workers checked and conducted label data input from home. Finally, we decided to develop a system that would automatically label the text data extracted by OCR and input them into the appropriate cells of the database. Even though the text data could be extracted from specimen images, it needed a human to input them into the database. Therefore, we adopted Named Entity Recognition (NER), a system that extracts named entities such as place names, identifying proper nouns from unstructured text data. It enables information recorded in herbarium specimens to be tagged as named entities. We tried text matching at first, but the result was not satisfactory, so we started to use machine learning instead. We compared three natural language libraries for Japanese: BERT (Bidirectional Encoder Representations from Transformers), Albert (A Lite version of BERT), and SpaCy. Despite BERT and SpaCy returning similarly high f-scores (indicating good performance), we decided to use SpaCy because it runs better on ordinary PCs or servers. With sufficient machine learning after the creation of a text corpus (a specialised dataset) specific to labels on herbarium specimens, we successfully developed the application. The project files are available on GitHub*3 (Takano et al. 2024). We then examined whether this system could be applied to non-plant specimen images, i.e., fishes or birds, and found that it could efficiently extract data. Therefore, we decided to publicize this system on the cloud server and share it with other natural history museums in Japan*4. Curators can obtain a unique ID and password and upload specimen images from their collection to extract label data. The digitization of natural history collections in Japan has been long behind other countries, and this system will help to accelerate it. The system mentioned above is specialized for the natural history collections of Japan, but we believe it is possible to build similar programs in other countries, and we hope our experience will contribute to the mobilization of the world’s natural history collections.

It Is Time to Take Complaints Seriously? An Exploratory Analysis of Communications Sent by Users to a Public Healthcare Agency before, during and after the COVID-19 Pandemic

Taking due account of users’ perspectives is crucial for improving the quality of healthcare services. This study aimed to analyse the representations and evaluation criteria that users of a public health agency express towards care and treatment services and to explore whether and how the content and meaning of their communications varied according to pre-pandemic, pandemic or post-pandemic periods. A total of 501 communications sent to the public relations office of an Italian health agency were collected. An automatic content analysis procedure was applied to the textual corpus. Four main thematic cores were identified concerning the request for care and respect, the value of the doctor–patient relationship and the difficulties in contacting services and accessing care. Two main latent dimensions of meaning were identified, which capture the dialectic between the demand for relationships and the demand for access to care, and between attention to the relational competence of health workers and attention to the needs and rights of users. Communications collected during the pre-pandemic and post-pandemic periods mainly concern the difficulty of access to care; those collected during the pandemic period mainly concern the doctor–patient relationship. Interpersonal aspects and timely access to care appear to be crucial in users’ assessment of the quality of care.

Ultimate Fantasy. Subwersyjne strategie queerowania Sztucznej Inteligencji w projektach transliterackich

This article describes artistic examples of queering Artificial Intelligence (AI), which can be understood as a practice that challenges the (hetero)normative nature of neural networks by implementing a queer perspective. The evaluation of ways in which AI reflects societal norms is conducted by addressing biases that disproportionately affect marginalized communities. On this basis, the author highlights the need for inclusive practices that make it possible for queer experiences to be represented by technology while also discussing why AI cannot be neutral. The in-depth study of Ultimate Fantasy, a collection of literary texts generated by a Queer AI, reveals how artists use language models in novel, subversive, and possibly liberating ways. The author aims to frame this practice as an example of a queer utopian aesthetic project in accordance with José Muñoz’s understanding of queerness. The various motifs evident in the short story collection – such as queer modes of love or trauma – are analyzed as reflections of themes present in the corpus of queer texts used to train the language model.

Media Representation of Tutoring as a Phenomenon of Pedagogical Discourse

The aim of this study is to explore the media representation of tutoring as a phenomenon within pedagogical discourse. An analysis of a thematic corpus of texts reveals that the imported concept of TUTORING acquires new conceptual features that reflect the linguistic and cultural specificity of its interpretation in the Russian-speaking media landscape. Distinctive characteristics of the media representation of the conceptual education of TUTOR are established in comparison with traditional pedagogical professions and its definition in professional standards. It is demonstrated that in the Russian-speaking media discourse, tutoring is perceived by the professional discursive community as a profession of the future, tasked with shaping individuals capable of addressing the global challenges of modernity. Evaluative characteristics of the phenomenon of TUTORING are identified, reflecting its perception by both the professional discursive community and a broader readership. In the former case, positive evaluations prevail, characterized by notions of ‘assistance’ and ‘support’; in the latter, negative evaluative traits emerge, associated with skepticism towards tutoring. Figurative-perceptual characteristics of tutoring are presented, expressed through metaphorical strategies based on source domains such as “Sport,” “Journey,” and “Nature.” The study of the phenomenon of tutoring underscores the significance of the discursive factor in understanding the concept.