Hasil untuk "Discourse analysis"

Yijin Wu, Wen Ma

Caldas-Coulthard C 1994 ‘On reporting reporting: the representation of speech in factual and factional narratives’ in M Coulthard (ed.) Advances in Written Text Analysis London: Routledge. pp. 295–308. Halliday MAK 1978 Language as Social Semiotic London: Edward Arnold. Halliday MAK 1985 Introduction to Functional Grammar London: Edward Arnold. Machin D 2007 Introduction to Multimodal Analysis London: Hodder Arnold. O’Halloran KL 2004 ‘Introduction’ in KL O’Halloran (ed.) Multimodal Discourse Analysis: systemic functional perspectives London: Continuum. pp. 1–7.

J. Jagers, S. Walgrave

Akhil Gupta

P. Chilton

This is an essential read for anyone interested in the way language is used in the world of politics. Based on Aristotle's premise that we are all political animals, able to use language to pursue our own ends, the book uses the theoretical framework of linguistics to explore the ways in which we think and behave politically. Contemporary and high profile case studies of politicians and other speakers are used, including an examination of the dangerous influence of a politician's words on the defendants in the Stephen Lawrence murder trial. International in its perspective, Analysing Political Discourse also considers the changing landscape of political language post-September 11, including the increasing use of religious imagery in the political discourse of, amongst others, George Bush. Written in a lively and engaging style, this book provides an essential introduction to political discourse analysis.

L. Faigley, G. Kress, T. V. Leeuwen

S. Erduran, S. Simon, J. Osborne

Theo van Leeuwen, R. Wodak

Jennifer E. Arnold, Anthony Losongco, T. Wasow et al.

R. Iedema

Hala Shaker Hammad

Children spend almost one-third of their day in schools, and much of the peer pressure arises in this educational setting. In September 2023, the World Health Organisation (WHO) released two publications to urge schools around the world to take the necessary steps toward creating a smoke and nicotine-free environment and implementing policies that prevent young people from starting smoking. The language of such documents usually conceals a high level of legitimation and persuasion to reach the target audience and achieve the intended goals. Meanwhile, the organisation strengthens its legitimacy when its actions are perceived by the public as desirable, moral, or appropriate. Data for this study were obtained from two key documents, namely ‘Freedom from Tobacco and Nicotine: Guide for Schools’ and ‘Nicotine and Tobacco-Free Schools Toolkit’. Both documents were collected and downloaded from the official website of the WHO. The current study uses the Critical Discourse Analysis (CDA) approach to analyse the construction of legitimacy in the WHO’s latest anti-smoking publications with van Leeuwen’s legitimation strategies as its analytical tool. The analysis has identified the use of multiple legitimation strategies, and the results indicate that the smoking ban discourse shows a general authoritarian attitude. Moreover, there is a shift toward a more rational, practical, and school-centred stance, a switch from “fighting the bad” to “protecting the good”. The results emphasise the role of persuasive language in crafting policy documents to generate favourable outcomes and maintain the organisation’s legitimacy.

Eason Chen, Ce Guan, A Elshafiey et al.

Peer learning, where learners teach and learn from each other, is foundational to educational practice. A novel phenomenon has emerged: AI agents forming communities where they share skills, discoveries, and collaboratively discuss knowledge. This paper presents an educational data mining analysis of Moltbook, a large-scale community where over 2.4 million AI agents engage in discourse that structurally resembles peer learning. Analyzing 28,683 posts (after filtering automated spam) and 138 comment threads with statistical and qualitative methods, we identify discourse patterns consistent with peer learning behaviors: agents share skills they built (74K comments on a skill tutorial), report discoveries, and engage in collaborative problem-solving. Qualitative comment analysis reveals a taxonomy of response patterns: validation (22%), knowledge extension (18%), application (12%), and metacognitive reflection (7%), coded by two independent raters (Cohen's $κ= 0.78$). We characterize how these AI discourse patterns differ from human peer learning: (1) statements outperform questions with an 11.4:1 ratio ($χ^2 = 847.3$, $p < .001$); (2) procedural content receives significantly higher engagement than other content (Kruskal-Wallis $H = 312.7$, $p < .001$); (3) extreme participation inequality (Gini = 0.91 for comments) reveals non-human behavioral signatures. We propose six empirically grounded hypotheses for educational AI design. Crucially, we distinguish between surface-level discourse patterns and underlying cognitive processes: whether agents "learn" in any meaningful sense remains an open question. Our work provides the first empirical characterization of peer-learning-like discourse among AI agents, contributing to EDM's understanding of AI-populated educational environments.

Teun A. van Dijk

This critical review of more than three decades of studies of frames and framing in Social Movement (SM) research first offers a brief history of the notion of ‘frame’ in various disciplines, and then discusses empirical studies of frame alignment, frame disputes, frame resonance and master frames, among other notions. It is found that the very notion of discursive of cognitive frames remains very vague in these studies, and what are actually studied are for instance, beliefs, attitudes, goals, ideologies or values, especially how they are expressed in discourse. Also studies of relations between frames and culture, identity and discourse show that the notions of frames and framing are theoretically and methodologically unsatisfactory in empirical studies. It is concluded that the methods of the cultural paradigm of SM research may take advantage of the advances of more explicit methods in the study of language, discourse, interaction and cognition.

Xueshi Li, Qianqian Chen, Yan Zhu et al.

Abstract Food saving is a pressing global challenge, and understanding its divergent framings is vital for designing effective strategies. This study examines the alignment and divergence between media discourse and individual attitudes toward food saving in China using a mixed-methods approach that combines content analysis of 123 news articles with Q-methodology involving 60 participants. Drawing on Boltanski and Thévenot’s framework of seven value orders, the research identifies “domesticity” as a core value emphasized by both media and individuals, while media narratives underrepresent values such as “the environment” and “inspiration,” which are central to individual perspectives. This misalignment highlights why awareness campaigns often fail to effect substantial behavioral change. By analyzing the interplay between media narratives and public attitudes, the study not only provides actionable insights for policymakers and educators in China, but also offers a transferable model for interpreting frame (mis)alignment in other rapidly modernizing, state-led contexts. The proposed multi-level explanatory model contributes to international food policy scholarship by advancing the theoretical understanding of how value orders shape, and sometimes constrain, effective interventions in food saving governance.

Ioana Constandache

This research proposes a systematic and comprehensive investigation of Oscar Wilde's work focusing on The Picture of Dorian Gray (1890), widely regarded as the centrepiece of his aesthetic and philosophical discourse. The study begins by contextualizing the author's biography and education, emphasizing the decisive influence of Greco-Roman classicism and the reverberations of Victorian aestheticism. These cultural landmarks are examined to elucidate how they are intricately integrated into the novel's ideational and narrative structure. A detailed analysis of the paradigmatic oppositions Wilde mobilizes-idealism and materialism, spirit and body, truth and appearance-is offered to highlight the dialectical relationship between art and existence, a recurring theme throughout his oeuvre.  The analytical approach also considers Wilde's biographical condition, particularly his inner and social exile, reflected in the moral and aesthetic tensions experience by the protagonist within the context of a declining Victorian society. It aims to decode the novel's symbolic and aesthetic dimensions while situating it within the broader discourse of Wilde's contemporary aesthetic and ethical debates, exploring his ambivalence toward both traditional and modern values. This approach contributes to a nuanced and in-depth interpretation of Wilde's work, revealing the stratifications of his artistic discourse and the associated identity issues, in alignment with modern critical perspectives. 

Evy Beijen, Pien Pieterse, Yusuf Çelik et al.

Religious language continues to permeate contemporary discourse, even in ostensibly secular domains such as environmental activism and climate change debates. This paper investigates how explicit and implicit forms of religious language appear in climate-related texts produced by secular and religious nongovernmental organizations (NGOs). We introduce a dual methodological approach: a rule-based model using a hierarchical tree of religious terms derived from ecotheology literature, and large language models (LLMs) operating in a zero-shot setting. Using a dataset of more than 880,000 sentences, we compare how these methods detect religious language and analyze points of agreement and divergence. The results show that the rule-based method consistently labels more sentences as religious than LLMs. These findings highlight not only the methodological challenges of computationally detecting religious language but also the broader tension over whether religious language should be defined by vocabulary alone or by contextual meaning. This study contributes to digital methods in religious studies by demonstrating both the potential and the limitations of approaches for analyzing how the sacred persists in climate discourse.

Sneha Gathani, Kevin Li, Raghav Thind et al.

Various analytical techniques-such as scenario modeling, sensitivity analysis, perturbation-based analysis, counterfactual analysis, and parameter space analysis-are used across domains to explore hypothetical scenarios, examine input-output relationships, and identify pathways to desired results. Although termed differently, these methods share common concepts and methods, suggesting unification under what-if analysis. Yet a unified framework to define motivations, core components, and its distinct types is lacking. To address this gap, we reviewed 141 publications from leading visual analytics and HCI venues (2014-2024). Our analysis (1) outlines the motivations for what-if analysis, (2) introduces Praxa, a structured framework that identifies its fundamental components and characterizes its distinct types, and (3) highlights challenges associated with the application and implementation. Together, our findings establish a standardized vocabulary and structural understanding, enabling more consistent use across domains and communicate with greater conceptual clarity. Finally, we identify open research problems and future directions to advance what-if analysis.

Jai Kruthunz Naveen Kumar, Aishwarya Umeshkumar Surani, Harkirat Singh et al.

Reddit is a major venue for mental-health information interaction and peer support, where privacy concerns increasingly surface in user discourse. Thus, we analyze privacy-related discussions across 14 mental-health and regulatory subreddits, comprising 10,119 posts and 65,385 comments collected with a custom web scraper. Using lexicon-based sentiment analysis, we quantify emotional alignment between communities via cosine similarity of sentiment distributions, observing high similarity for Bipolar and ADHD (0.877), Anxiety and Depression (0.849), and MentalHealthSupport and MentalIllness (0.989) subreddits. We also construct keyword dictionaries to tag privacy-related themes (e.g., HIPAA, GDPR) and perform temporal analysis from 2020 to 2025, finding a 50% increase in privacy discourse with intermittent regulatory spikes. A chi-square test of independence across subreddit domains indicates significant distributional differences. The results characterize how privacy-oriented discussion co-varies with user sentiment in online mental-health communities.

Ruikun Hou, Babette Bühler, Tim Fütterer et al.

Classroom discourse is an essential vehicle through which teaching and learning take place. Assessing different characteristics of discursive practices and linking them to student learning achievement enhances the understanding of teaching quality. Traditional assessments rely on manual coding of classroom observation protocols, which is time-consuming and costly. Despite many studies utilizing AI techniques to analyze classroom discourse at the utterance level, investigations into the evaluation of discursive practices throughout an entire lesson segment remain limited. To address this gap, our study proposes a novel text-centered multimodal fusion architecture to assess the quality of three discourse components grounded in the Global Teaching InSights (GTI) observation protocol: Nature of Discourse, Questioning, and Explanations. First, we employ attention mechanisms to capture inter- and intra-modal interactions from transcript, audio, and video streams. Second, a multi-task learning approach is adopted to jointly predict the quality scores of the three components. Third, we formulate the task as an ordinal classification problem to account for rating level order. The effectiveness of these designed elements is demonstrated through an ablation study on the GTI Germany dataset containing 92 videotaped math lessons. Our results highlight the dominant role of text modality in approaching this task. Integrating acoustic features enhances the model's consistency with human ratings, achieving an overall Quadratic Weighted Kappa score of 0.384, comparable to human inter-rater reliability (0.326). Our study lays the groundwork for the future development of automated discourse quality assessment to support teacher professional development through timely feedback on multidimensional discourse practices.

Elena Chistova

We introduce UniRST, the first unified RST-style discourse parser capable of handling 18 treebanks in 11 languages without modifying their relation inventories. To overcome inventory incompatibilities, we propose and evaluate two training strategies: Multi-Head, which assigns separate relation classification layer per inventory, and Masked-Union, which enables shared parameter training through selective label masking. We first benchmark monotreebank parsing with a simple yet effective augmentation technique for low-resource settings. We then train a unified model and show that (1) the parameter efficient Masked-Union approach is also the strongest, and (2) UniRST outperforms 16 of 18 mono-treebank baselines, demonstrating the advantages of a single-model, multilingual end-to-end discourse parsing across diverse resources.

Daniel Brubaker, William Sheffield, Junyi Jessy Li et al.

The role of world knowledge has been particularly crucial to predict the discourse connective that marks the discourse relation between two arguments, with language models (LMs) being generally successful at this task. We flip this premise in our work, and instead study the inverse problem of understanding whether discourse connectives can inform LMs about the world. To this end, we present WUGNECTIVES, a dataset of 8,880 stimuli that evaluates LMs' inferences about novel entities in contexts where connectives link the entities to particular attributes. On investigating 17 different LMs at various scales, and training regimens, we found that tuning an LM to show reasoning behavior yields noteworthy improvements on most connectives. At the same time, there was a large variation in LMs' overall performance across connective type, with all models systematically struggling on connectives that express a concessive meaning. Our findings pave the way for more nuanced investigations into the functional role of language cues as captured by LMs. We release WUGNECTIVES at https://github.com/kanishkamisra/wugnectives