Hasil untuk "Discourse analysis"

Marida Nach, Ronney Ncwadi

Digitalisation is a key catalyst which transforms international trade by enhancing efficiency, reducing costs, expanding market access and unlocking new opportunities, significantly boosting export performance. Understanding this interplay is essential for Brazil, Russia, India, China and South Africa (BRICS) countries, major players in global trade. This study examines the digitalisation-exports relationship in BRICS, specifically how Information and Communication Technology (ICT) catalyses exports. Using a combination of panel and country-specific autoregressive distributed lag (ARDL) models, this method captures country heterogeneity and both short-term and long-term dynamics. Panel autoregressive distributed lag identifies common BRICS trends, while country-specific autoregressive distributed lag highlights distinctive country effects, strengthening the analysis. Results show that, in the short term, Information and Communication Technology’s effect on exports varies across models. However, in the long term, Information and Communication Technology consistently exerts a statistically significant effect. Findings emphasise digitalisation’s pivotal role in enhancing BRICS exports, particularly long term. Yet, effectiveness differs across countries. Disparities in digital infrastructure, digital literacy and institutional quality suggest digitalisation alone is insufficient. Addressing these challenges enables BRICS to leverage digitalisation and strengthen their position as prominent emerging export countries. This study contributes to the digital economy discourse with empirical evidence-based policy implications.

Haris Jamaludin, Budi Hartono, Arsito Ari Kuncoro

Inclusive education is critical to ensuring equitable learning opportunities for all students, regardless of their abilities or backgrounds. This study aims to analyze the optimization of inclusive education by implementing artificial intelligence (AI), focusing on identifying the opportunities and challenges that arise. A systematic literature review was conducted as the research method, referencing five journals related to the application of AI in education and other relevant sectors. The findings reveal that AI has significant potential to enhance the quality of inclusive education by enabling personalized learning materials, real-time student data analysis, and improved teacher-student interactions. These advancements can help address diverse learning needs and promote a more inclusive learning environment. However, several challenges must be addressed, including technological disparities, limited infrastructure, and ethical concerns related to AI usage, such as data privacy and algorithmic bias. The study concludes that the successful implementation of AI in inclusive education requires collaborative efforts among governments, educational institutions, and other stakeholders to ensure accessibility, equity, and sustainability. Key recommendations include the development of supportive policies, enhancement of digital literacy among educators and students, and investment in technological infrastructure to bridge the digital divide. This research contributes to the growing discourse on the integration of AI in education, providing insights for policymakers and practitioners aiming to harness AI's potential for inclusive education.

Mokhamad Sukron, Said Agil Husin Al-Munawar, Zaitunah Subhan et al.

This study investigates the interpretation of the Majelis Tafsir Al-Qur'an (MTA) regarding the obligation of Friday prayers for women, employing the analytical frameworks of Fiqh al-Ḥadīth and Maqāṣid al-Sharīʿah. MTA adopts a literal exegesis of QS. al-Jumuʿah: 9, asserting its universal applicability irrespective of gender. The study critically reevaluates the traditionally understood Hadiths to exempt women, interpreting them as providing legal flexibility rather than categorical exclusion. By applying sanad (chain of transmission) and matan (text-content) analysis, MTA integrates classical methodological rigor with contextual reasoning, thereby advocating a reformist yet tradition-conscious stance. This research highlights MTA's inclusive perspective as a significant contribution to contemporary Islamic legal discourse, aiming to promote enhanced religious participation and social cohesion. Nonetheless, the study identifies ongoing challenges, including contextual limitations and restricted mosque access for women. The findings underscore how MTA's interpretive model embodies a progressive rethinking of Islamic obligations in response to evolving social realities.

Varsha Suresh, M. Hamza Mughal, Christian Theobalt et al.

Research in linguistics shows that non-verbal cues, such as gestures, play a crucial role in spoken discourse. For example, speakers perform hand gestures to indicate topic shifts, helping listeners identify transitions in discourse. In this work, we investigate whether the joint modeling of gestures using human motion sequences and language can improve spoken discourse modeling in language models. To integrate gestures into language models, we first encode 3D human motion sequences into discrete gesture tokens using a VQ-VAE. These gesture token embeddings are then aligned with text embeddings through feature alignment, mapping them into the text embedding space. To evaluate the gesture-aligned language model on spoken discourse, we construct text infilling tasks targeting three key discourse cues grounded in linguistic research: discourse connectives, stance markers, and quantifiers. Results show that incorporating gestures enhances marker prediction accuracy across the three tasks, highlighting the complementary information that gestures can offer in modeling spoken discourse. We view this work as an initial step toward leveraging non-verbal cues to advance spoken language modeling in language models.

Osman Özdemir

The aim of this study is to examine the status of Turkish as a language of technology from the perspective of the past to the present and within the framework of the basic concepts of being a language of technology. Accordingly, the topic is discussed within the framework of technology, language, thought, science, and the relationship between technology and language. In this study, in which a basic qualitative research method was used, document analysis was preferred as a data collection tool. By considering relevant studies in the literature, an inductive data analysis was used to draw a framework for the issue of Turkish as a language of science. In the first part of the study, the basic concepts of language and technology were discussed from a historical perspective. Then, the status of language as a technology, the effect of language on thought and technology with its vocabulary set, technology shaping language and thoughtas a discourse, human language technology, and the contribution of technology to language by creating new concepts were discussed. In the findings section, the current situation of Turkish was analyzed through the issue of a language being a language of technology. Accordingly, the mutual relationship between Turkish and technology was discussed. In this section, the contributions of Turkish to technology and the effects of technology on Turkish were analyzed in two ways. Then, the impacts of Turkish on science and technology from past to present were mentioned from a historical perspective. Finally, the possibilities of Turkey as a future language of technology in the future were emphasized. In this direction, the potential of Turkish to be a language of technology in terms of its structure and its relationship with its processing as a language of science were mentioned.

Lishan Zhang, Han Wu, Xiaoshan Huang et al.

Deductive coding is a common discourse analysis method widely used by learning science and learning analytics researchers for understanding teaching and learning interactions. It often requires researchers to manually label all discourses to be analyzed according to a theoretically guided coding scheme, which is time-consuming and labor-intensive. The emergence of large language models such as GPT has opened a new avenue for automatic deductive coding to overcome the limitations of traditional deductive coding. To evaluate the usefulness of large language models in automatic deductive coding, we employed three different classification methods driven by different artificial intelligence technologies, including the traditional text classification method with text feature engineering, BERT-like pretrained language model and GPT-like pretrained large language model (LLM). We applied these methods to two different datasets and explored the potential of GPT and prompt engineering in automatic deductive coding. By analyzing and comparing the accuracy and Kappa values of these three classification methods, we found that GPT with prompt engineering outperformed the other two methods on both datasets with limited number of training samples. By providing detailed prompt structures, the reported work demonstrated how large language models can be used in the implementation of automatic deductive coding.

S. M. Seals, Valerie L. Shalin

The summarization of conversation, that is, discourse over discourse, elevates pragmatic considerations as a pervasive limitation of both summarization and other applications of contemporary conversational AI. Building on impressive progress in both semantics and syntax, pragmatics concerns meaning in the practical sense. In this paper, we discuss several challenges in both summarization of conversations and other conversational AI applications, drawing on relevant theoretical work. We illustrate the importance of pragmatics with so-called star sentences, syntactically acceptable propositions that are pragmatically inappropriate in conversation or its summary. Because the baseline for quality of AI is indistinguishability from human behavior, we draw heavily on the psycho-linguistics literature, and label our complaints as "Turing Test Triggers" (TTTs). We discuss implications for the design and evaluation of conversation summarization methods and conversational AI applications like voice assistants and chatbots

Chenxu Wang, Ping Jian, Mu Huang

Implicit Discourse Relation Recognition (IDRR), which infers discourse relations without the help of explicit connectives, is still a crucial and challenging task for discourse parsing. Recent works tend to exploit the hierarchical structure information from the annotated senses, which demonstrate enhanced discourse relation representations can be obtained by integrating sense hierarchy. Nevertheless, the performance and robustness for IDRR are significantly constrained by the availability of annotated data. Fortunately, there is a wealth of unannotated utterances with explicit connectives, that can be utilized to acquire enriched discourse relation features. In light of such motivation, we propose a Prompt-based Logical Semantics Enhancement (PLSE) method for IDRR. Essentially, our method seamlessly injects knowledge relevant to discourse relation into pre-trained language models through prompt-based connective prediction. Furthermore, considering the prompt-based connective prediction exhibits local dependencies due to the deficiency of masked language model (MLM) in capturing global semantics, we design a novel self-supervised learning objective based on mutual information maximization to derive enhanced representations of logical semantics for IDRR. Experimental results on PDTB 2.0 and CoNLL16 datasets demonstrate that our method achieves outstanding and consistent performance against the current state-of-the-art models.

Hamdullah Baycar, Mehmet Rakipoglu

The United Arab Emirates (UAE) proposes “peaceful” religious discourse by supporting religious scholars such as Hamza Yusuf and Abdallah bin Bayyah and institutions such as the Forum for Promoting Peace in Muslim Societies and the Emirates Fatwa Council. The UAE has attempted to present itself as promoting a moderate form of Islam to counter political Islam. This study is based on data from religious verdicts (<i>fatwās</i>), speeches, and conference records of these scholars and institutions. The main point of the research is to show to what extent providing additional support to recently established religious institutions and emerging scholars is used as soft power to promote the UAE’s version of Islam and present the UAE as a moderate and tolerant country. Applying critical discourse analysis, the study aims to uncover the existing connection between emerging religiopolitical discourse and UAE-based legal verdicts of scholars (<i>ulamā</i>) and the organizations that they initiated. This study further argues that “moderate Islam” and “tolerance”, used as religious soft power, are other tools that the UAE has applied in line with expectations for influence and power-seeking based on small state theory.

Aisha Alaa Saleh, Khalid Abdul Wahab Al-Mudares

Contemporary urban discourse is paying increasing attention to the issue of urban resilience, due to the stresses, disasters and disturbances (natural and human) that the cities of the world are experiencing and facing, which confirms the need to be familiar with the concept of urban resilience, its dimensions, practices, and characteristics at different levels; In order to reach the aspects of developing the urban energy sector in them, and in a way that supports the preparedness of cities to face potential expected and unexpected disturbances in the future, as cities are usually formed from many main and sub-systems that are dynamically intertwined with each other, such as: the social and economic system, infrastructure systems, land use, and media Various transports, which have a high level of direct interactions with the natural environment; ; It is therefore necessary to understand how the city deals with the odds of threats and challenges in an integrated manner; To overcome its weaknesses and enhance its resilience of use, which aims to make cities more secure, resilient and sustainable in the future, as well as that requires rethinking the field of expanding the use of renewable energies and the general urban landscape. To become a search problem “Failure to exploit the potential of natural energies on the possibility of exploiting renewable natural energies with their components (active and passive) in the production of resilience urban formations in cities.” The aim of the research is to try to "extract an integrated theoretical framework on the characteristics of urban energy resilience from international and Arab experiences, and to diagnose its most important planning and design pillars and indicators, which can be adopted to evaluate the reality of urban energy resilience in local cities." The research hypothesized that “the exploitation of energy systems produced from renewable natural resources, for the purposes of environmental treatments for resilient cities, especially in the buildings of housing projects and their urban surroundings, reduces the consumption of fossil energies for the city, frees its sites from linking to depleted energy transmission networks, and reduces potential environmental pollution problems, which contributes to in the production of flexible energy systems and helps in the generation of flexible cities." The descriptive analysis method was adopted.

Marika Vicziany, Jaideep Hardikar

This paper evaluates India’s first officially approved self-administered rapid antigen test kit against COVID-19, a device called CoviSelf. The context is rural India. Rapid antigen tests (RATs) are currently popular in situations where vaccination rates are low, where sections of the community remain unvaccinated, where the COVID-19 pandemic continues to grow and where easy or timely access to RTPCR (reverse transcription-polymerase chain reaction) testing is not an option. Given that rural residents make up 66% of the Indian population, our evaluation focuses on the question of whether this self-administered RAT could help protect villagers and contain the Indian pandemic. CoviSelf has two components: the test and IT (information technology) parts. Using discourse analysis, a qualitative methodology, we evaluate the practicality of the kit on the basis of data in its instructional leaflet, reports about India’s ‘digital divide’ and our published research on the constraints of daily life in Indian villages. This paper does not provide a scientific assessment of the effectiveness of CoviSelf in detecting infection. As social scientists, our contribution sits within the field of qualitative studies of medical and health problems. Self-administered RATs are cheap, quick and reasonably reliable. Hence, point-of-care testing at the doorsteps of villagers has much potential, but realising the benefits of innovative, diagnostic medical technologies requires a realistic understanding of the conditions in Indian villages and designing devices that work in rural situations. This paper forms part of a larger project regarding the COVID-19 pandemic in rural India. A follow-up study based on fieldwork is planned for 2022–2023.

Cécile Bruyet

Abstract Wondering how medieval people perceived their environment has long moved scholars onto untamed research paths. A strong focus on scholastic writings as sources has left an unfinished picture of medieval societies’ perceptions of nature. Pilgrimage accounts written by lay authors offer a rare opportunity to explore other perspectives on nature, although of course in a setting which was profoundly shaped by religious experience and tradition. Through the example of Arnold von Harff, travelling between 1496 and 1498 in the Mediterranean, I propose methods to recognise the different coexisting attitudes towards the natural world, theorised by David Herlihy, in secular writings. Combining discourse analysis with literary GIS, I suggest some explanations as to why travellers would switch between attitudes along their journey, and how spatio-temporal parameters influenced their decisions. As a result, we understand that fear was only one of von Harff’s many attitudes to the natural world, and that his ability to stage different aspects of his identity was firmly determining his perception(s) of nature. By interpreting the landscapes in the Eastern and Western Mediterranean differently, von Harff could learn from and about the environment, suggesting that secular travel was commendable along the allegedly strict pilgrimage roads.

Patrick Huber, Giuseppe Carenini

With a growing number of BERTology work analyzing different components of pre-trained language models, we extend this line of research through an in-depth analysis of discourse information in pre-trained and fine-tuned language models. We move beyond prior work along three dimensions: First, we describe a novel approach to infer discourse structures from arbitrarily long documents. Second, we propose a new type of analysis to explore where and how accurately intrinsic discourse is captured in the BERT and BART models. Finally, we assess how similar the generated structures are to a variety of baselines as well as their distribution within and between models.

Nicole Doerr

This article is an empirical investigation into the visual mobilization strategies by far-right political parties for election campaigns constructing Muslim immigrants as a “threat” to the nation. Drawing on an interdisciplinary theoretical approach of social movement studies and research on media and communication, I focus on the far-right political party Alternative for Germany (AfD), which has produced several widespread inflammatory series of visual election posters featuring anti-Islam rhetoric, combined with provocative images of gender and sexuality. By approaching visual politics through a perspective on actors constructing visual forms of political mobilization, I show how far-right populist “movement parties” are supported by professional graphic designers commercializing extremist ideologies by creating ambivalent images and text messages. My findings on the AfD’s visual campaign politics document the instrumentalization and appropriation of the rhetoric of women’s empowerment and LGBT rights discourse, helping the AfD to rebrand its image as a liberal democratic opposition party, while at the same time, maintaining its illiberal political agenda on gender and sexuality. Visual representations of gender and sexuality in professionally created election posters served to ridicule and shame Muslim minorities and denounce their “Otherness”—while also promoting a heroic self-image of the party as a savior of white women and Western civilization from the threat of male Muslim migrants. By documenting the visual politics of the AfD, as embedded in transnational cooperation between different actors, including visual professional graphic designers and far-right party activists, my multimodal analysis shows how far-right movement parties marketize and commercialize their image as “progressive” in order to reach out to new voters.

Rania Ahmed

This research proposes a cognitive semantic study of the mental framework of the self in search of its identity in the universe of the other. It is the self of the heroine of Camille Laurens' novel Dans ces bras-là, which espouses a postmodern vision in the construction of its fragmentary novelistic discourse. The present study postulates an analysis of the conceptual structure with which the semantic structure of Camille Laurens’s text identifies. It tends to study the cognitive framework of the quest for the ego and to analyze the categories that emerge from it. It is about defining the concepts by which the heroine's ego has segmented her environment of men into meaningful categories. My aim is constructivist and my approach is based on two levels: The extra-linguistic level where I will study the conceptual structure of Laurens' text, and the linguistic level where I will study the semantic isotopes that dominate the text in view to access its cognitive coherence.

Zhengyuan Liu, Nancy F. Chen

While multi-party conversations are often less structured than monologues and documents, they are implicitly organized by semantic level correlations across the interactive turns, and dialogue discourse analysis can be applied to predict the dependency structure and relations between the elementary discourse units, and provide feature-rich structural information for downstream tasks. However, the existing corpora with dialogue discourse annotation are collected from specific domains with limited sample sizes, rendering the performance of data-driven approaches poor on incoming dialogues without any domain adaptation. In this paper, we first introduce a Transformer-based parser, and assess its cross-domain performance. We next adopt three methods to gain domain integration from both data and language modeling perspectives to improve the generalization capability. Empirical results show that the neural parser can benefit from our proposed methods, and performs better on cross-domain dialogue samples.

Yuchen He, Zhuosheng Zhang, Hai Zhao

Multi-party dialogue machine reading comprehension (MRC) raises an even more challenging understanding goal on dialogue with more than two involved speakers, compared with the traditional plain passage style MRC. To accurately perform the question-answering (QA) task according to such multi-party dialogue, models have to handle fundamentally different discourse relationships from common non-dialogue plain text, where discourse relations are supposed to connect two far apart utterances in a linguistics-motivated way.To further explore the role of such unusual discourse structure on the correlated QA task in terms of MRC, we propose the first multi-task model for jointly performing QA and discourse parsing (DP) on the multi-party dialogue MRC task. Our proposed model is evaluated on the latest benchmark Molweni, whose results indicate that training with complementary tasks indeed benefits not only QA task, but also DP task itself. We further find that the joint model is distinctly stronger when handling longer dialogues which again verifies the necessity of DP in the related MRC.

Jiaqi Li, Ming Liu, Zihao Zheng et al.

Multiparty Dialogue Machine Reading Comprehension (MRC) differs from traditional MRC as models must handle the complex dialogue discourse structure, previously unconsidered in traditional MRC. To fully exploit such discourse structure in multiparty dialogue, we present a discourse-aware dialogue graph neural network, DADgraph, which explicitly constructs the dialogue graph using discourse dependency links and discourse relations. To validate our model, we perform experiments on the Molweni corpus, a large-scale MRC dataset built over multiparty dialogue annotated with discourse structure. Experiments on Molweni show that our discourse-aware model achieves statistically significant improvements compared against strong neural network MRC baselines.

Jay Chen, Barath Raghavan, Paul Schmitt et al.

Online discourse takes place in corporate-controlled spaces thought by users to be public realms. These platforms in name enable free speech but in practice implement varying degrees of censorship either by government edict or by uneven and unseen corporate policy. This kind of censorship has no countervailing accountability mechanism, and as such platform owners, moderators, and algorithms shape public discourse without recourse or transparency. Systems research has explored approaches to decentralizing or democratizing Internet infrastructure for decades. In parallel, the Internet censorship literature is replete with efforts to measure and overcome online censorship. However, in the course of designing specialized open-source platforms and tools, projects generally neglect the needs of supportive but uninvolved `average' users. In this paper, we propose a pluralistic approach to democratizing online discourse that considers both the systems-related and user-facing issues as first-order design goals.

Risha Iffatur Rahmah, Budinuryanta Yohanes, Suhartono Suhartono

SEXIST LANGUAGE IN THE SPEECH OF MOSLEM FEMALE PREACHERS (CRITICAL DISCOURSE ANALYSIS) Abstract: This study aims to find sexist language in the speech of female preachers through representation, interpretation, and forms of discrimination in the text. This study used a qualitative phenomenological research method and used critical discourse analysis by Faircloughn as supporting the data. The data shows that females speak more sexist if they talk to the same gender than a different gender. From this phenomenon, the impact on the use of vocabularies that license gender identity by using the terms marked, unmarked, and semantic derogation. There are other relationships with grammar using declarative, imperative, and interrogative sentence types in intentionality modalities; epistemic; deontic; dynamic. This relationship also discussed the uses of mentioning text in a text structures by convection of relationships, structuring, and ordering a text. Keywords: Sexist language, Gender discrimination, Representation, Gender identity, Prejudice   BAHASA SEKSIS PADA PEREMPUAN PENCERAMAH AGAMA ISLAM (ANALISIS WACANA KRITIS) Abstrak: Penelitian ini bertujuan untuk menemukan bahasa seksis pada tuturan perempuan penceramah melalui representasi, intepretasi, dan bentuk diskriminasi dalam analisis teks. Temuan tersebut diproses dari metode analisis wacana kritis Fairclough dengan jenis penelitian kualitatif fenomenologis. Hasil penelitian ini menunjukkan bahwa perempuan penceramah bertutur seksis terhadap perempuan dibandingkan laki-laki, meskipun keduanya juga sama-sama terseksiskan. Representasi tuturanya mengarah pada hubungan budaya di antara peranan suami, istri, dan mertua.Sedangkan, intepretasi keseksisannya ada pada pelemahan identitas gender baik laki-laki maupun perempuan.  Hal ini berdampak pada penggunaan kosakata yang melemahkan identitas gender dengan menggunakan istilah bertanda, tidak bertanda, dan derograsi semantik. Adapun hubungan lainnya terdapat pada tata bahasa dengan menggunakan jenis kalimat deklaratif, imperatif, dan introgatif dalam modalitas intensionalitas; epistemik; deontik; dinamik. Hubungan ini juga disertai penggunaan penyebutan pronominal di struktur teks dengan konveksi interaksi, penataan, dan pengurutan teks. Kata kunci: Bahasa seksis, Diskriminasi gender, Representasi, Identitas gender, Prasangka