Social Media Discourse Research Articles

Linguistic Landscapes of Social Media Discourse: Exploring Language Practices and Identities on Jordanian Online Platforms

The present research is designed to investigate the language practices and identities of Jordanian users on the selected social media platforms of Facebook and Twitter. A total of 400 posts and tweets were selected from both social media platforms. Based on the Systemic Functional Linguistics theory, the study found that the users demonstrated various language practices on social media like code-switching, emojis, localized expressions, and identity affiliations like racism, patriotism, and feminism. Consequently, the study established that Jordanian Arabic is the most frequently-used language style, while the use of English and MSA as secondary language styles was considerably less popular. Additionally, code-switching was the most prevalent language practice. The study recommended educational policies to advocate bilingualism, while for social media, the strategies need to reflect linguistic characteristics to increase reach and engagement.

Beyond “Lügenpresse”: How Politicians Criticize and Delegitimize the Media in Germany

Media criticism is a crucial part of meta-journalistic discourse, ensuring that journalists adhere to their democratic functions, such as informing citizens in an honest and complete manner. However, the profession increasingly faces hostile, nonevidence-based attacks from politicians that attempt to strategically fuel distrust among citizens and delegitimize opposed viewpoints. Despite this reality, we lack a systematic overview of the boundaries between constructive feedback and weaponized attacks in media criticism. To address this gap, we inductively analyzed how media criticism is represented within the social media discourse of ten German politicians from all major parties. Using a grounded theory approach, we conducted a qualitative content analysis of a subset of their tweets from 2015, 2017, and 2022 that contain media criticism ( N = 545), mapping the types and severity of the criticism, the construction of opposing narratives, and the explicitness of references to facticity over opinions. We identified four themes within media criticism discourse, ranging from misinformation attributions to severe accusations of the intentional distortion of reality through the media. Politicians (strategically) employ a wide range of media criticism and inaccuracy claims beyond judgments of facticity with differing degrees of severity for the profession. Based on our findings, we propose a typology of media criticism from political elites that adds nuance to our understanding regarding the boundaries between supportive and disruptive criticism for journalism.

Examining the impact of incivility and intolerance on participation in social media discussions: An experimental investigation

This study investigates how incivility and intolerance impact participation in social media discussions by examining the emotions they evoke. An online experiment (N=1,192) was conducted where participants were exposed to civil, uncivil, and intolerant conditions through simulated Twitter conversations. The study aimed to determine which emotions — anger, anxiety, and disgust — are triggered under these conditions and how these emotions influence individuals’ willingness to participate in social media discussions. Results indicated that anger increased participation in uncivil conditions but had a reverse effect in intolerant conditions, reducing participation. Participants exposed to intolerant comments felt higher levels of disgust and anxiety, leading to a significant decrease in their willingness to participate. Conversely, civil discussions did not elicit strong negative emotions and thus did not significantly impact participation. These findings highlight the nuanced effects of different types of incivility on emotional responses and subsequent engagement in online discussions. The study underscores the importance of distinguishing between uncivil and intolerant discourse to understand their distinct impacts on social media participation.

Linguistic Accommodation and Identity in The Context of Social Media Discourse

Peaceful coexistence among members of the society is paramount. However, conflicts among the people living together are inevitable and therefore conflict resolution mechanisms must always be put in place. This paper focuses on how language can be used as a tool for resolving and maintaining peace among the individuals in the context of social media. Our society is organised in such a manner that people interact at various levels in the community and there are different forums and platforms that individuals use in the interaction process. During their interactions, language plays a very important role in ensuring that people live in harmony. Living harmoniously may be a concern for people that work together, live in the same neighbourhood, go to church together or live together. These people may interact on face-to-face basis and or use other media such as social media to reach out to one another. This paper narrows down to the kind of interactions that take place in the social media and how the interactants accommodate or cope with each other. The paper analyses texts extracted from Chuka University Students’ social media discourse (from the author’s PhD thesis) to reveal how students accommodate one another. This is an important aspect particularly nowadays when people have made social media an integral tool of communication and interaction. There are different platforms and genres of social media interaction platforms such as Facebook, twitter, Instagram and WhatsApp just to mention a few but this paper focuses on WhatsApp. The WhatsApp groups from which data for analysis were extracted, were those formed by Chuka University students in Tharaka Nithi County, Kenya. This paper is informed by Communication Accommodation Theory and Social Identity Theory. Since it was a qualitative investigation, a descriptive research design was used. Snowballing was used in the identification of the WhatsApp groups from which the texts were extracted purposively. The texts used in this paper were purposively collected on the basis of their content to show accommodation and identity among the social media users. The content analysis of the texts was done and results discussed. The findings revealed that students accommodate one another in their interactions and that they use language to mark their identity. The accommodation is achieved by using language in a manner that is peculiar to them. They for instance come up with their own jargons, phrases and forms of words that they use in their communication

Charting water sanitation concerns within vulnerable communities and international contexts on X

This study used a computational exploratory approach to examine X discourse on water sanitation challenges in the Black Belt region in the United States and compared it with larger international contexts. The research sought to uncover themes that impact salient environmental health issues and support future interventions. A two-part research question addressing the nature of water issues in a local and global context, resulted in a data set (n = 12,472 observations) analyzed using computational text analysis. Findings indicated that there was limited attention of issues discussed in the Black Belt region. On the other hand, global communication resulted in a greater discussion surrounding community-level problems and the very public nature of concerns, despite both issues being public-facing. Study findings contribute to the body of knowledge on social media discourse that develops as environmental health challenges develop into broader issues that emerge as global health risks.

Word Formation Processes in the Context of Social Media Discourse: A Case of Chuka University Students

The social media discourse is a hybrid of both written text and spoken discourse and therefore exhibits unique linguistic features that researchers can explore. This paper reveals the new dynamics of word formation processes in the social media discourse context, which is apparently a new genre. Morphological processes have in the past been analyzed in the context of spoken and written discourse. However, due to the evolution of the social media discourses that emanate from the communications that is mediated by divergent media platforms such as Facebook, WhatsApp, Instagrams and twitter, there is a need to shed light on how language is used in social media. This paper focuses on one aspect of such usage; how words are formed in the social media milieu. This paper therefore analyses the morphological processes drawing from Chuka University students’ social media discourse on WhatsApp platform. Students exhibits similar language usage due to the fact that they share a lot in common as a speech community. The paper therefore utilizes the social network theory to show how the interactants exploits the linguistic artifacts available at their social media network to interact meaningfully. Particularly, the focus is on the morphological processes that are evident in their interactions. The research design used is descriptive and the approach to data analysis is qualitative. The data used to inform this paper is drawn from the researcher’s thesis (2019). The findings revealed that students’ social media discourse results in the formation of new lexical items, use of symbols, Arabic numerals and letters to represent morphemes or words that are used in their day-to-day interactions. Similarly, morphological processes such as compounding, blending, clipping, borrowing, abbreviations and acronyms are common in the students’ social media discourse.

Social media discourses of Nigerian social affairs: a critical appraisal of YouTube vloggers’ panacea hypotheses for national recovery

ABSTRACT Different strata of Nigerian society including social media vlogs have been discussing the ills plaguing Nigeria. Such social ills include debt burden, flooding linked to Cameroon’s Lagdo Dam, food crisis resulting from border closure, and insecurity following government’s Visa on Arrival policy. Many suggestions have been offered as solutions. The study considers the perspectives of both Diaspora and local vloggers across gender and ages. Guided by Nancy Fraser’s subaltern counter-publics theoretical principle and Hollis Chenery’s theory of Structural Change, this paper evaluates YouTube discourses on Nigeria with a view to interpreting the vloggers’ hypotheses and the local factors militating against the vloggers’ viewpoints. Some of the panaceas recommended by the vloggers include no-debt pardoning, jettisoning project abandonment culture, voting on competence rather than ethnic affiliation, and emulation of the United States and Germany on ethnic unification. Other recommendations include oil theft blockage, reversal of the Visa on Arrival policy, self-determination, and inclusion of women in curbing food crisis. This study raises the consciousness of the Nigerian citizens on the country’s socio-political development roadmap enabled by the ubiquitous nature of social media. The study concludes that institutionalized corruption, leadership ineptitude, nepotism, and patriarchal hegemony hamper the actualization of the vloggers’ viewpoints.

The impact of social media discourse on financial performance of e-commerce companies listed on Borsa Istanbul

This research investigates how changes in public discourse on social media (particularly Twitter, now X) influence financial performance of companies listed on the e-commerce XTCRT index of Borsa Istanbul amid the COVID-19 pandemic. Utilising a unique 4-layer network structure, the study integrates daily closing prices, highest and lowest values, and trading volume data of these companies with Twitter discussions on six categories: culture, economy, health, politics, technology, world affairs. By using advanced computational methods such as multilayer network analysis, long short-term memory architecture, nonlinear autoregressive distributed lag analysis, we find a high responsiveness of the e-commerce index to social media content, particularly in discussions related to health, technology, world affairs. The study underscores that social media discussions significantly shape index composition, resulting in noticeable shifts in market dynamics, including fluctuations in stock prices, trading volumes, and market sentiment. Our study advocates for a more advanced approach to market analysis that incorporates the dynamics of online public discussions.

“Tweet of the town”: Synthesizing Local and Social Media Discourse on Book Bans

This project explores the intersection of local and online discourse around book bannings. I use the McMinn County School Board’s decision in 2022 to remove Art Spiegelman’s graphic memoir, Maus, as a case study for this discourse. Through a combination of interviews with McMinn County residents and data collected from Twitter, I argue that social media has altered local community discourse and responses to book bannings. Interviews with local residents asked them to discuss their experiences when Maus was removed by the school board and to reflect on how the local community responded amidst worldwide scrutiny once the event reached digital spaces via social media. Online discourse on Twitter involved collecting tweets mentioning the McMinn County Schools Twitter account along with tweets discussing Maus to understand the broader online response to the board’s decision. I use Danielle Allen’s discourse flow model as the theoretical framework for this project and in my initial findings, discourse around the Maus ban has traveled as described by Allen. In the age of social media, discourse frequently begins at the local level before traveling online and then back into local spaces. Ongoing data analysis has shown that locally, residents were concerned with not only the board’s decision, but also the perception of their community once news of the banning spread. This is supported by online discourse on Twitter, where initial analysis shows frequent characterization of the McMinn County community in a negative light based on the school board’s actions.

Unveiling public perceptions at the beginning of lockdown: an application of structural topic modeling and sentiment analysis in the UK and India

BackgroundThe appearance of the COVID-19 virus in December 2019, quickly escalated into a global crisis, prompting the World Health Organization to recommend regional lockdowns. While effective in curbing the virus’s spread, these measures have triggered intense debates on social media platforms, exposing widespread public anxiety and skepticism. The spread of fake news further fueled public unrest and negative emotions, potentially undermining the effectiveness of anti-COVID-19 policies. Exploring the narratives surrounding COVID-19 on social media immediately following the lockdown announcements presents an intriguing research avenue. The purpose of this study is to examine social media discourse to identify the topics discussed and, more importantly, to analyze differences in the focus and emotions expressed by the public in two countries (the UK and India). This is done with an analysis of a big corpus of tweets.MethodsThe datasets comprised of COVID-19-related tweets in English, published between March 29th and April 11th 2020 from residents in the UK and India. Methods employed in the analysis include identification of latent topics and themes, assessment of the popularity of tweets on topic distributions, examination of the overall sentiment, and investigation of sentiment in specific topics and themes.ResultsSafety measures, government responses and cooperative supports are common themes in the UK and India. Personal experiences and cooperations are top discussion for both countries. The impact on specific groups is given the least emphasis in the UK, whereas India places the least focus on discussions related to social media and news reports. Supports, discussion about the UK PM Boris Johnson and appreciation are strong topics among British popular tweets, whereas confirmed cases are discussed most among Indian popular tweets. Unpopular tweets in both countries pay the most attention to issues regarding lockdown. According to overall sentiment, positive attitudes are dominated in the UK whilst the sentiment is more neutral in India. Trust and anticipation are the most prevalent emotions in both countries. In particular, the British population felt positive about community support and volunteering, personal experiences, and government responses, while Indian people felt positive about cooperation, government responses, and coping strategies. Public health situations raise negative sentiment both in the UK and India.ConclusionsThe study emphasizes the role of cultural values in crisis communication and public health policy. Individualistic societies prioritize personal freedom, requiring a balance between individual liberty and public health measures. Collectivistic societies focus on community impact, suggesting policies that could utilize community networks for public health compliance. Social media shapes public discourse during pandemics, with popular and unpopular tweets reflecting and reshaping discussions. The presence of fake news may distort topics of high public interest, necessitating authenticity confirmation by official bloggers. Understanding public concerns and popular content on social media can help authorities tailor crisis communication to improve public engagement and health measure compliance.

Sentiment analysis of post-COVID-19 health information needs of autism spectrum disorder community: insights from social media discussions.

This study explores the health information needs of individuals with autism spectrum disorder (ASD) and their caregivers in the post-COVID-19 era by analyzing discussions from Reddit, a popular social media platform. Utilizing a mixed-method approach that integrates qualitative content analysis with quantitative sentiment analysis, we analyzed user-generated content from the "r/autism" subreddit to identify recurring themes and sentiments. The qualitative analysis uncovered key themes, including symptoms, diagnostic challenges, caregiver experiences, treatment options, and stigma, reflecting the diverse concerns within the ASD community. The quantitative sentiment analysis revealed a predominance of positive sentiment across discussions, although significant instances of neutral and negative sentiments were also present, indicating varied experiences and perspectives among community members. Among the machine learning models used for sentiment classification, the Bi-directional Long Short-Term Memory (Bi-LSTM) model achieved the highest performance, demonstrating a validation accuracy of 95.74%. The findings highlight the need for improved digital platforms and community resources to address the specific health information needs of the ASD community, particularly in enhancing access to reliable information and fostering supportive environments. These insights can guide future interventions and policies aimed at improving the well-being of autistic persons and their caregivers.

Transcreation on social media through translingual English

ABSTRACT Drawing on a creative and translingual approach to translation, the researcher examines online transcreation on social media. This study focuses on online transcreation by multilingual speakers who subtitle and translate video content through translingual English. This article first illustrates the relationships among translanguaging, translation, and transcreation. The article then provides metafunctional and multimodal discourse analyses of figurative, phatic, and pragmatic expressions and associated snapshots of manga-related visual images, anime-focused actions, and comic multimodal performances from subtitled videos on YouTube. Against the backdrop of transnational and transcultural flows (e.g. Japanese-mania and the Korean wave), the analyses reveal YouTubers’ transcreational strategies in a playful register. This study contributes to the theoretical and practical development of translingual transcreation in participatory social media discourse.

Health Use Cases of AI Chatbots: Identification and Analysis of ChatGPT Prompts in Social Media Discourses

The popularity of ChatGPT has raised questions surrounding AI’s potential for health use cases. Since the release of ChatGPT in 2022, social media users have shared their prompts and ChatGPT responses on different topics such as health. Despite editorials and opinion articles discussing the potential uses of ChatGPT, there is a lack of a systematic approach to identify and analyze the use cases of ChatGPT in health. This study establishes a framework for gathering and identifying tweets (i.e., posts on social media site “X”, formerly known as Twitter) that discuss health use cases of ChatGPT, integrating topic modeling with constructivist grounded theory (CGT) to organize these topics into common categories. Using this framework, nine topics were identified, which were further grouped into four categories: (1) Clinical Workflow, (2) Wellness, (3), Diseases, and (4) Gender Identity. The Clinical Workflow category was the most popular category, and included four topics: (1) Seeking Advice, (2) Clinical Documentation, (3) Medical Diagnosis, and (4) Medical Treatment. Among the identified topics, “Diet and Workout Plans” was the most popular topic. This research highlights the potential of social media to identify the health use cases and potential health applications of an AI-based chatbot such as ChatGPT. The identified topics and categories can be beneficial for researchers, professionals, companies, and policymakers working on health use cases of AI chatbots.

Disinformation and the Ghost of Margaret Sanger

This study sought to investigate the prominence of U.S. birth control pioneer and eugenicist Margaret Sanger in social media discourse through a critical disinformation studies lens. Using computational and qualitative analysis techniques, 60 months of public Facebook posts and Google search data were analyzed to explore the scope, reach, and engagement with messages that reference Sanger and examine how injustice frames utilizing Sanger’s historical ties to eugenics are being used today to misinform and disinform on abortion and other issues. Injustice frames featuring Sanger were deployed to portray abortion as a method for Black genocide; vilify feminism as racist, anti-woman, and anti-motherhood; and depict the Black Lives Matter social justice movement and cancel culture as hypocritical. This analysis also captured a moment in time when Sanger’s legacy was being reconsidered by Planned Parenthood, the organization she founded, indicating that a long-sought-after reckoning with the racist roots of the early birth control movement in the United States may be underway—with both predictable and unpredictable rippling effects in disinformative spaces.

The Resurgence of New Malay Nationalism on social media post-GE14

The 14th General Election has significantly changed Malaysia when Barisan Nasional suffered its first ever defeat since Independence. However, among the Malay majority, there was a growing sense of political anxiety and uneasiness as a result of the perceived loss of power, and to some extent, the erosion of national identity. In response, the nationalists and the Islamists have regrouped and reunited. This is manifested with the formal alliance of the two largest Malay-based parties, UMNO and PAS. Amidst the backdrop of this new political realignment, social media played an important role in setting the narrative, and mobilising the masses. Therefore, working from within this background, this paper analysed the discourse of the new Malay nationalism on social media by employing a social media tool, SeoTools, to analyse the Twitter data. The findings revealed a new insight into the dynamics of the Malay mind and motivation from the context of politics, religion, and economy. There was a significant correlation between popular sentiment and social media discourse, in that there was a renewed resurgence to reassert traditional values and identity. The failure to rein in the emotion, and the expectation, eventually cause the fall of Pakatan Harapan in 2020.

Book Theft as Social Deviance in Modern China: An Elegant Offense or the Intellectual Robin Hood

During China’s transition from pre-modern to modern society, book theft, as a form of social deviance, reflected the multifaceted cultural metaphors of books in modern Chinese social life. The shift from the notion that “common thieves do not steal books” to book theft as a representation of cultural power struggles exemplifies the media cultural transformation in modern Chinese society. Contemporary attitudes towards book theft reveal complex tensions between economic order, publishing supply and demand, social mentality, cultural capital, knowledge power, media discourse, and public opinion during this period of societal change. In this context, book theft can be seen as a dual phenomenon, embodying both a clever and sophisticated act that challenges dominant norms and values on one hand, and a form of rebellion that seeks to redistribute power and knowledge, akin to the legendary outlaw Robin Hood, on the other.

Stoltenberg, Daniela: The Spaces of Public Issues. How Social Media Discourses Shape Public Imaginations of Issue Spatiality.

Stoltenberg, Daniela: The Spaces of Public Issues. How Social Media Discourses Shape Public Imaginations of Issue Spatiality.

Balancing benefits and risks of exercise in pregnancy: a qualitative analysis of social media discussion

Exercise improves pregnancy outcomes, but few pregnant individuals meet physical activity guidelines. The main objective of this study was to explore the perception of exercise during pregnancy using posts and...

Beyond virtual boundaries: the intersection of the metaverse technologies, tourism, and lifelong learning in China’s digital discourse

In the evolving landscape of digital education, the metaverse emerges as a revolutionary platform, particularly within the realm of tourism, viewed through the lens of lifelong learning. This study delves into the integration of the metaverse in the tourism and education sectors in China, aiming to uncover the intricate dynamics of public perceptions and the educational potential of this digital innovation. This research utilizes semantic network and sentiment analysis of social media discussions on China’s Weibo platform to provide a detailed understanding of sentiments toward the metaverse’s impact on tourism education. Semantic Network Analysis explores the complex dialog surrounding the metaverse in the context of lifelong learning. The findings reveal a balanced mix of enthusiasm for the immersive educational opportunities afforded by the metaverse and concerns regarding data privacy, digital addiction, and ethical considerations. It is evident from this duality that a balanced approach is necessary when the metaverse is integrated into tourism and learning while being sensitive to technological opportunities and ethical challenges. The metaverse could be an immersive, interactive learning environment endorsed by modern educational theories, supporting active learning through experience. The metaverse will provide valuable assistance to tourism education, which will help enhance this field through the simulation of real tourism for students to learn, which will foster cultural understanding and meet the demands of a globalized tourism industry. It further recommends that policies and practices should be formulated to ensure equal access, respect for the privacy of every participant, and the ethical use of the technology. This study contributes to the analysis of the potentials and challenges of the metaverse in the tourism and learning industry. It highlights the metaverse as an ‘emerging tool for lifelong learning’ and offers insights into how educators, policymakers, and industry leaders, all aiming at the integration of digital innovations in education, should exploit the metaverse.

The Impact of Journalistic Cultures on Social Media Discourse: US Primary Debates in Cross-Lingual Online Spaces

This cross-lingual project examines how social media posts of Spanish- and English-language media impact incivility in user comments during the 2020 primary political debates in the United States. We analyzed Facebook posts of news organizations that hosted the debates and used a state-of-the-art machine-learning model to analyze the corresponding comments. Our findings reveal distinct journalistic cultures on the post-level: English-language media are significantly more likely to use interpretation while Spanish-language media employ more audience-engagement and factual reporting strategies. We argue that in order to understand incivility in social media discourse during political debates, we need to consider journalistic cultures: While interpretative reporting explains lower levels of incivility in the English-language discourse, factual reporting explains lower levels of incivility in the Spanish-language discourse. We suggest that we need to consider how features of news reporting (textual and visual) impact discourse quality directly but also indirectly via emotional arousal in comments.