Corpus Of Articles Research Articles

Financial Sustainability Through Literacy and Retirement Preparedness

This study discusses financial sustainability in retirement via a comprehensive bibliometric and content analysis on financial literacy and retirement preparedness for 1970–October 2024. Data for this study are extracted from the Scopus database. In line with the PRISMA guideline, the inclusion and exclusion criteria were applied, and the final corpus of articles used in the analysis is 518 articles. These articles are analyzed using the bibliometric methods: Bibliometrix R-package (Biblioshiny) version 4.0 and VOSviewer 1.6.20. The descriptive analysis identified the publication trends, prominent authors, articles, sources, country collaboration, and quadrant analysis. Based on the bibliographic coupling, the following themes were identified: (1) financial literacy and retirement planning, (2) behavioral finance and psychological determinants of retirement planning and preparedness, (3) financial risk, decision making, and retirement preparedness, and (4) gender, socioeconomic factors, and financial literacy disparities. This study has consolidated and enriched the understanding of how financial literacy, education, psychology and behaviors, and financial risk play a pivotal and central role in shaping long-term financial sustainability, as well as retirement planning and preparedness. From a practical perspective, an all-inclusive understanding of the above is essential for guiding regulators and policymakers in designing policies, targeted interventions, and programs that empower individuals towards retirement preparedness, considering regional, socioeconomic, and gender-related factors.

Targeting COVID-19 and Human Resources for Health News Information Extraction: Algorithm Development and Validation.

Global pandemics like COVID-19 put a high amount of strain on health care systems and health workers worldwide. These crises generate a vast amount of news information published online across the globe. This extensive corpus of articles has the potential to provide valuable insights into the nature of ongoing events and guide interventions and policies. However, the sheer volume of information is beyond the capacity of human experts to process and analyze effectively. The aim of this study was to explore how natural language processing (NLP) can be leveraged to build a system that allows for quick analysis of a high volume of news articles. Along with this, the objective was to create a workflow comprising human-computer symbiosis to derive valuable insights to support health workforce strategic policy dialogue, advocacy, and decision-making. We conducted a review of open-source news coverage from January 2020 to June 2022 on COVID-19 and its impacts on the health workforce from the World Health Organization (WHO) Epidemic Intelligence from Open Sources (EIOS) by synergizing NLP models, including classification and extractive summarization, and human-generated analyses. Our DeepCovid system was trained on 2.8 million news articles in English from more than 3000 internet sources across hundreds of jurisdictions. Rules-based classification with hand-designed rules narrowed the data set to 8508 articles with high relevancy confirmed in the human-led evaluation. DeepCovid's automated information targeting component reached a very strong binary classification performance of 98.98 for the area under the receiver operating characteristic curve (ROC-AUC) and 47.21 for the area under the precision recall curve (PR-AUC). Its information extraction component attained good performance in automatic extractive summarization with a mean Recall-Oriented Understudy for Gisting Evaluation (ROUGE) score of 47.76. DeepCovid's final summaries were used by human experts to write reports on the COVID-19 pandemic. It is feasible to synergize high-performing NLP models and human-generated analyses to benefit open-source health workforce intelligence. The DeepCovid approach can contribute to an agile and timely global view, providing complementary information to scientific literature.

Unveiling Weak Signals of Emergence in Underwater Sensing Research Trends

Detecting emerging research trends is crucial as it allows for the proactive identification and monitoring of novel and influential topics in the scientific community. Monitoring research trends aids researchers, institutions, and policymakers in allocating resources, fostering innovation, and staying competitive in rapidly changing scientific landscapes. The growing significance of underwater sensing technologies in various domains has propelled research endeavours aimed at understanding the characteristics of academic discourse in this field. In this work, we comprehensively analyzed the academic research topics related to underwater sensing technologies using advanced computational methodologies. Leveraging natural language processing, topic modelling, and weak signal detection techniques, and focusing on underwater sensing as the case technology, we dissect a large corpus of scholarly articles published between 2007 and 2021 to unveil underlying thematic patterns and emergent trends within this domain while shedding light on signals of emerging technologies. Among the eighty extracted topics, six research topics were identified and recognized as emerging weak signals, and validated by experts. Notably, deep learning for underwater imaging was the only topic that transitioned from being weak to a strong signal in the final period.

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.

The impact of COVID-19 on the debate on open science: a qualitative analysis of published materials from the period of the pandemic

This study is an analysis of the international debate on open science that took place during the pandemic. It addresses the question, how did the COVID-19 pandemic impact the debate on open science? The study takes the form of a qualitative analysis of a large corpus of key articles, editorials, blogs and thought pieces about the impact of COVID on open science, published during the pandemic in English, German, Portuguese, and Spanish. The findings show that many authors believed that it was clear that the experience of the pandemic had illustrated or strengthened the case for open science, with language such as a “stress test”, “catalyst”, “revolution” or “tipping point” frequently used. It was commonly believed that open science had played a positive role in the response to the pandemic, creating a clear ‘line of sight’ between open science and societal benefits. Whilst the arguments about open science deployed in the debate were not substantially new, the focuses of debate changed in some key respects. There was much less attention given to business models for open access and critical perspectives on open science, but open data sharing, preprinting, information quality and misinformation became most prominent in debates. There were also moves to reframe open science conceptually, particularly in connecting science with society and addressing broader questions of equity.

Developing a Text‐Based Measure of Humility in Inquiry Using Computational Grounded Theory

ABSTRACTWe describe a project in which we develop a text‐based measure of HI in the context of scholarly communication using corpora of scientific publications. The data and analytic approach we use will circumvent known concerns with self‐reported data on humility levels and will be calculable on a large scale. We use a computational grounded theory approach to develop a text‐based measure of HI. We draw from an annotated corpus of scientific articles in economics, psychology, and sociology (2010–2023), generating three supra‐dimensions of HI (Epistemic, Rhetorical, and Transparent) and several novel sub‐codes of HI. We present our initial analysis with a focus on the three dimensions of HI derived from a computational grounded theory approach. The text‐based measure helps us better understand how contextual factors shape HI and contribute to mixed methods in information science research.

Research Advancement in Forest Property Rights: A Thematic Review over Half a Decade Using Natural Language Processing

This paper proposes a thematic literature review of advances in the literature on forest property rights over the first half of this decade. From a methodological point of view, we exploited a corpus of scientific articles published between 2019 and 2023, extracted from the Scopus and Web of Science databases. We then performed a co-word analysis using the Louvain algorithm to reveal thematic clusters. This approach enabled us to identify seven distinct trends over the past half-decade, each highlighting specific aspects and geographical diversity of forest property rights, which were then evaluated using a thematic map. The main findings revealed that (policies, livelihoods and agroforestry) and (institutions, sustainability and non-timber forest products) stand out as central and influential themes, which have a significant impact and present notable advances that have shaped recent discussions and practices. Furthermore, themes (forest policy and resource management) and (conservation and the rights of indigenous communities) are well developed, which have a solid research base, offering an in-depth understanding of the relevant research questions. Conversely, themes (institutional change and forest conservation) and (deforestation, indigenous rights and community management) represent emerging themes, which are receiving increasing attention and are likely to become major of focus. In contrast, (forest governance, community management and land conflict resolution) which indicates a waning influence in terms of miscellaneous implications. The findings of this thematic literature review will help guide policymakers, researchers, and practitioners based on recent developments in international forest property rights, during a half-decade marked by a break with previous trends, leading to legislative changes and strategic adaptations essential for the sustainable management of forest resources, bolstered by technological advancements and environmental efforts.

“Telling China’s story well”? Tifa, translation, and discursive power in the Quotidiano del Popolo

ABSTRACT Examining China’s growing efforts to affirm its ‘discoursive power’ (话语权) in the Euro-Mediterranean region, this paper presents a case study of the Communist Party of China’s (CPC) communication of its ‘external publicity’ (对外宣传) via news translation. The study focuses on translation strategies of the Italian version (Quotidiano del Popolo) of the official Party newspaper 人民日报 to investigate the implications and effects of translation shifts involving tifa (提法, political formulations and fixed expressions). A qualitative textual analysis applied the Descriptive Translation three-stage methodology to a corpus of articles on the Beijing 2022 Olympic and Paralympic Games, with reference to ‘constraint’ and ‘relation’ in translation. Understatement, omission, and indirect translation were identified as translation shifts in the corpus, suggesting ideological tensions behind most such shifts. While the first two modes help downplay China’s geo-political ambition, the last results in ineffective translation that can obstruct the intended political message, hindering the ability to ‘tell China’s story well’ (讲好中国故事). This study seeks to elucidate the complexity and political intricacies of ‘correctly’ receiving and replicating the Chinese political message in a foreign language other than English.

Functioning and translation of English and Russian architectural terms in academic discourse

The study provides the analysis of architectural terminology in English and Russian in academic discourse. The object of the study is the terminological system of architecture. The subject of the study is the specifics of the use, functioning and translation of English and Russian architectural terminology in academic discourse. The classification and systematization of architectural terms, their hierarchical structure and functional types in academic texts are considered. In addition, the interdisciplinary nature of the architectural sublanguage is emphasized, which intersects with terms from the fields such as engineering, architecture, construction, art and design. The paper also identifies existing difficulties and problems that arise when translating English and Russian-language architectural terms, including differences in the linguistic structure of languages, semantic ambiguity, the need for a high degree of specialization of the translator for the correct interpretation of the term, the use of idiomatic and figurative language to describe some architectural terms, etc. The study uses a comprehensive methodology, in particular, methods of comparative and component analysis, as well as methods of corpus linguistics used to study semantic fields, hierarchical relationships and functional types of terms. The research results emphasize the importance of standardization of architectural terminology, understanding of cultural and historical background, as well as technical knowledge to ensure effective communication in the global architectural community. Analyzing the corpus of texts, including dictionaries, architectural reviews and academic articles, the author explains how specific terms function in academic discourse. This study makes a special contribution to the development of linguistic research in the field of architecture, offering an in-depth analysis of semantic fields and their role in structuring architectural vocabulary. The novelty of the research lies in an integrated approach to the study of the functioning and translation of architectural terms, which allows to identify the difficulties associated with the interdisciplinary character of the terminology. The results of the study will be useful not only for teachers and translators, but also for international experts in the field of architecture.

Are videogames represented as violent in the press? Hypothesis testing using md-cads and corpora of UK newspapers from 2000 and 2020

Previous academic research has argued that videogames are represented as violent in the media, and that these representations provide a justification to study videogames as a social object. However, little systematic research has been done to confirm whether such representations occur frequently, or whether this is a non-representative assumption based on a small number of news stories. Through using methods associated with Modern-Diachronic Corpus-Assisted Discourse Studies (md-cads), we explore two corpora of newspaper articles from the British press containing references to videogames: one contains data from 2000 and the other from 2020. We find that whilst newspapers do represent videogames as promoting violence, these representations occur much more frequently in 2000 than in 2020, and that in 2020 this idea is more regularly challenged. Furthermore, in 2020 there is a greater focus on the benefit of videogames for the economy compared to 2000. The research highlights the need to critically revaluate assumptions about how the media represents not only videogames, but also comparable topics.

Reducing, reusing, and recycling in the furniture industry: A mini-review

This study explores sustainable practices within the furniture industry, focusing on the principles of reduce, reuse, and recycle. Through a comprehensive review of scholarly literature retrieved from databases like Scopus, Web of Science, and Google Scholar a moderate corpus of articles is identified. The analysis reveals a predominant emphasis on strategies aimed at minimizing resource consumption, extending product lifespans, and optimizing material recovery. While reduce, reuse and recycle serve as foundational pillars of sustainable furniture production, the literature also highlights complementary principles such as "rethink" and "refuse," urging critical reassessment and rejection of unsustainable practices. Despite the diversity in research interests and methodologies, the synthesis of findings underscores the need for standardization and comprehensive approaches to address environmental challenges throughout the furniture lifecycle. The study advocates for further research and collaboration to drive meaningful progress towards a more sustainable future for furniture production and consumption. This abstract encapsulates the key findings and implications of the study, providing a concise overview of the state of research on sustainable practices within the furniture industry. The aim of this short review is to analyse the scientific articles and their quantity relating to ecodesign in the furniture industry, with particular emphasis on the principles of reduce, reuse and recycle, as well as complementary concepts such as ‘rethinking’ and ‘refuse’.

Frequency Analysis, Distribution, and Coverage of Academic Words in Materials Science Research Articles: A Corpus-Based Study

This study explored words in materials science research articles using New Academic Word List (NAWL) and New General Service List (NGSL) created by Browne at al. (2013) as reference lists. The objectives of this research were to explore the frequency and coverage of the NAWL and the NGSL in materials science research articles and identify frequently occurring academic words in materials science research articles that were not included in the NAWL and the NGSL. The corpus used for the analysis was compiled from 115 research articles published in five international journals related to the field of materials science. The findings revealed that the coverage of the NAWL words in the corpus of the present study was at 6.18 percent, together with the NGSL, the cumulative coverage of both word lists in the corpus of the present study was at 75.97 percent, and that there were 356 content words which did not appear in both the NAWL and the NGSL but did occur frequently in the corpus of materials science research articles. The pedagogical implications of these findings are discussed in relation to teaching academic vocabulary to EFL learners of materials science who read and publish academic articles in English.

Effective Stance in Conservative Newspaper Opinion Articles on Irregular Immigration and Refugee Humanitarian Crises

This paper presents a quantitative and contrastive analysis of expressions of effective stance in conservative newspaper opinion articles related to irregular immigration and humanitarian crises involving refugees in both English and Spanish contexts. Drawing upon the seminal works of Langacker (2013) and Marín-Arrese (2021a, 2021b, 2023), the study examines six fundamental categories of effective stance expressions established according to factors such as orientation towards self or others, degree of control about the realisation of the event, and agreement with social norms. The dataset under examination comprises a 120,000-word corpus of opinion articles obtained from two conservative newspapers, The Telegraph from the United Kingdom and El Mundo from Spain. The words are evenly distributed, with each newspaper contributing 30,000 words in articles pertaining to three humanitarian crises involving refugees: Syria (2015), Afghanistan (2021), and Ukraine (2022-2023), and 30,000 words relating to articles on irregular immigration coinciding in time with each of the three refugee crises. The primary objective of the paper is to discern notable differences between the two newspapers and across the different refugee and irregular immigration crises under investigation. The analysis of the results, which uncover a larger number of effective stance expressions in the English subcorpus as well as distributional differences of subcategories across the subcorpora in both languages, provides a valuable understanding of the intricate patterns of usage and distribution of effective stance expressions within the realm of newspaper discourse, thereby enriching our comprehension of journalistic portrayals concerning the complexity of refugee crises and migratory movements.

Variation in psychopathological terminology

Abstract Representing specialized knowledge in the medical domain implies considering the dynamism of scientific and technological progress. The advancement of knowledge on diseases goes hand in hand with the reconceptualization processes undertaken by experts with consequent conceptual evolutions and possible variations of the terms used to designate medical concepts. Sometimes term variation is the result of a desire to avoid or overcome negative connotations anchored in medical terms, and leads to the creation of less evaluatively charged terms that carry a diminished ideological load. This study illustrates the case of Body Dysmorphic Disorder (BDD), a relatively under-/misdiagnosed medical condition which has been the object of multiple reconceptualizations by experts. We focus on the analysis of the conceptual evolution of BDD and the consequent variation occurring at the linguistic level. We adopt the theoretical assumption that terminology has a double dimension – conceptual and linguistic. Following on this assumption, the terminologist must examine both the experts’ conceptualizations of a given domain and the discourses produced by them in order to effectively represent the specialized knowledge of a specific subject field. To complete the analysis, we present how information about BDD is disseminated to non-experts through the analysis of a corpus of mass-media articles.

NEW PARADIGM OF CORPUS ANALYSIS OF MILITARY-POLITICAL NEWSPAPERS ARTICLES

This study using the corpus of newspaper articles from The Guardian, The Washington Post, and The New York Times attempts to explore contemporary methods of corpus analysis. It emphasizes that a corpus-driven approach is relevant for improving the technology of balancing text corpora. This approach is characterized by ways of representing corpus data and unifying decoded information based on the corpus. To this end, urgent news and international reports covering the political strategies of various countries in the context of the Russia-Ukraine war were analyzed. It is noted that understanding the essence of the defined issue required outlining the specifics of studying military-political language patterns within the corpus-driven approach. The research found that a variety of data types can influence the formation of the linguistic environment, which explains variations of language system models in textual dimensions. The results also showed random concordance lines, the semantic field of lexemes, and the most frequent units of the journalistic language system that reveal linguistic changes during the war period. Additionally, the study identifies final variables in statistical models, dominantsemantic positions of linguistic constructions, the valency of marked units, and their linguistic potential, status, and functions within the corpus. The importance of using Text Mining technology, the ANNOVA test, and Cortical.io software for data processing is also justified. It is concluded that improving corpus analysis methods depends on text attribution, hierarchical clustering, determining statistically significant differences between mean values of variables through analysis of variance. Moreover, the study enable the conclusion that the text processing mechanism plays an important role in the development of new paradigm of corpus analysis.

Same-sex marriage, gay marriage, or equal marriage?

Abstract Changes to marriage legislation across the globe have received much academic and public attention. However, the labels used to categorise different marital configurations are somewhat under researched. In this paper we analyse the premodification of marriage in a corpus of UK newspaper articles (2000–2018) to establish which labels are most commonly used in reference to same-sex marriage. These are gay marriage, same-sex marriage, homosexual marriage, and equal marriage. Drawing on the notion of category construction, we emphasise the fact that these labels are not neutral synonyms, as each encodes a particular understanding of same-sex marriage. Some labels even linguistically exclude certain groups, such as those who are bisexual or transgender. We use the tools of corpus-based discourse analysis to consider the nuanced differences between the category labels and consider whether the limitations of the labels are ever directly challenged.

Transdisciplinary method for exploration and visualization of neuroimaging papers and databases: Application to PTSD

A major improvement in MRI techniques has led to an exponential increase in data acquisition and, consequently, in the number of published articles reporting brain impairments and cognitive deficits underlying a disorder. Meta-analysis offers a means of synthesizing the available literature, testing existing models in the light of scientific advances, and revealing unexpected information. However, article selection, author specialization and top-down hypotheses can mask some results and introduce bias into interpretations. LinkRdata is a platform for automated, data-driven, meta-analytical methods suitable for processing large numbers of MRI articles, that can reduce selection and interpretation biases, thereby allowing scientists to review neurocognitive correlates of disorders in relation to their own corpus of articles. To validate our method, we applied it to fMRI studies of post-traumatic stress disorder. Results confirmed LinkRdata's power to uncover findings hidden by the top-down hypothesis approach.

Multidimensional Analysis of Differences in Lexico-Grammatical Patterns in Saudi and British Linguistics and English Language Teaching Research Articles

This study explores linguistic variation in research papers published by Saudi and British researchers in Linguistics and English language teaching (ELT). The main aim is to identify and compare interdisciplinary lexico-grammatical patterns between and within the sub-disciplines of these research articles, exploring the extent to which Saudi research articles align with or diverge from their British counterparts. Utilizing Biber’s (1988) multidimensional model, this research developed a specialized corpus of academic research articles, which was analyzed using multivariate statistical techniques to investigate linguistic variation. The corpus included tagging of 67 linguistic features, and factor analysis was employed to identify patterns of linguistic co-occurrence. Significant findings indicate that Saudi research papers distinctly differ from British papers in their preference for informational, explicit, non-argumentative, and abstract discourse. Notably, while most sections of the research papers showed variations in non-argumentative discourse, the ELT conclusion sections from both regions demonstrated a tendency towards mixed-purpose discourse. The significance of the study lies in its detailed analysis of how regional differences affect lexico-grammatical choices within academic writing, offering a deeper understanding of linguistic strategies in scholarly communication. The study concludes with recommendations for further research to explore underlying factors contributing to these differences and suggests the development of targeted academic writing aids to support researchers in achieving greater international coherence in their discourse. This could potentially enhance the clarity and impact of scholarly communication across diverse linguistic and cultural backgrounds.

From Argentina to Zimbabwe: Exploring the global appeal of the International Baccalaureate

This paper presents the third stage of a larger research project examining perceptions of the International Baccalaureate (IB) to better understand its growing influence on education systems around the world. The first two stages involved a synchronic and diachronic analysis of IB discourse in a 27 million word specialized corpus of global press articles, created as an unsolicited window into public opinion (Mautner, 2008). The present study uses the same corpus to explore how the IB is represented in different countries, what values and attitudes may be associated with it, and how it interacts with other global education actors. Bottom up and top down methods from corpus-assisted discourse studies (CADS) were used to analyze 34,104 newspaper articles from 56 countries. Frequency, collocation and concordance analyses revealed four dominant discourses of deficiency connected to national education systems in countries across the ideological spectrum that helped to legitimize the inclusion of private actors in the provision of education. Results also showed unique discourses associated with the IB in North America, thereby highlighting the key role that this region plays in the IB world.

Sentiment analysis of global news on environmental issues: insights into public perception and its impact on low-carbon economy transition

In this study, we leverage sentiment analysis to investigate public perception towards environmental issues as conveyed through global news articles and its potential implications on the transition to a low-carbon economy. Utilizing an extensive corpus of news articles sourced globally, we deploy Natural Language Processing (NLP) techniques to quantify sentiment in these articles, capturing public sentiment’s dynamism and complexity towards various environmental issues. Our methodology involves sentiment scoring of key aspects like “climate change”, “climate policy”, “renewable energy”, “solar energy”, “wind energy”, and “environmental impact” which facilitated a detailed sentiment trend analysis over time. We also incorporated a Latent Dirichlet Allocation (LDA) model to conduct topic modelling, identifying five major topics recurring in the discourse. Our correlation analysis uncovers interesting relationships such as a positive correlation between sentiment scores of “low carbon” and “electric cars”, and a negative correlation between “greenhouse gas emissions” and “electric cars". The findings indicate that public sentiment towards environmental issues is not only multifaceted but also evolving, with significant implications for policy-making and stakeholder engagement in the low-carbon transition. These results exemplify sentiment analysis as a powerful tool in understanding public perception, providing actionable insights for researchers, policymakers, and stakeholders involved in environmental issues and the low-carbon economy transition.