Digital Discourse Research Articles

Hashtag War in Gaza: An Analysis of the Role of Indonesian Citizens in #JulidFisabilillah from the Transnational Conflict Dimension

Abstract: The Israeli-Palestinian conflict not only has an impact on land but also extends to cyberspace. This research investigates the digital landscape of the Israeli-Palestinian conflict, specifically focusing on online activism surrounding the Gaza conflict. This research investigates the hashtag #JulidFisabilillah, a leading online movement originating from Indonesian citizens. Through comprehensive analysis, this research aims to uncover the motivations, narratives, and impacts of #JulidFisabilillah in the broader context of the Israeli-Palestinian War. By examining digital discourse, social media trends, and the role of Indonesian society in shaping online narratives, this research provides insight into the transnational dimensions of the conflict and the influence of digital activism on public opinion. These findings contribute to a deeper understanding of the role played by Indonesian netizens on online platforms in mobilizing global support and shaping perceptions during geopolitical conflicts.

LLMs Among Us: Generative AI Participating in Digital Discourse

The emergence of Large Language Models (LLMs) has great potential to reshape the landscape of many social media platforms. While this can bring promising opportunities, it also raises many threats, such as biases and privacy concerns, and may contribute to the spread of propaganda by malicious actors. We developed the "LLMs Among Us" experimental framework on top of the Mastodon social media platform for bot and human participants to communicate without knowing the ratio or nature of bot and human participants. We built 10 personas with three different LLMs, GPT-4, Llama 2 Chat, and Claude. We conducted three rounds of the experiment and surveyed participants after each round to measure the ability of LLMs to pose as human participants without human detection. We found that participants correctly identified the nature of other users in the experiment only 42% of the time despite knowing the presence of both bots and humans. We also found that the choice of persona had substantially more impact on human perception than the choice of mainstream LLMs.

Toward Inclusivity: Rethinking Islamophobic Content Classification in the Digital Age

In this paper, we implement a comprehensive three class system to categorize social media discussions about Islam and Muslims, enhancing the typical binary approach. These classes are: I) General Discourse About Islam and Muslims, II) Criticism of IslamicTeachings and Figures, and III) Comments Against Muslims. These categories are designed to balance the nuances of free speech while protecting diverse groups like Muslims, ex-Muslims, LGBTQ+ communities, and atheists. By utilizing machine learning and employing transformer-based models, we analyze the distribution and characteristics of these classes in social media content. Our findings reveal distinct patterns of user engagement with topics related to Islam, providing valuable insights into the complexities of digital discourse. This research contributes to the fields of quantitative social science by offering an improved method for understanding and moderating online discussions on sensitive religious and cultural subjects.

Museums, Climate Change and Energy Education: A Digital Discourse Analysis

Abstract The purpose of this study was to explore how science and environmentally related museums in Alberta, Canada are digitally engaging with climate change and energy education. This inquiry utilised qualitative discourse analysis to examine the discourses, dynamics and tensions present in digital museum contexts related to climate and energy education in Alberta. Drawing on Eisner’s three curricula — the explicit, implicit and null — the study focused on museums’ websites and social media activity. The museums studied share common foci on science, environment, or energy but range in size and location. As a long-standing energy-based economy, Alberta provides an interesting, and often contested, setting to observe climate and energy education in practice at museums, many of which exist in communities and within governance and stakeholder networks which are connected to the energy industry. Discourse-connected findings, discussion and implications are presented in relation to museums’ institutional mandates, curricular initiatives, pedagogical practices, special events and infrastructure initiatives.

Settle for Biden: The scalar production of a normative presidential candidate on Instagram

Abstract This article performs a multimodal digital discourse analysis to examine how the 2020 social media political campaign called ‘Settle for Biden’ successfully encouraged young Progressives to vote for Joe Biden. In contrast to previous US presidential campaigns that highlight the extraordinary capabilities of their candidates, this campaign utilized the scalar and chronotopic production of normativity to highlight Biden's ‘mediocre’ capabilities. The campaign's focus on ‘settling’ for a mediocre candidate was feasible only in the sociopolitical context of 2020, at a time when Donald Trump's leadership had come to be perceived as chaotic and dangerous. While using humor to make salient the normal nature of Biden, the campaign used semiotic strategies appealing to interconnected unmarked normativities associated with class, age, race, and gender. To draw on Hall (2021), the campaign produces ‘language in the middle’, constructing Biden as neither extraordinary nor reprehensible yet preferable to the abnormality of his competitor. (Normativity, scales, chronotopes, multimodality, intertextuality, politics, social media)*

Beyond Echo Chambers: Unraveling the Impact of Social Media Algorithms on Consumer Behavior and Exploring Pathways to a Diverse Digital Discourse

Purpose: This study delves into the intricate dynamics of how social media algorithms cultivate echo chambers, with a focus on their profound influence on consumer behavior. Methodology: Through an exhaustive review of existing literature and detailed case studies, we explore the mechanisms by which personalized content delivery systems on social media platforms not only reinforce users' pre-existing beliefs and preferences but also significantly impact their consumption patterns, decision-making processes, and overall perception of reality. Findings: Our analysis reveals that while these algorithms are designed to enhance user engagement and satisfaction, they inadvertently foster digital polarization, diminish exposure to diverse viewpoints, and contribute to the spread of misinformation. The paper further investigates the broader societal implications of these echo chambers, including decreased public trust in traditional information sources and the erosion of democratic discourse. To counteract these effects, we propose a multifaceted approach encompassing increased algorithmic transparency, user empowerment through digital literacy education, and policy interventions aimed at encouraging content diversity. Unique Contribution to Theory, Policy and Practice: Our recommendations are designed to mitigate the echo chamber effect and foster a more inclusive and well-informed online public sphere. By addressing these challenges, we underscore the need for a concerted effort among stakeholders—including policymakers, educators, and technology developers—to navigate the complexities of the digital landscape and ensure a more diverse and resilient digital environment.

Jai Mackenzie, Connected parenting: Digital discourses and diverse family practices. London: Bloomsbury, 2023. Pp. 248. Hb. £96.

Jai Mackenzie, Connected parenting: Digital discourses and diverse family practices. London: Bloomsbury, 2023. Pp. 248. Hb. £96.

Exploring Stress Detection in Tweets: A Comparative Business Analysis of Classification Algorithms

Abstract: In today's digitally-driven landscape, social media platforms such as Twitter, Facebook, and WordPress have emerged as critical conduits for public discourse, resulting in an overwhelming influx of unprocessed data, particularly on Twitter. Coping with the sheer volume of this data presents a significant challenge. To address this, sentiment analysis, a technique that categorizes sentiments into positive, negative, or neutral, offers a promising solution. This study delves into three main approaches for sentiment analysis: Machine learning-based methods, Sentiment lexicon-based approaches, and Hybrid methods. Its primary research objectives revolve around the identification of suitable algorithms and metrics for evaluating the performance of Machine Learning Classifiers. Additionally, the study aims to compare these metrics with respect to the dataset size, gauging their impact on the most appropriate sentiment analysis algorithm.The research methodology applied is experimental, entailing a rigorous assessment of algorithms using carefully selected metrics. The results of this investigation spotlight Naïve Bayes, Random Forest, XGBoost, and CNN-LSTM as the leading machine learning algorithms under consideration. These algorithms are assessed based on key performance metrics such as precision, accuracy, F1 score, and recall. Notably, the CNN-LSTM model emerges as the optimal choice for sentiment analysis of Twitter data within the specified dataset size, achieving a remarkable accuracy rate of 88%.In summary, this research successfully pinpoints the most suitable algorithm for sentiment analysis of Twitter data, especially in the context of dataset size. The CNN- LSTM model showcases its effectiveness, serving as a robust tool for sentiment analysis and delivering an impressive accuracy rate. This study significantly enhances our comprehension of public sentiment on Twitter, providing valuable insights into the ever-evolving realm of digital discourse and the analysis of vast unprocessed data

The emergence of the synergistically complex power in digital era: challenges to human capital

The article examines the dynamics of power in the context of the specifics of digital discourse from the industrial modernity up to the modern times. This is determined by the transition from one episteme of knowledge and thinking to another, the emergence of a network society, as well as digitalization processes. The author substantiates the claim that under the influence of these factors, the nature of power is permanently becoming more complex, acquiring an increasingly hybrid character amd also pays special attention to the analysis of the ambivalent consequences of the nonlinear transformations of power for the formation of human capital: on the one hand, newly created power resources are used for the benefit of people, however, like all complex innovation processes, the development of power is accompanied by unintentional “collateral damage” (Z. Bauman), which takes the form of challenges to irrational rationality, dehumanization, on which both those in power and the governed are forced to reflect, displaying their social responsibility. The factors contributing to the formation of a synergistically complex power are specifically revealed, including: speed, network realities, symbolic codes, “digital revolution” and “digital metamorphosis” (U. Beck). In conclusion, the author suggests some possible government responses to the challenges that have arisen: strengthening the social responsibility component of the human capital; taking into account the specifics of national realities, historical memory, and the established value realities in the life-worlds of Russians; the formation of “bridges” connecting peoples in line with the emergence of a multipolar world, with the aim to codevelop global and national-local human capital, sustainable development of the country and the world.

Discurso digital e divulgação científica no Twitter: análise da heterogeneidade tecnoenunciativa em tuíte reunido pela hashtag #divulgaçãocientífica

This article presents partial results of Glück's thesis (2024). The study aimed to investigate the phenomenon of technoenunciative heterogeneity, in particular the reported technodiscourse, and its implications for science communication action in a scientific dissemination tweet gathered from the hashtag #divulgaçãocientífica. From a theoretical point of view, Digital Discourse Analysis concepts are presented, according to Marie-Anne Paveau, as well as Sophie Moirand's postulations about corpora extension in a digital environment. The analysis of the tweet generated consisted of the following steps: (i) generation of data for analysis on the topic of science dissemination; (ii) description of the tweet from the data generated from the Twitter ecosystem; (iii) identification of strategies for materializing technoenunciative heterogeneity, via Paveau; (iv) considerations about the materialization of the phenomenon of technoenunciative heterogeneity and its implication for scientific dissemination. The analysis corroborates the fact that native digital discourses are of a technolinguistic nature, in a true composite from an ecological, symmetrical, and post-dualist perspective.

Psycholinguistic underpinnings of image formation: Suggestion and manipulation in the educational network discourse

This study delves into the intricate psycholinguistic mechanisms that underpin image formation within the educational network discourse, with a specific focus on the dynamics of suggestion and manipulation. In an era where digital communication reigns supreme, understanding how language shapes perceptions and influences behavior is paramount. This research seeks to unravel the complex interplay between suggestion, manipulation, and the formation of images within educational networks. Drawing from insights across disciplines such as psychology, linguistics, and communication studies, this study examines how linguistic cues and contextual factors interact to shape individuals' perceptions and responses within educational settings. Acknowledging the transformative power of language in shaping attitudes, beliefs, and actions, this study aims to shed light on the subtle yet profound ways in which educators employ linguistic strategies to influence discourse within educational networks. By employing a multifaceted approach that integrates theoretical frameworks with empirical analysis, this research endeavors to uncover the underlying mechanisms driving suggestion and manipulation within educational discourse. Through a meticulous examination of textual elements, discourse patterns, and communicative strategies employed by educators in digital environments, this study seeks to elucidate the intricate processes involved in image formation. By exploring the role of suggestion and manipulation in shaping perceptions, attitudes, and behaviors, this research contributes to a deeper understanding of the psycholinguistic underpinnings of educational network discourse. Furthermore, this study not only offers theoretical insights but also practical implications for educators, policymakers, and practitioners involved in educational communication. By highlighting the ethical considerations and implications of linguistic manipulation within educational networks, this research aims to empower stakeholders to navigate digital discourse with greater awareness and discernment. In conclusion, this study represents a significant contribution to the field of thinking skills and creativity by offering new insights into the psycholinguistic dynamics of image formation within educational networks. By unraveling the complexities of suggestion and manipulation, this research opens avenues for further inquiry and underscores the importance of critical thinking and creativity in navigating contemporary digital landscapes.

Decoding Digital Discourse: Artificial Intelligence – powered Cyberbullying Detection

Social media platforms have fundamentally transformed how people share information and communicate. While they offer significant benefits, they also pose challenges, such as the increasing prevalence of cyberbullying. While many studies have emphasized the accuracy of text classification techniques for detecting cyberbullying, this research explores the potential of automating not just the detection but also the reporting of harmful posts. We developed a Support Vector Machine model using WEKA, designed to identify cyberbullying statements in the English language. This model yielded an accuracy of 57% with a kappa score of 0.2094. After developing the model, we extracted public posts from Twitter and applied text preprocessing methods, including cleaning and tokenization. These preprocessed data were then transformed into a Bag-of- Words (BoW) representation. When a post is identified as cyberbullying by our model, a comprehensive report is generated detailing the author's name, post content, and the timestamp. This innovative method holds promise for the timely detection of malicious content, offering social media platform administrators an efficient tool for prompt intervention.

The Hardware Turn in the Digital Discourse: An Analysis, Explanation, and Potential Risk

The Hardware Turn in the Digital Discourse: An Analysis, Explanation, and Potential Risk

Exploring Linguistic Innovations within Chinese Internet Slang in Language and Social Media

This paper explores the dynamic landscape of Chinese internet slang and digital culture, analyzing its evolution, impact, and challenges. Through case studies and critical analysis, it delves into the linguistic innovations, cultural implications, and societal dynamics shaping digital discourse in contemporary China. The study investigates the emergence of new slang terms, the role of digital platforms in fostering online communities, and the complexities of navigating privacy concerns and regulatory frameworks. By examining future directions and implications, the paper seeks to offer insights into the transformative potential of Chinese internet slang and digital culture in shaping communication, identity, and social interactions in the digital age.

Muslim women consumers: Critical interpretations of US modest fashion brands entangled with the fashion-advocacy-capitalist-façade

Following 9/11, some young Muslim American women have been wearing hijabs to assert their Islamic identities. They are also seeking fashionable modest clothing, yet, despite their growing buying power, the US modest fashion market targeting Muslim women appears underserved. The purpose of this study was to critically examine how niche modest fashion brands in the United States target Muslim women while drawing upon theoretical concepts centring on oppression and agency related to the long history of gendered Islamophobia Muslims have experienced. We analysed eleven brands’ websites and social media applying the constant comparative method and identified four themes: empowering Muslim women, reclaiming modesty as modern and beautiful, meeting fashionable modest wear demand, and rejecting and perpetuating colourism. In our analysis of the digital discourses of US modest fashion brands, we revealed that these brands emerged to meet the demand of young Muslim woman in the United States who are embracing the hijab and modest clothing as a potent symbol of resistance against western ideologies, the fashion system’s oppressive acts towards Muslim women and traditional Islamic dress codes. Yet, their advocacy-centred messages – empowerment, reclaiming modesty as beautiful – operate within a profit-driven system, which we theorize as a fashion-advocacy-capitalistic-façade. The fashion-advocacy-capitalist-façade concept helps explain the slippery slope that fashion brands are tiptoeing as they aim to empower Muslim women, offer trendy modest clothing, reject traditional Islamic dress codes for women and create space in the fashion market for this unmet demand. Although these brands aim to promote a positive sense of self for Muslim women, they cannot be withheld from critical examination and potential interpretations when operating within the capitalist-driven industry that is so often plagued with significant injustices.

Концепт СЛАКТИВИЗМ и его реализация в сетевых дискурсивных практиках (на материале русского, английского и французского языков)

This publication is conducted in the stream of studying neology in the modern language influenced by the active use of internet communication and network discursive practices. The aim of the research is to identify the semantic and pragmatic characteristics of the linguistic realization of the concept of SLACKTIVISM. The social significance of the concept is asserted, its intersections and relationships with semantically similar concepts such as PROPAGANDA, ACTIVISM circulating in the modern networked information space are determined. The scientific novelty of the conducted research lies in providing a systematic description of a new, unstudied concept in domestic philology, on the basis of the Russian, English, and French languages. This includes accentuating the history of its emergence, the contradictory nature of its linguistic implementation in the digital discourse of new media, and network techno-discursive practices. As a result, the concept of SLACKTIVISM is portrayed as an expression of a new form of internet activity that contributes to social and political changes both on a narrow scale and in the broader geopolitical space. The linguistic level examination indicates preferences for figurative nominations and common means of representation in European languages and national-cultural specificity.

Who is our friend and who is our enemy? The enregisterment of tribalising digital discourse during the COVID-19 pandemic

Abstract This study demonstrates how tribalism and nationalism, exacerbated by the COVID-19 pandemic, have given rise to the enregisterment of a cultural discursive practice – dui (怼) – on Chinese social media. Based on a sample of social media posts collected through a combination of ‘noticing’ and systematic data scanning and archiving over a month, our analysis shows that dui shifted from a discursive practice of friendly teasing, a specific function that underpinned its rise of popularity prior to the onset of the pandemic, to an oppositional discursive practice characterised by wrangling, words of violence and a conversationalised journalistic discourse of refuting. We argue that COVID-19 has heightened Chinese netizens’ sensitivities towards China’s perceived friends and enemies. This politicisation, together with the associated traditional discourses of national pride and humiliation, contributed to the emergence of dui as a tribalising discourse, which in turn has further destabilised and polarised the user community on Chinese social media and beyond. The study illustrates the mutually constitutive nature of the enregisterment of discursive practices and social relationships and the importance of bringing together discourse analytical and socio-cultural perspectives in analytical terms.

The Changing Face of Free Speech: A Study of Article 19 in the Digital Age in India

In the digital age, India’s narrative of free speech has encountered both evolution and turbulence. Rooted in the democratic ethos, Article 19 of the Indian Constitution safeguards this freedom, reflecting the country’s commitment to upholding a citizen’s right to express. With the proliferation of online platforms—ranging from social media to news portals—the citizens have found dynamic avenues to articulate their viewpoints. As Nelson Mandela once said, “To be free is not merely to cast off one’s chains but to live in a way that respects and enhances the freedom of others.” However, this freedom has its pitfalls in the digital realm: the rapid dissemination of misinformation and the perils of divisive rhetoric. This research delves into the protective umbrella of Article 19 of the Constitution, emphasizing its pivotal role in safeguarding expression. The current landscape necessitates a balance, a careful navigation between the unrestricted flow of opinions and the dangers of digital misinformation. Issues of censorship, both governmental and self-imposed, further complicate this balance. As the world envisages the future of India’s digital discourse, it becomes paramount to ensure that the sanctity of free speech, as championed by Article 19, is preserved, yet responsibly exercised. Conclusively, the paper underscores the imperative of navigating the nuanced balance between unbridled digital expression and the responsibilities accompanying it, all through the lens of Article 19.

Analysing the Functionality of Twitter for Science Dissemination in EFL Teaching and Learning

Communication through social media is a phenomenon whose relevance has involved the consideration of online discourse in the language teaching context. This article explores the functionality of Twitter (now called “X”) for science dissemination within the teaching and learning of English as a foreign language. To do this, 100 tweets from the accounts @WWF and @Greenpeace were gathered and analysed from the perspective of digital discourse analysis and communicative language teaching. I argue that using these tweets encourages the development of key competencies, provides room for the practice of integrated skills, and enhances the application of 21st-century skills. Conclusively, science dissemination tweets may be considered adequate for teaching and learning English.

The Speech Genre of Commentary as a Way to Realize the Social Needs of Internet Communication Participants (Based the Survey Results).

The Speech Genre of Commentary as a Way to Realize the Social Needs of Internet Communication Participants (Based the Survey Results). The article studies commenting as a speech activity for creating and reading comments and an effective way to realize the social needs of representatives of a digital society. It reveals the features of comments as a primary network genre existing in the context of network discourse. During the research, a survey of Russian-speaking Internet users was conducted. The following conclusions are made: network users create a digital discourse designed to meet their needs for social interaction on a new emotional and cognitive level, as well as the need for self-expression in the outer world. The specific speech norms of commenting are: sincerity, focus on personal experience; constructiveness; positivity; benevolence; usefulness, relevance; "the right of the speaker". The results of the work can be used as a basis for further research of network discourse, communication on the Internet, in the process of codification of communicative and ethical norms of network communication, as well as in sociological researches of digital society.