Text Types Research Articles

A multi-dimensional analysis of corporate blogs

Abstract Using a corpus-based multi-dimensional analysis, this study investigates the linguistic features and variation of corporate blogs from four industries: Service industry, the Wholesale and Retail Trade industry, the Manufacturing industry, and Information industry. The primary goal of this study is to examine the linguistic variation in corporate blogs from different industries. The data used for the current study is a 570,745-word corpus consisting of 995 textual posts from 40 top-ranked corporate blogs. In the multi-dimensional analysis, 67 linguistic features in the corpus are tagged, counted and normalized by using a Multidimensional Analysis Tagger (MAT). We imported the output files containing relevant statistical information from the MAT and then to SPSS 25.0 for a further t-test analysis. Overall, the corporate blogs are closest to the text type of general narrative exposition. The study finds that, as a hybrid genre, corporate blogs are basically informationally dense, non-narrative, interactive, and contextually independent. There are some statistically significant differences between four sub-corpora in corporate blogs. In particular, the Wholesale & Retail Trade sub-corpus is the most distinctive one that is significantly different from others on many dimensions, characterized by giving instructions, or telling stories, rather than persuading their audiences to do something.

GenAI and Socially Responsible AI in Natural Language Processing Applications: A Linguistic Perspective

It is a widely-accepted fact that the processing of very large amounts of data with state-of-the-art Natural Language Processing (NLP) practices (i.e. Machine Learning –ML, language agnostic approaches) has resulted to a dramatic improvement in the speed and efficiency of systems and applications. However, these developments are accompanied with several challenges and difficulties that have been voiced within the last years. Specifically, in regard to NLP, evident improvement in the speed and efficiency of systems and applications with GenAI also entails some aspects that may be problematic, especially when particular text types, languages and/or user groups are concerned. State-of-the-art NLP approaches with automated processing of vast amounts of data in GenAI are related to observed problematic Aspects 1-7, namely: (1) Underrepresentation, (2) Standardization. These result to (3) Barriers in Text Understanding, (4) Discouragement of HCI Usage for Special Text Types and/or User Groups, (5) Barriers in Accessing Information, (6) Likelihood of Errors and False Assumptions and (7) Difficulties in Error Detection and Recovery. An additional problem are typical cases, such as less-resourced languages (A), less experienced users (B) and less agile users (C). A hybrid approach involving the re-introduction and integration of traditional concepts in state-of-the-art processing approaches, whether they are automatic or interactive, concerns the following targets: i), (ii) and (iii): Making more types of information accessible to more types of recipients and user groups (i), Making more types of services accessible and user-friendly to more types of user groups (ii), Making more types of feelings, opinions, voices and reactions visible from more types of user groups (iii) Specifically, in the above-presented cases traditional and classical theories, principles and models are re-introduced and can be integrated into state-of-the art data-driven approaches involving Machine Learning and neural networks, functioning as training data and seed data in Natural Language Processing applications where user requirements and customization are of particular interest and importance. A hybrid approach may be considered a compromise between speed and correctness / userfriendliness in (types of) NLP applications where the achievement of this balance plays a crucial role. In other words, a hybrid approach and the examples presented here target to prevent mechanisms from adopting human biases, ensuring fairness and socially responsible outcome and responsible Social Media. A hybrid approach and the examples presented here also target to customizing content to different linguistic and cultural groups, ensuring equitable information distribution. Here, we present characteristic examples with cases employing the re-introduction of four typical types of traditional concepts concerning classical theories, principles and models. These four typical classical theories, principles and models are also not considered to be flawless, however they can be transformed into practical strategies that can be integrated into evaluation modules, neural networks and training data (including knowledge graphs) and dialogue design. The proposed and discussed re-introduction of traditional concepts is not limited only to the particular models, principles and theories presented here. The first example concerns the application of a classic principle from Theoretical Linguistics. The concept employed in the second example concerns a model from the field of Linguistics and Translation. The third and the fourth examples demonstrate the interdisciplinary application of models and theoretical frameworks from the fields of Linguistics-Cognitive Science and Linguistics-Psychology respectively.

Do Reading Goals Make a Difference for Refutation Text Effectiveness?

Refutation texts seem to be a promising approach to counter misconceptions. They provoke a cognitive conflict by explicitly naming a misconception and correcting it with a scientific explanation. However, the literature reports mixed findings about their effectiveness, underlining the need to examine potential moderators. For example, when presenting preservice teachers a refutation text to combat an educational myth, the instructed reading goal might be of importance because reading goals can affect how readers process a text. In this study, we examined whether reading goals influence the effect of refutation texts and facilitate belief change about an educational myth in preservice teachers. The preregistered experiment (N = 168) followed a 2 × 2 × 2 mixed design with the between-participants factors text type (refutation vs. traditional) and reading goal (explanation vs. entertainment), and the within-participants factor time (before vs. after reading). Participants who had read a refutation text rather than a traditional text were more likely to change their false belief. However, the refutation effect was independent of participants’ reading goals. These results strengthen existing evidence that refutation texts are better suited for addressing misconceptions than traditional textbooks. However, we still require a better understanding of the conditions that increase refutation text effectiveness.

Jane Austen’s Will – and Those of the Two Cassandras

ABSTRACT As a follow-up to my (linguistic) close-reading of Jane Austen’s Will, this paper analyses the Wills of her mother and sister, Cassandra Austen-Leigh and Cassandra Elizabeth Austen. The dates of these Wills as well as their contents demonstrate the particular concerns of these two testators, both in drawing up legally valid documents and to make sure that their – eventually – not inconsiderable possessions would go to the right legatees. In doing so, the (invalid but nevertheless officially proved) Will of their famous family member set an important example. At the same time, the contents of the Wills, and especially the one by Cassandra, show consideration with the needs of unmarried – or otherwise husbandless – women that were part of their social network, friends as well as dependants. This consideration reveals awareness of the existence of a parallel social world to that described by Jane Austen in her novels, where women who would not or could not marry gained some financial security through their relatives’ Wills. Following up references to people mentioned in the Will, such as the daughter of Henry Austen’s housekeeper, Mary Perigord, moreover, demonstrates the importance of Late Modern English Wills as an insufficiently explored text type.

Plotting Against Plausibility: Toward a Poetics of the Improbable

ABSTRACT The concept of probability has been central to narrative poetics since before the time of Aristotle. By contrast, non-probabilistic types of narrative have largely been ignored or treated as misguided or sadly failed attempts at probabilistic stories. The history of literature, however, includes several distinct types of non- or anti-probabilistic narrative, all of which have been in existence for centuries. This article identifies four types of text that suspend, supersede, ignore, or travesty probabilistic concerns; examples of these are, respectively, the romance, supernatural works, apologues, and many absurdist dramas and postmodern fictions. Especially compelling in this context are the works, by a variety of authors including Aristophanes, Oscar Wilde, Eugene Ionesco, and Tom Stoppard, that mock the very idea of a probabilistic order of events. This article goes on to analyze how such works sequence narratives once the framework of probability is removed.

Специфика языковой реализации жанра обращения руководства в годовом отчете (на материале русского языка)

The article is carried out within the framework of the analysis of institutional business discourse and is devoted to the problem of genres in corporate communication. The paper aims to reveal structural-linguistic and communicative-pragmatic peculiarities of the genre of top-managers’ message in the annual report in Russian language. The article considers the genre as an open and flexible scheme in a prototypical model with different frequency of elements. More and less typical sets and narrative schemes are described, which make it possible to establish genre relatedness in the type of text under study. Typical speech patterns and their sequences are also established. The scientific originality of the study lies in the fact that the change in the genre-forming factors of the top-managers’ message in annual reports belongs to one of the insufficiently developed areas in Russian linguistics. In this regard, for the first time an integrated approach to the linguistic analysis of this genre has been implemented on the Russian material. As a result of the analysis, it was revealed that the elements of the genres of business letter and report are the most frequent in the type of text under analysis. It has been established that the category of addressee serves to vary the distance between communicants. It is also demonstrated that the described discursive practices of constructing written speech in the top-managers’ messages in annual reports of Russian companies are due not only to the informing, but also to the argumentative function.

Preservation of sentiment in machine translation of low-resource languages: a case study on Slovak movie subtitles

AbstractThis research explores the effectiveness of machine translation from Slovak to English for sentiment analysis, specifically focusing on the translation of movie subtitles. The study employs a parallel corpus of segmented movie subtitles in both languages and utilizes IBM Watson™ Natural Language Understanding service and Google Translate. The research aims to assess the correlation between human-generated text and machine-translated text in sentiment analysis. A comparative analysis was also conducted using OpenAI to evaluate the sentiment of the Slovak text directly, without translation into English. The findings reveal a strong correlation between human text and machine translation, with a Pearson correlation coefficient of 0.86, and a correlation with OpenAI’s GPT model evaluation at 0.72. Despite the relatively high accuracy of the end-to-end solution using OpenAI, the methodology comprising machine translation followed by sentiment analysis in English was found to be significantly more precise. The research further investigates the challenges in translating specific language nuances, such as humor and vulgarism, and their impact on sentiment analysis. The study concludes that machine translation can be effectively used for sentiment analysis in Slovak, a flective language, and highlights the potential of advanced language models in low-resource languages. Future research directions include expanding the study to other text types and comparable languages beyond Slovak.

“Stumbling blocks” in the translation of technical documentation

The objective of this study is to clarify the notion of “technical documentation” and explore the challenges and strategies involved in translating this type of text. Technical documentation is crucial in helping customers understand how to use the product effectively that is why it should be well-structured, allowing users to find the information they need quickly and easily. Examples of technical writing include technical manuals, operating instructions, scientific books, monographs, academic papers and articles, and patent translations. However, several obstacles can impede the translation process, potentially resulting in inaccuracies or misunderstandings. Common translation difficulties include untranslatable words, multiple-word meanings, differences in grammatical and syntactic systems, technical and specialized terminology, and “false friends.” The process of translation of such texts is intricate, involving the transfer of information from one language to another while considering cultural, linguistic, and contextual factors. While translating technical texts, the translator may encounter various obstacles, such as linguistic challenges, source text issues, expertise gaps, and realia. Improving the effectiveness of translating technical documentation involves a combination of best translation practices. Effective communication and collaborative efforts are crucial elements for project success. It is also important for professional translators to be vigilant and use the right resources to avoid common pitfalls and deliver high-quality. By combining these strategies, you can enhance the efficiency and accuracy of translating technical documentation, ensuring that the information is effectively communicated to a global audience.

The Potential of Narrative for Understanding Protein Biosynthesis in the Context of Viral Infections

The Potential of Narrative for Understanding Protein Biosynthesis in the Context of Viral Infections

XTime: A general rule-based method for time expression recognition and normalization

Time expression (a.k.a., timex) recognition and normalization (TERN) is a crucial task for downstream research. However, previous studies have overlooked the critical characteristics of timexes that significantly impact the task. To gain deeper insights, we conduct an analysis across four diverse English datasets to examine the key attributes of timex constituents. Our analysis reveals several noteworthy observations, such as: timexes tend to very short; the majority of timexes contain time tokens; there exist strong mapping relationships between time tokens and timex types; there exists a priority relationship among timex types; and timex values exhibit only some standard formats. Based on these insights, we propose a novel general rule-based method termed XTime11Source codes and datasets are available at https://github.com/xszhong/XTime. to recognize timexes from free text and normalize them into standard formats. Notably, XTime’s rules are designed in a general and heuristic manner, enabling its independence of diverse domains and text types. Experimental evaluations conducted on both in-domain and out-of-domain English datasets demonstrate that XTime consistently outperforms or performs comparably to representative state-of-the-art methods.

Νέοι εκπαιδευτικοί, νέες συνθήκες και νέα εργαλεία για την εκπαίδευση παιδιών με μεταναστευτικό και προσφυγικό υπόβαθρο

The main objective of the Language Curriculum is to make the educational system responsive to the new conditions that have emerged in schools. Considering the requirements of the Curricula, new learning tools were used in this research and were applied in the context of language teaching at primary schools at the Department of Primary Education, University of the Aegean. These tools included a combination of theories, i.e. Cummins' (2005) theory for the development of Academic Language Proficiency, approaches about New Learning (Kalantzis & Cope, 2005) and Transformative Pedagogy (Cummins, 2005; Kalantzis & Cope, 2013). The aim of the research was for future teachers to learn how to support the multilingual students in schools in critically processing the diverse textual types in the language lessons, thereby achieving both the development of linguistic and communicative competence and the interaction of the school community with the wider society.

Flicker and reading speed: Effects on individuals with visual sensitivity.

Flicker and patterns of stripes in the modern environment can evoke visual illusions, discomfort migraine, and seizures. We measured reading speed while striped and less striped texts were illuminated with LED lights. In Experiment 1, the lights flickered at 60 Hz and 120 Hz compared to 60 kHz (perceived as steady light). In Experiment 2, the lights flickered at 60 Hz or 600 Hz (at which frequency the phantom array is most visible), and were compared to continuous light. Two types of text were used: one containing words with high horizontal autocorrelation (striped) and another containing words with low autocorrelation (less striped). We measured the number of illusions participants saw in the Pattern Glare (PG) Test. Overall, reading speed was slowest during the 60 Hz and 600 Hz flicker and was slower when reading the high autocorrelation text. Interestingly, the low PG group showed greater effects of flicker on reading speed than the high PG group, which tended to be slower overall. In addition, reading speed in the high PG group was reduced when the autocorrelation of the text was high. These findings suggest that uncomfortable visual environments reduce reading efficiency, the more so in individuals who are visually sensitive.

Deteksi Cyberbullying Menggunakan BERT dan Bi-LSTM

Cyberbullying is a digital problem that is not a new phenomenon. This existed before the advent of social networks, and cyberbullying has a wide impact, including a person's mental and physiological conditions such as sadness, anxiety and depression. The main objective of this research is to develop an effective cyberbullying detection system using natural language processing techniques. The method used in this research includes the application of the BERT (Bi-Directional Encoder Representations from Transformers) and Bi-LSTM (Bi-Directional Long Short-Term Memory) models as a deep learning approach to analyze text and detect cyberbullying behavior. This approach allows the system to understand complex language contexts and capture patterns that traditional methods may find difficult to identify. Testing was carried out using a dataset that included various types of Indonesian language texts containing cyber bullying acts. The research results show that the combination of BERT and Bi-LSTM is able to provide superior detection performance with a high accuracy rate of 90% and the ability to identify variations of cyber bullying. This research makes a significant contribution to efforts to protect individuals from the negative impacts of cyber bullying through the development of a sophisticated and adaptive detection system.

Conducting L2 listener verbal reports: Common missteps by novice researchers and ways to address them

We have conducted second language (L2) listener verbal reports (VRs) for many years, and during that time have also advised or trained colleagues and research assistants to use these VRs. Based on these experiences, this article outlines various common missteps we and our trainees have made in conducting the VRs and how these missteps were, or could be, addressed. Through this approach, we provide advice to novice researchers planning to use this method to study L2 listeners. This advice is given as a series of recommendations in the following areas: the type of texts to use in the VR and how to select and trial them beforehand; how to prepare the participants for their VR; the language to use in the VR (L1 or L2); and procedural advice when conducting the VR. In addition, there's an extended section advising on the use of researcher questions to help elicit information from the participants about their listening behaviors during the VR. This is followed by advice on how to generally help train a novice researcher to conduct listener VRs. The article concludes by identifying some possible future research directions for addressing validity threats to listener VRs.

Representation of neurodivergence in fiction books: exploring neurodivergent young peoples' perspectives

AbstractIn recent years, there has been growing awareness of the importance of representation in fiction books, to ensure all children and young people can see themselves reflected in what they read. Much of this work has focused, importantly, on increasing ethnic representation, yet there has been much less exploration of the representation of other minority experiences, such as those of neurodivergent young people, and how these are perceived by neurodivergent young people themselves. This article provides new insights into neurodivergent young people's perceptions of representation of neurodivergence in fiction books (and other text types) based on semi‐structured interviews with 16 neurodivergent young people (aged 14 to 17 year olds) from 2 high schools in Scotland. Using an inductive data‐driven thematic analysis process, three themes were identified: (1) representation of neurodivergence should be complex, realistic, and positive; (2) representation of neurodivergence should be normalised; (3) representation of neurodivergence beyond books is important. Each of these themes is explored in detail, followed by implications for future research, practice and the publishing of Young Adult fiction.

사회복지관 사례관리의 일 조직화에 대한 제도적 문화기술지

The purpose of this study was to explore the case management in social welfare centers and to identify the texts that influence the case management using institutional ethnography. To achieve this, qualitative face-to-face interviews with case managers and administrators in social welfare centers were conducted and the interview contents were analyzed. The main findings of the study are as follows. First, the text that influencing case management in social welfare centers can be divided into two phases; ‘administrative texts for case management in social welfare centers’ and ‘unstructured texts required for case managers’. Five types of administrative texts for case management and six types of unstructured texts, including the discovery of welfare blind spots, were identified. secondary, the texts revealed in this study were found to influence case management practices in social welfare centers in a variety of ways, contributing to the institutionalization of case management. The research findings were discussed in the text. The main implication of the discussion is that case management in social welfare centers is needed so that the subjects of social action can be more clearly revealed, and for this, case management in which case managers and clients of social welfare centers can take the lead.

"Merdeka"! and the dynamics of extreme violence; The first year of the Indonesian Revolution through the eyes of three Dutch journalists

In the first year after World War II, there was a power vacuum in Indonesia. The Indonesians had declared their independence. The Allies had assigned the administration of the former Dutch colony to the British. The Dutch thought they could continue their colonial ambitions. It was a year of utter chaos and extreme violence. While most Dutch journalists remained in Jakarta, three went to the war zones: two of them as reporters and the other as a soldier. The analysis of three texts on the first year of the Indonesian War of Independence by Dutch eyewitnesses shows the importance of subjecting them to closer scrutiny. In the massive focus on the violence in the Indonesian freedom struggle, literary texts of this kind are too often not taken into consideration, even though they are crucial to gaining an insight into the thinking about this war at that time. Because of their hybrid nature, this type of text is pre-eminent in revealing the tension between clashing conceptions, realities, and truths.

Quality Assessment for The Translations of Museum Texts: A Case Study of The Archaeology and Ethnography Museum of Edirne

Museums have significant roles in promoting and presenting cultural heritage and cultural values in various ways. An intrinsic part of intercultural communication in museums, bilingual museum texts (e.g. labels, brochures, explanatory texts etc.) have become an important field to be investigated within the framework of Translation Studies. In order to make a contribution to the analysis of translation of museum texts, this study aims to provide a quality assessment of English translations of texts in the Archeology and Ethnography Museum of Edirne. Even though English translations of different texts types such as labels, brochures and explanatory texts are available in the museum, this study specifically focuses on the translation of explanatory texts presenting the ethnographic identity and archeological findings of the city. For this purpose, twenty-three texts displayed in information boards have been selected and their translations have been analyzed according to translation quality assessment model of Multidimensional Quality Metrics (MMQ). As a result of a detailed qualitative and quantitative analysis of the selected texts, the type, distribution and frequency of translation errors encountered in the selected corpus have been described according to eight dimensions of the metric. Based on this text-based and linguistically-oriented methodology, the functionality of the translated museum texts has been evaluated. It is concluded that this study will provide a theoretical framework and methodological guide to improve the quality assessment competences of lectures and students at the departments of translation studies as well as professional translators and researchers working in the area of museum translation.

Optimizing an English text reading recommendation model by integrating collaborative filtering algorithm and FastText classification method

To comprehend the genuine reading habits and preferences of diverse user cohorts and furnish tailored reading recommendations, this study introduces an English text reading recommendation model designed specifically for long-tail users. This model integrates collaborative filtering algorithms with the FastText classification method. Initially, the integrated collaborative filtering algorithm is explicated, followed by the calculation of the user's interest distribution across various types of English texts, achieved through an enhanced Ebbinghaus forgetting curve and analysis of user reading behaviors. Subsequently, an intelligent English text reading recommendation is generated by amalgamating collaborative filtering algorithms with association rule-based recommendation algorithms. Through optimization of the recommendation generation process, the model's recommendation accuracy is enhanced, thereby augmenting the performance and user satisfaction of the recommendation system. Finally, a comparative analysis is conducted with respect to the Top-N algorithm model, matrix factorization-based algorithm model, and FastText classification model, illustrating the superior recommendation accuracy and F-Measure value of the proposed model. The study findings indicate that when the recommendation list contains 10, 30, 50, and 70 texts, the recommendation accuracy of the proposed algorithm model is 0.75, 0.79, 0.8, and 0.74, respectively, outperforming other algorithms. Furthermore, as the number of texts increases, the F-Measure of all four models gradually improves, with the final F-Measure of the proposed model reaching 0.81. Notably, the F-Measure of the English text reading recommendation model proposed in this study significantly surpasses that of the other three recommendation methods. Demonstrating commendable performance in recall rate, root mean square error, normalized cumulative gain, precision, and accuracy, the model adeptly reflects user reading interests, thereby enhancing the accuracy of text recommendations and the overall system performance. The study findings offer crucial insights and guidance for enhancing the accuracy and overall efficacy of English text recommendation systems.

Pre-Trained Language Models for Text Generation: A Survey

Text Generation aims to produce plausible and readable text in human language from input data. The resurgence of deep learning has greatly advanced this field, in particular, with the help of neural generation models based on pre-trained language models (PLMs). Text generation based on PLMs is viewed as a promising approach in both academia and industry. In this article, we provide a survey on the utilization of PLMs in text generation. We begin with introducing two key aspects of applying PLMs to text generation: (1) how to design an effective PLM to serve as the generation model; and (2) how to effectively optimize PLMs given the reference text and to ensure that the generated texts satisfy special text properties. Then, we show the major challenges that have arisen in these aspects, as well as possible solutions for them. We also include a summary of various useful resources and typical text generation applications based on PLMs. Finally, we highlight the future research directions which will further improve these PLMs for text generation. This comprehensive survey is intended to help researchers interested in text generation problems to learn the core concepts, the main techniques and the latest developments in this area based on PLMs.