Hasil untuk "Discourse analysis"

C. Grbich

PART ONE: GENERAL APPROACHES TO COLLECTING AND ANALYZING QUALITATIVE DATA Introduction Design Methodologies, Data Management and Analytical Approaches Incorporating Data from Multiple Sources: Mixing Methods PART TWO: TRADITIONAL ANALYTICAL APPROACHES Classical Ethnography Critical Ethnographic Approaches Feminist Approaches Grounded Theory Phenomenology PART THREE: NEWER QUALITATIVE APPROACHES Postmodern Influences on Society and Qualitative Research Auto-Ethnography Poetic Inquiry Ethnodrama and Performative Art Cyber-Ethnography and E-Research PART FOUR: ANALYTIC APPROACHES FOR EXISTING DOCUMENTATION Structuralism and Post-Structuralism Semiotic Structural and Post-Structural Analysis (Deconstruction) Content Analysis of Texts Content Analysis of Visual Documentation Narrative Analysis Conversation Analysis Discourse Analysis PART FIVE: DATA MANAGEMENT USING QUALITATIVE COMPUTER PROGRAMMES Coding An Overview of Qualitative Computer Programs PART SIX: INTERPRETING AND PRESENTING QUALITATIVE DATA Theorizing from Data Innovative Data Display

Ivan N. Alov, Marko D. Petrović, Alisa M. Belyaeva

Urban depopulation has become an increasingly visible phenomenon worldwide, affecting cities of different sizes and economic structures. This article develops a typology of U.S. depopulating cities beyond the Rust Belt’s iconic industrial cities, which dominate academic literature, to include a wider range of shrinking settlements in the shadows. The analysis is based on a dataset of U.S. census places constructed from decennial census population data (1990–2020) combined with employment structure indicators and spatial classification variables identifying metropolitan position and industrial specialization. Using 1990–2020 population change and three explanatory dimensions—city size, industrial heritage, and peripheral location—the analysis identified 1082 places that lost at least 10% of their population. Logistic regression showed manufacturing and mining reliance, small size, and remoteness as significant predictors of depopulation. Based on these factors, settlements are divided into seven types, from large urban centers to small peripheral towns with fewer than 5000 people. The overwhelming predominance of small towns (97%) in the sample highlights their distinct development challenges and questions the narrative of decline focused solely on larger industrial cities. By situating American trajectories within the broader shrinking cities discourse, the findings demonstrate the value of typology as a methodological tool for identifying intra-group heterogeneity, capturing regional differences, and establishing a more reliable basis for comparative urban studies. Ultimately, the study shows that urban decline in the United States is not exclusively a Rust Belt phenomenon, but a multidimensional process encompassing different scales, sectors, and geographies.

Ning Xu, Longchao Xu, Xiang-Wu Yan

This study investigates the relationship between data factor marketization (DFM) and enterprise innovation quality (EIQ) through econometric analysis. Leveraging the staggered implementation of data trading platforms across Chinese cities as a quasi-natural experiment, we employ difference-in-differences methodology on comprehensive panel data from Chinese listed companies spanning 2007–2022. Our findings demonstrate that DFM implementation significantly elevates innovation quality among affected enterprises. The conclusion remains robust across multiple specification tests, placebo analyses, and instrumental variable approaches addressing endogeneity concerns. The research illuminates four distinct mechanisms through which DFM enhances innovation: strengthening enterprise information infrastructure, alleviating financing constraints, stabilizing supplier relationships, and increasing the scale of intangible assets of enterprises. DFM has stronger promoting effects on EIQ in large cities, eastern cities, and cities with higher intellectual property protection levels, and is also more capable of enhancing innovation quality in state-owned enterprises, growth-stage enterprises, and enterprises with CEOs having information technology backgrounds. These findings advance theoretical understanding of digital transformation's role in innovation systems while offering empirical foundations for policy frameworks seeking to leverage data as a strategic production factor. By demonstrating the multifaceted pathways through which market-based allocation of data elements influences innovation outcomes, this research contributes to the scholarly discourse on innovation drivers in transitional economies.

Konstantin S. Zaikov , Denis S. Kortunov

The article examines the impact of the post-truth phenomenon on the perception of international securi-ty in the Arctic region. The main focus is on analyzing information distortions in the media resources of leading foreign mass media outlets (The New York Times, The Washington Post, The Guardian, The Daily Telegraph). Based on content analysis and discourse analysis of 176 publications from 2022 to 2025, the study reveals that the Western media systematically constructs an image of the Arctic as a zone of per-manent crisis and military-political confrontation, where Russia and China are presented as key sources of instability. The actions of Western states, in contrast, are presented as necessary and defensive. The au-thors identify characteristic post-truth techniques: use of emotionally charged headlines, selective presentation of facts, distortion of cause-and-effect relationships, and imposition of simplified narratives. The article assesses the risks of such destructive information influence, including growing mistrust be-tween Arctic states, escalation of conflict potential, and reduction of opportunities for international co-operation in scientific, environmental, and economic spheres. Based on the identified trends, two key scenarios for the development of the situation in the region are developed: “acute escalation” and “freezing of cooperation”. In response to these challenges, a system of comprehensive multi-level measures is proposed, including promotion of international information security, creation of objective information resources about the Arctic, improvement of media literacy among the population, and sup-port for expert and scientific contacts to counter manipulative narratives and maintain stability in the Arctic.

Yibing Yao, Jiaming Xu, Hong Geng et al.

Urban renewal has driven historic conservation districts to experience a series of changes characterized by gentrification. In the 21st century, internet traffic can be fully monetized. The intervention of the internet has made the gentrification process more diversified. Using color and item detection, points of interests (POIs), and word cloud analysis, this study takes a typical historic conservation district as an example to explore how it changed spatially, economically, and socially during the gentrification process. The results show that the internet celebrity economy possesses both promoting and dissolving effects. The promoting effects include the following: (1) the internet celebrity economy breaks the elites’ monopoly on spatial aesthetic discourse; (2) emotional value has promoted the integration of different groups’ consumption; and (3) gentrification occurs locally so spatial exclusion is not significant. The dissolving effects include the following: (1) the low-cost and rapid renovation of space reduces spatial quality; and (2) the fast-moving consumer model may possibly lead to unsustainable development. This study proposes that the intervention of the internet celebrity economy can alleviate the isolation drawbacks of traditional gentrification and promote social equity, and the promoting effects outweigh the negative effects.

Ramya Namuduri, Yating Wu, Anshun Asher Zheng et al.

As large language models become increasingly capable at various writing tasks, their weakness at generating unique and creative content becomes a major liability. Although LLMs have the ability to generate text covering diverse topics, there is an overall sense of repetitiveness across texts that we aim to formalize and quantify via a similarity metric. The familiarity between documents arises from the persistence of underlying discourse structures. However, existing similarity metrics dependent on lexical overlap and syntactic patterns largely capture $\textit{content}$ overlap, thus making them unsuitable for detecting $\textit{structural}$ similarities. We introduce an abstraction based on linguistic theories in Questions Under Discussion (QUD) and question semantics to help quantify differences in discourse progression. We then use this framework to build $\textbf{QUDsim}$, a similarity metric that can detect discursive parallels between documents. Using QUDsim, we find that LLMs often reuse discourse structures (more so than humans) across samples, even when content differs. Furthermore, LLMs are not only repetitive and structurally uniform, but are also divergent from human authors in the types of structures they use.

Satyanad Kichenassamy

Bunyakovsky's integral inequality (1859) is one of the familiar tools of modern Analysis. We try and understand what Bunyakovsky did, why he did it, why others did not follow the same path, and explore some of the mathematical (re)interpretations of his inequalities. This is achieved by treating the texts as discourses that provide motivation and proofs by their very discursive structure, in addition to what meets the eye at first reading. Bunyakovsky paper is an outgrowth of the mathematical theory of mean-values in Cauchy's work (1821), but viewed from the point of view of Probability and Statistics. Liouville (1836) gave a result that implies Bunyakovsky's inequality, but did not identify it as significant because his interests lay elsewhere. Grassmann (1862) stated the inequality in abstract form but did not prove it for reasons that can be identified. Finally, by relating the result to quadratic binary forms, Schwarz (1885) opened the way to a geometric interpretation of the inequality that became important in the theory of integral equations. His argument is the source of one of the proofs most commonly taught nowadays. At about the same time, the Rogers-H{ö}lder inequality suggested generalizations of Cauchy's and Bunyakovsky's results in an entirely different direction. Later extensions and reinterpretations show that no single result, even now, subsumes all known generalizations.

Gaurab Chhetri, Darrell Anderson, Boniphace Kutela et al.

This study presents the first multi-platform sentiment analysis of public opinion on the 15-minute city concept across Twitter, Reddit, and news media. Using compressed transformer models and Llama-3-8B for annotation, we classify sentiment across heterogeneous text domains. Our pipeline handles long-form and short-form text, supports consistent annotation, and enables reproducible evaluation. We benchmark five models (DistilRoBERTa, DistilBERT, MiniLM, ELECTRA, TinyBERT) using stratified 5-fold cross-validation, reporting F1-score, AUC, and training time. DistilRoBERTa achieved the highest F1 (0.8292), TinyBERT the best efficiency, and MiniLM the best cross-platform consistency. Results show News data yields inflated performance due to class imbalance, Reddit suffers from summarization loss, and Twitter offers moderate challenge. Compressed models perform competitively, challenging assumptions that larger models are necessary. We identify platform-specific trade-offs and propose directions for scalable, real-world sentiment classification in urban planning discourse.

Aishat M. Aibazova

The article studies multimodal verbal, visual and auditory mechanisms of contamination of universal, global and national value spaces in the aspect of dominant axiological concepts’ interpretation of regional film discourse. Film discourse can be considered as the most representative field for the shift of value dominants, combining various semiotic code systems for the most effective implementation of the perlocutionary effect, pursuing the main goal of transforming the conceptual and value space of the recipient. As part of the analysis of the key methods of glocalization of axiologems, a complex of methods of the hermeneutic and interpretative approach was used, including contextual, linguacultural, etymological, linguaaxiological, discursive and modal methods. The polymodal and polycode nature of the empirical material requires systematic consideration of ways to intensify traditional spiritual values in their verbalization. The key method of contaminating tradition and innovation in modifying the content of axiological concepts is a constitutive link to global, universal components shared by other ethnonational communities. Such an association occurs in the context of the expansion of the positive and negative spaces of the described concept deportation, which is significant both for the Karachay-Balkarian linguaculture under consideration and for many peoples of the USSR. The concept represents a whole precedent world, including individual concepts for concretizing values and anti-values in a situational and local rethinking. The key axiological concepts in the translation of traditional values and anti-values of the deportation are recognized as jashau (“life”), as a global axiologeme, with the concept of elum/ajal (“death”) leveled out and thrown to the periphery; as well as private locally interpreted concepts bilim (“knowledge”), syy/namys (“dignity/honor”), kishilik (“courage”), azatlyk (“freedom”). The overtones of universal perception in the generalized content of these concepts make it possible to create a glocalized space of interpretation that reflects common values and meanings in the ethno-national linguistic consciousness.

Min He, Shengnan Chen

IntroductionThis study explores the dynamics of Linguistic Landscapes (LL) in the commercial tourist district near Labrang Monastery by analyzing the use of Tibetan, Mandarin, and English on café menus. Traditionally, LL research has focused on language visibility as an indicator of vitality, overlooking contextual complexities. We challenge this approach by considering geocultural contexts, instigators’ language proficiency, and intended audience.MethodThis study employed a triangulation approach, combining multiple methods of data collection and analysis. First, we conducted a preliminary observation of shop names in the region. Second, with the consent of shop owners, we comprehensively documented visual and textual artifacts both inside and outside the cafés, including signboards, menus, wall billboards, and displayed books. Third, we conducted extensive semi-structured interviews with shop owners and customers. These interviews, transcribed for analysis, provided insights into language usage preferences and decision-making processes.ResultsBy advocating for a holistic LL research approach, integrating qualitative insights with quantitative data, this study contributes to a deeper understanding of LL dynamics. Our findings show that geocultural contexts, instigators’ language proficiency, and intended audience all play a role in shaping language representation and vitality.DiscussionThe absence of a language on signage does not necessarily signify diminished vitality but can reflect strategic decisions influenced by religious, individual and commercial factors. Beyond mere visibility, languages on café menus serve as symbolic markers of ethnic identity and reflect the functions they assume within the speech community, offering insights into language vitality across different usage contexts. This research enriches scholarly discourse on LL, particularly within the Chinese context, by emphasizing the multifaceted nature of language presence and its vitality.

Lucas Delgado, Chris Thornhill

The paper aims to examine and understand the recent developments in Brazilian democracy in a sociological perspective. It offers an analysis of the conjunctural preconditions for the recent rise of authoritarian populism, presenting ways in which Brazil can be viewed as paradigm of democratic erosion and/or resilience.  The article describes the foundational premises that made the development of contemporary democracies possible, and it proceeds from this description to explain how features common to authoritarian populist movements in Brazil and elsewhere are detrimental to these premises. It is argued that democracies are likely to thrive when welfare provisions and access to human rights are open to increasing sectors of the population, generating an inclusionary citizenship effect. The political polarization regarding the Brazilian welfare system and the discourse against international human rights, culminated in the weakening of the Brazilian welfare net and setbacks in the recognition of human rights by courts. These processes preceded, and were aggravated by, the rise of authoritarian populism in Brazil, generating an exclusionary view of citizenship that tended to intensify social conflict, with increasing militarization at both governmental and social levels. Arguably, the absence of warfare or an imminent warfare threat in the most recent democratic transition in Brazil reduced the capacity of welfare and constitutional human rights provisions to limit the influence of the military on democracy. While the efforts to build up the welfare system and protect human rights are still ongoing, the militarization element remains latent, posing a constant threat to democratic consolidation in Brazil.

Jiahui Xu, Feng Jiang, Anningzhe Gao et al.

In dialogue systems, discourse plays a crucial role in managing conversational focus and coordinating interactions. It consists of two key structures: rhetorical structure and topic structure. The former captures the logical flow of conversations, while the latter detects transitions between topics. Together, they improve the ability of a dialogue system to track conversation dynamics and generate contextually relevant high-quality responses. These structures are typically identified through discourse parsing and topic segmentation, respectively. However, existing supervised methods rely on costly manual annotations, while unsupervised methods often focus on a single task, overlooking the deep linguistic interplay between rhetorical and topic structures. To address these issues, we first introduce a unified representation that integrates rhetorical and topic structures, ensuring semantic consistency between them. Under the unified representation, we further propose two linguistically grounded hypotheses based on discourse theories: (1) Local Discourse Coupling, where rhetorical cues dynamically enhance topic-aware information flow, and (2) Global Topology Constraint, where topic structure patterns probabilistically constrain rhetorical relation distributions. Building on the unified representation and two hypotheses, we propose an unsupervised mutual learning framework (UMLF) that jointly models rhetorical and topic structures, allowing them to mutually reinforce each other without requiring additional annotations. We evaluate our approach on two rhetorical datasets and three topic segmentation datasets. Experimental results demonstrate that our method surpasses all strong baselines built on pre-trained language models. Furthermore, when applied to LLMs, our framework achieves notable improvements, demonstrating its effectiveness in improving discourse structure modeling.

Veronika Katermina / Катермина Вероника Викторовна, Anna Gnedash / Гнедаш Анна Александровна

The study is dedicated to the analysis of the features of the formation of online fan discourse in asynchronous multimodal discursive fields on the Internet on the example of football communities in the social network vk.com. The empirical base of the study was network data (posts on community and group walls, comments on posts, statistics on likes of posts and comments, statistics on reposts, popular posts) obtained from the 3 most popular Russian football-themed online communities and uploaded through the vk.com API interface. On the basis of the processed network data the discursive fields of football communities were built and analyzed. This allowed for describing culturally significant concepts and the scenarios of communicative behavior of football fans conditioned by them, as well as to identify universal and specific scenarios of communicative patterns of behavior in the fan culture. Исследование посвящено анализу особенностей формирования сетевого фанатского дискурса в асинхронных мультимодальных дискурсивных полях в сети Интернет на примере футбольных сообществ в социальной сети ВКонтакте. Эмпирической базой исследования стали сетевые данные (посты на стене сообществ и групп, комментарии к постам, статистика лайков постов и комментариев, статистика репостов, популярные посты), полученные из 3 самых популярных российских сетевых сообществ, посвящённых футбольной тематике и выгруженные через интерфейс API ВКонтакте (Топ-100 сообщений-постов и около 500 000 комментариев к ним за период с 1 января 2022 г. по 31 августа 2022 г.). Три полученных дата-сета были подвергнуты процедурам Data Science, математического моделирования, реляционной социологии, корпусной лингвистики и лингводискурсивного анализа. На основе обработанных сетевых данных были построены и проанализированы дискурсивные поля футбольных сообществ. Это позволило описать культурно значимые концепты и обусловленные ими сценарии коммуникативного поведения футбольных фанатов, а также выявить универсальные и специфические сценарии коммуникационных паттернов поведения в фанатской культуре.

Malvina Bozhidarova, Jonathn Chang, Aaishah Ale-rasool et al.

This study explores the dynamic relationship between online discourse, as observed in tweets, and physical hate crimes, focusing on marginalized groups. Leveraging natural language processing techniques, including keyword extraction and topic modeling, we analyze the evolution of online discourse after events affecting these groups. Examining sentiment and polarizing tweets, we establish correlations with hate crimes in Black and LGBTQ+ communities. Using a knowledge graph, we connect tweets, users, topics, and hate crimes, enabling network analyses. Our findings reveal divergent patterns in the evolution of user communities for Black and LGBTQ+ groups, with notable differences in sentiment among influential users. This analysis sheds light on distinctive online discourse patterns and emphasizes the need to monitor hate speech to prevent hate crimes, especially following significant events impacting marginalized communities.

Yuchen Eleanor Jiang, Tianyu Liu, Shuming Ma et al.

Several recent papers claim human parity at sentence-level Machine Translation (MT), especially in high-resource languages. Thus, in response, the MT community has, in part, shifted its focus to document-level translation. Translating documents requires a deeper understanding of the structure and meaning of text, which is often captured by various kinds of discourse phenomena such as consistency, coherence, and cohesion. However, this renders conventional sentence-level MT evaluation benchmarks inadequate for evaluating the performance of context-aware MT systems. This paper presents a new dataset with rich discourse annotations, built upon the large-scale parallel corpus BWB introduced in Jiang et al. (2022). The new BWB annotation introduces four extra evaluation aspects, i.e., entity, terminology, coreference, and quotation, covering 15,095 entity mentions in both languages. Using these annotations, we systematically investigate the similarities and differences between the discourse structures of source and target languages, and the challenges they pose to MT. We discover that MT outputs differ fundamentally from human translations in terms of their latent discourse structures. This gives us a new perspective on the challenges and opportunities in document-level MT. We make our resource publicly available to spur future research in document-level MT and the generalization to other language translation tasks.

T. A. Svetonosova

The present article aims to identify stylistic figures, providing intertextual connections of American presidents’ inaugural addresses with other texts which are of great importance to the USA and the American nation. Stylistic figures are figurative and expressive means of connecting texts of the past with texts of the present. The stylistic figures “allusion”, “application”, “paraphrase”, and “citation” have been analysed in the inaugural addresses delivered by four American presidents (2001–2021) – George Bush Jr., Barack Obama, Donald Trump, and Joseph Biden. These stylistic figures determine intertextual contacts of the inaugural addresses with the texts which characterize the country’s historical and modern development – the United States Declaration of Independence, John Page’s letter to Thomas Jefferson, the Constitution of the United States, the past Presidents’ speeches, patriotic songs. Inaugural addresses form a well-established genre in political discourse, and this genre is aimed at integrating and inspiring the people as well as at performing and establishing President’s and his administration’s general policies. The analysis of the genre of the “inaugural address” is an integral part of political discourse research. Political discourse is perceived as a system of communication that has real and virtual measures. The analysis of stylistic figures which provide intertextual connections belongs to the study of the virtual measure of political discourse – its semiotic area. The analysis conducted in the article is based on political discourse research, intertextuality theory, critical discourse analysis theory as well as on practical papers on presidential communication. This article’s methodology includes methods of observation, deduction, induction, controlled sampling, and the method of discourse analysis. Having analyzed the inaugural addresses and having identified the stylistic figures which incorporate other texts into the inaugural addresses, the author concludes that, firstly, the ideas and principles formulated in the past and implemented in the country’s development concept are sacred and unshakeable, and secondly, these ideas and principles have a great impact on the American nation’s consolidation and integration.

Mehrdad Zareh, Xiaoping Qian

In this paper, we report the use of rational Triangular Bezier Splines (rTBS) to numerically solve the von Karman equations, a system of fourth order PDEs. $C^{1}$ smoothness of the mesh, generated by triangular Bezier elements, enables us to directly solve the von Karman systems of equations without using mixed formulation. Numerical results of benchmark problems show high accuracy and optimal convergence rate in L1, H1 and H2 norm for quadratic and cubic triangular Bezier elements. Results of this study show that triangular isogeometric analysis can efficiently and accurately solve systems of high order PDEs. Keywords: Rational triangular Bezier splines; Isogeometric analysis; Von Karman; Optimal convergence rate; High order PDEs; Smooth mesh; Triangular elements.

Philipp Wicke, Marianna M. Bolognesi, Panos Athanasopoulos

Doctors and nurses in these weeks and months are busy in the trenches, fighting against a new invisible enemy: Covid-19. Cities are locked down and civilians are besieged in their own homes, to prevent the spreading of the virus. War-related terminology is commonly used to frame the discourse around epidemics and diseases. The discourse around the current epidemic makes use of war-related metaphors too, not only in public discourse and in the media, but also in the tweets written by non-experts of mass communication. We hereby present an analysis of the discourse around #Covid-19, based on a large corpus tweets posted on Twitter during March and April 2020. Using topic modelling we first analyze the topics around which the discourse can be classified. Then, we show that the WAR framing is used to talk about specific topics, such as the virus treatment, but not others, such as the effects of social distancing on the population. We then measure and compare the popularity of the WAR frame to three alternative figurative frames (MONSTER, STORM and TSUNAMI) and a literal frame used as control (FAMILY). The results show that while the FAMILY frame covers a wider portion of the corpus, among the figurative frames WAR, a highly conventional one, is the frame used most frequently. Yet, this frame does not seem to be apt to elaborate the discourse around some aspects involved in the current situation. Therefore, we conclude, in line with previous suggestions, a plethora of framing options—or a metaphor menu—may facilitate the communication of various aspects involved in the Covid-19-related discourse on the social media, and thus support civilians in the expression of their feelings, opinions and beliefs during the current pandemic.

Grigorii Guz, Peyman Bateni, Darius Muglich et al.

This paper evaluates the utility of Rhetorical Structure Theory (RST) trees and relations in discourse coherence evaluation. We show that incorporating silver-standard RST features can increase accuracy when classifying coherence. We demonstrate this through our tree-recursive neural model, namely RST-Recursive, which takes advantage of the text's RST features produced by a state of the art RST parser. We evaluate our approach on the Grammarly Corpus for Discourse Coherence (GCDC) and show that when ensembled with the current state of the art, we can achieve the new state of the art accuracy on this benchmark. Furthermore, when deployed alone, RST-Recursive achieves competitive accuracy while having 62% fewer parameters.

Sungkyu Park, Sungwon Han, Jeongwook Kim et al.

COVID-19 has become one of the most widely talked about topics on social media. This research characterizes risk communication patterns by analyzing the public discourse on the novel coronavirus from four Asian countries: South Korea, Iran, Vietnam, and India, which suffered the outbreak to different degrees. The temporal analysis shows that the official epidemic phases issued by governments do not match well with the online attention on COVID-19. This finding calls for a need to analyze the public discourse by new measures, such as topical dynamics. Here, we propose an automatic method to detect topical phase transitions and compare similarities in major topics across these countries over time. We examine the time lag difference between social media attention and confirmed patient counts. For dynamics, we find an inverse relationship between the tweet count and topical diversity.