Twitter Discourse Research Articles

“ChatGPT says no”: agency, trust, and blame in Twitter discourses after the launch of ChatGPT

AbstractChatGPT, a chatbot using the GPT-n series large language model, has surged in popularity by providing conversation, assistance, and entertainment. This has raised questions about its agency and resulting implications on trust and blame, particularly when concerning its portrayal on social media platforms like Twitter. Understanding trust and blame is crucial for gauging public perception, reliance on, and adoption of AI-driven tools like ChatGPT. To explore ChatGPT’s perceived status as an algorithmic social actor and uncover implications for trust and blame through agency and transitivity, we examined 88,058 tweets about ChatGPT, published in a ‘hype period’ between November 2022 and March 2023, using Corpus Linguistics and Critical Discourse Analysis, underpinned by Social Actor Representation. Notably, ChatGPT was presented in tweets as a social actor on 87% of occasions, using personalisation and agency metaphor to emphasise its role in content creation, information dissemination, and influence. However, a dynamic presentation, oscillating between a creative social actor and an information source, reflected users’ uncertainty regarding its capabilities and, thus, blame attribution occurred. On 13% of occasions, ChatGPT was presented passively through backgrounding and exclusion. Here, the emphasis on ChatGPT’s role in informing and influencing underscores interactors’ reliance on it for information, bearing implications for information dissemination and trust in AI-generated content. Therefore, this study contributes to understanding the perceived social agency of decision-making algorithms and their implications on trust and blame, valuable to AI developers and policymakers and relevant in comprehending and dealing with power dynamics in today’s age of AI.

Changing Images? Italian Twitter Discourse on China and the United States during the First Wave of COVID-19

ABSTRACT Although public diplomacy and its influence on foreign public opinion have been central themes in recent research, the latter often lacks methodological diversity and does not consider how states create competing images. Our study offers a framework for understanding Italian public opinion using a triangulation approach that combines traditional public opinion surveys with advanced text analysis of social media content. We compare the representation of China and the United States in the Italian Twitter community during the first wave of the COVID-19 pandemic. Our analysis shows that Italians who perceived China as a viable alternative to Western governments in public opinion surveys did so because they distrusted Western leaders and institutions.

The Kuwaiti Government’s Twitter Discourse During the COVID-19 Pandemic: Toward a Crisis Communication Model Using SCCT and CERC

In an effort to de-Westernise crisis communication literature, this study explores the Kuwaiti government’s COVID-19 discourse over Twitter by using criteria from Crisis and Emergency Risk Communication model (CERC) and Situational Crisis Communication Theory (SCCT). The Kuwaiti government mostly used instructing strategies, complying with crisis communication principles. However, contrary to recommendations from literature, reputation strategies were prioritised over adjusting strategies, confirming the influence of politics during crises. The results also revealed that the public interacted with instructing and adjusting strategies more than reputation strategies demonstrating the public’s need for information rather than reputation. Regarding Twitter use, the results indicated that the government lacked the necessary skills to communicate proficiently over the platform. The implications of the findings are discussed in relation to theory development in crisis communication and governmental use of social media.

Toward Mainstreaming of Feminist (Counter)Publics? The Networked Structure of Feminist Activism on Twitter

This study investigates the roles of feminist actors in the Twitter discourse about sexualized violence that came up during the confirmation of Brett Kavanaugh as a U.S. Supreme Court justice in October 2018. We theorize the discourse from the perspective of feminist counterpublics because it helps in understanding the extant power relations in public debate that are also manifest in digital networks. In this empirical study, we reconstruct the Twitter network discourse about the judge’s confirmation and examine the role of feminist actors and their counterpublic characteristics. Our findings indicate that the discourse network was highly polarized, but feminist voices were well integrated within the (progressive) center. Although feminists acted in the role of challengers seeking the attention of established political actors and news media, they did not remain isolated. Instead, they positioned themselves in the center of the progressive network and therefore influenced the general public discourse.

The Pulse of Long COVID on Twitter: A Social Network Analysis.

Long coronavirus disease (COVID) is a complex and multifaceted health condition with a range of severe symptoms that can last for weeks or even months after the acute phase of the illness has passed. Employing social network analysis (SNA) can rapidly provide significant health information to communities related to long COVID. This study aimed to identify the key themes, most influential users, and overall sentiments in the Twitter discourse on long COVID. Data were collected from a Twitter search with the specific keywords "long COVID" from December 1, 2022, to February 22, 2023, using NodeXL Pro. Visualizations, including network graphs and key influencers, were created using Gephi, and sentiment analysis was conducted with Azure Machine. In total, 119,185 tweets from 94325 users were related to long COVID. Top influencers include medical professionals, researchers, journalists, and public figures, with news media platforms as primary information sources; the most common hashtag was #longCOVID, indicating that it is a significant issue of concern among the Twitter community. In the sentiment analysis, most tweets were negative. The study highlights the importance of critically evaluating information shared by influential users and seeking out multiple sources of information when making health-related decisions. In addition, it emphasizes the value of examining social media conversations to understand public discourse on long COVID and suggests that future researchers could explore the role of social media in shaping public perceptions and behaviors related to health issues. Strategies for enhancing scientific journal engagement and influence in online discussions are discussed as well.

A Critical Discourse Analysis on the #StopAsianHate movement: Using Topic Modeling through MDCOR to Identify the Most Salient Themes from the Perspective of Social Representations Theory

The Atlanta Spa shooting evoked the Stop Asian Hate movement in the US. This study examines what primary topics were covered in Twitter discourse in #StopAsianHate and which phases of collective symbolic coping emerged from the perspective of social representations theory. 21,474 tweets in #StopAsianHate on Twitter in the first weeks from May to August were analyzed by topic modeling using MDCOR. The results of this research showed that the phases of awareness and divergence emerged in the discourse, while the phases of convergence and normalization remained unidentified. The knowledge generated in this research may contribute to identifying the main topics that appeared in #StopAsianHate on Twitter, and it may also inform the supporters of the Stop Asian Hate movement about the following actions.

Framing vulnerability: An ecolinguistic analysis of gender and climate change discourse

This study examines how climate change organizations employ discourse strategies to highlight the vulnerability of women to climate change. It also explores how these strategies disrupt the conventional climate change narrative by integrating gender issues and emphasizing women's social and cultural experiences. The study utilizes the framework of ecolinguistics to examine narratives woven into the textual discourse. The research, based on 40 tweets from organizations such as the UN Environment Program and UN Women, offers insights into how these organizations utilize ecolinguistic techniques in communicating climate issues. The findings of the study revealed that gender intersections with other social identities determine vulnerabilities to environmental changes, as the research highlights the disproportionate impacts on women, especially those from marginalized backgrounds. This study contributes to the existing literature in terms of exploring the depiction of this issue in the Twitter discourse of international organizations.

How the experience of California wildfires shape Twitter climate change framings

Climate communication scientists search for effective message strategies to engage the ambivalent public in support of climate advocacy. The personal experience of wildfire is expected to render climate change impacts more concretely, pointing to a potential message strategy to engage the public. This study examined Twitter discourse related to climate change during the onset of 20 wildfires in California between the years 2017 and 2021. In this mixed method study, we analyzed tweets geographically and temporally proximal to the occurrence of wildfires to discover framings and examined how frequencies in climate framings changed before and after fires. Results identified three predominant climate framings: linking wildfire to climate change, suggesting climate actions, and attributing climate change to adversities besides wildfires. Mean tweet frequencies linking wildfire to climate change and attributing adversities increased significantly after the onset of fire. While suggesting climate action tweets also increased, the increase was not statistically significant. Temporal analysis of tweet frequencies for the three themes of tweets showed that discussion increased after the onset of a fire but persisted typically no more than 2 weeks. For fires that burned for longer periods of more than a month, external events triggered climate discussions. Our findings contribute to identifying how the personal experience of wildfire shapes Twitter discussion related to climate change, and how these framings change over time during wildfire events, leading to insights into critical time points after wildfire for implementing message strategies to increase public engagement on climate change impacts and policy.

‘I Tweet about Our #GreenEnergy’—Automated Classification of Social Identity and Opinion Mining of the Dutch Twitter Discourse on Green-Energy Technologies

Understanding the complexities of public opinion is crucial for a green-energy transition. This present study examines the sentiment of public opinion towards various energy technologies on Twitter during the Dutch 2021 general elections. A dataset comprising 186,822 tweets and profile descriptions was analyzed using two automated text classifiers to explore how individuals with different self-proclaimed identities perceive green-energy technologies. The analysis involved the application of the sentiment and social identity classifier models, followed by a frequency and co-occurrence analysis. The findings revealed a negative overall sentiment towards green-energy technologies in the Twitter discourse. It further showed that perceptions may differ depending on a technology’s development stage, with emerging technologies generally receiving more favorable views compared to established ones. Furthermore, it was found that, although there is a general trend of negative sentiment based on political identity, and positive sentiment based on occupational identity, this trend did not consistently apply to specific energy technologies. This discrepancy can likely be attributed to varying implementation effects and contextual situations associated with the technologies. The findings suggest that personalized communication strategies for specific social groups may be beneficial for understanding and addressing public opinions, needs, and concerns within the energy transition. The complexity of understanding public opinion in the context of green-energy highlights the need for a nuanced approach in future research.

Tweets don't vote - Twitter discourse from Wales and England during Brexit.

The Welsh vote for "leave" in the Brexit referendum surprised some academics and analysts due to its strong preference for Labor and its close financial ties to the EU. It also brought up a debate about apparent differences in Welsh and English attitudes towards race, ethnicity, and migration, with the former often claiming to have a more positive stance regarding the presence of ethnic minorities and foreign nationalities. This paper proposes to analyze discourse posted on Twitter during June 2016, specifically targeting Wales and England with the aim to offer insight into the perceptions and beliefs of Welsh and English individuals on the platform and if attitudes on race, ethnicity, and migration played a significant role. Counterfactuals are checked with posts from the first few weeks of the refugee crisis in Afghanistan in 2021, the war on Ukraine, and the announcement of the Rwanda policy. The current discussion of Welsh national identity includes its claims as a "nation of sanctuary" and that understands oppression and marginalization. Thus, Welsh perspectives on Brexit become an interesting viewpoint to comprehending ethnic minorities and foreigners as it creates a possible conflict between the institutional discourse, cultural views, and perceived economic needs. In this context, this paper takes the view that Twitter is an area where individuals post their thoughts uninhibited, and where we can conduct an aggregate analysis of that public sentiment.

Does Organizational Messaging Make a Difference? Investigating Themes and Language Style in Twitter Discourse and Engagement by Mental Health Organizations

The present study investigated the latent topics and language styles present in mental health organizational discourse on Twitter. The researchers sought to analyze identifying the prevalence of and language used in social support messaging in tweets about mental health care, the overarching topics regarding mental health care, and predicted that tweets with higher engagement will have increased frequency of words with positively valenced emotion and cognitive processing. A GSDMM was run to uncover latent themes that emerged in a data set of 326.9k tweets and 7.2 m words about organizational discussions of mental health. A generalized linear model using the Poisson distribution was used to assess the role of engagement, positive emotion, and cognitive processing. The study found support for both positive emotion and cognitive processing as statistically significant predictors of engagement. Directions for research include the development of health message strategies, policy needs, and online interventions.

Digital vaccination passport and administrative burden of COVID-19 official application based on Twitter(X) discourse: public interest vs democracy

Digital vaccination passport and administrative burden of COVID-19 official application based on Twitter(X) discourse: public interest vs democracy

A Twitter network and discourse analysis of the Rana Plaza collapse

Ten years after the collapse of the Rana Plaza textile factory in Dhaka, Bangladesh that killed over 1000 factory workers, the event has become a symbol for the desolate working conditions in fast fashion producer countries in the global south. We analyze the global Twitter discourse on this event over a three week window around the collapse date over the years 2013–2022 by a mixture of network-theoretic quantitative and discourse-theoretic qualitative methods. In particular, key communicators and the community structure of the discourse participants are identified using a multilayer network modeling approach and the interpretative patterns of the key communicator’s tweets of all years are analyzed using the sociology of knowledge approach to discourse. This combination of quantitative and qualitative methods reveals that the discourse is separated into three phases: reporting, reprocessing, and commemoration. These phases can be identified by the temporal evolution, network-structural properties, and the contentual analysis of the discourse. After the negotiation of the interpretative framework in the reprocessing phase, subsequent years are characterized by its commemorative repetition as well as resulting demands by different international actor groups despite highly fluctuating participants.

Social solidarity with Ukrainian and Syrian refugees in the twitter discourse. A comparison between 2015 and 2022

ABSTRACT Incoming refugees from Ukraine are currently encountering a wave of solidarity that is seen, according to some, in stark contrast to the solidarity experienced by earlier groups of refugees i.e. from Syria during the so-called ‘immigration crisis’ in 2015. We aim to inform this debate on solidarity bias by collecting and analyzing quantitative data on (anti-)solidarity statements posted on Twitter during both waves of refugee immigration. We assess how social solidarity towards refugees differed between 2015 and the current wave of refugees fleeing Ukraine. To this end, we collect and analyze a longitudinal dataset of refugee-related tweets selected via hashtags and covering the period between January 2015 and August 2022. We first annotate the tweets for (anti-)solidarity expressions towards refugees. On these annotations, we train a supervised machine learning model and use it to automatically label over 2.3 million tweets. We assess the automatically labeled data for how statements related to refugee (anti-)solidarity developed and differed for distinct groups of refugees. Our findings show that in relative terms, refugee solidarity was expressed more often in tweets during September 2015 compared to March 2022. However, we find some evidence of solidarity bias in March 2022.

Hockey White in Canada

While multiculturalism and hockey are two features that are often said to define Canadian identity, they do not often overlap. This paper explores the Twitter discourse surrounding Harnarayan Singh’s 2021 debut sports broadcasts on Hockey Night in Canada and Sportsnet. Singh is the first Sikh person to call play-by-play in English in a national broadcast. We analyse this against the backdrop of racist remnants of colonialism in hockey resulting in the current majority presence of white players and sportscasters. Viewers’ reactions to Singh’s broadcasts mostly demonstrate positive alignment with Singh and support for inclusivity in hockey, however we find a pattern of race-related ideological assumptions embodying the existing tensions between movements to increase diversity in hockey while acknowledging a historic culture of racism in the sport.

‘This app is evil forest true true’: metaphor-based metadiscursive evaluations of Twitter by Nigerians

Abstract Previous linguistic studies on Nigeria-based Twitter discourse have investigated radicalist, terrorist, campaign, and electioneering discourses. These previous studies focus on discourses produced on Twitter, and not metadiscursive reflections about the social media space itself, and the discursive practice of dragging, in the context of celebrity–newcomer socialization, drawing theoretical insights from metaphoric conceptualizations. This article examines metaphor-based metadiscursive evaluations of the microblogging space by Nigerians. The data for the study comprise tweets retrieved from the Twitter account of a Nigerian celebrity new to Twitter, and subjected to metaphor scenario analysis. It was found that the metaphoric concepts of EVIL FOREST, STREET AS CULTURE/HIGHWAY, and DRAG/TIGER GENERATOR provide frames for characterizing, and evaluating Twitter, and the practice of dragging, respectively. Such user-based metadiscursive metaphoric reflections about the digital space, and culture grant access to the conceptual, and ideological structures that underscore participation in cyberspace. This article has implications for understanding the conceptual and ideological structures that underscore participation on Twitter NG, and the (dis)affiliative stance towards online bullying inherent in the practice of dragging.

Oral rehydration solution (ORS) for fasting doping: Examining the Twitter data in Indonesia.

Oral rehydration solution (ORS) or oralit is a sugar and salt-based solution that restores electrolyte balance, counters dehydration and mitigates metabolic acidosis. In Indonesia, particularly during the month of Ramadan, the use of ORS as a form of fasting doping has become increasingly prevalent. This study aimed to analyze the patterns of communication, key influencers, and sentiment within the Twitter network in Indonesia regarding the use of ORS as fasting doping. From March 15 to March 26, 2023, Twitter data was collected using NodeXL software. The dataset was then analyzed using NodeXL and Gephi software to identify key influencers and patterns within the network. To assess attitudes towards the use of ORS as fasting doping expressed in tweets, sentiment analysis was conducted using Azure Machine. The dataset consisted of 13,746 tweets, from which the analysis revealed that Twitter discourse concerning the use of ORS as fasting doping demonstrated a diverse range of individuals. The top five users with the highest betweenness centrality scores were medical doctors, mention and confess (menfess) accounts, and personal accounts. The sentiment analysis of the collected tweets unveiled a relatively high negative sentiment toward the use of ORS for fasting purposes. Notably, the proportion of positive and neutral sentiments were comparable. Our data indicate that ORS use as fasting doping is controversial in Indonesia. Most tweets express concerns about misuse and negative consequences, indicating a need for guidance and regulation from public health authorities. Further research and guidelines are necessary to ensure the safe and appropriate use.

Virtual Linguistic Landscapes of Power and Ideology: A Critical Discourse Analysis of Twitter Posts on Kuwaiti Politics

This study examines Twitter's role as a platform for political discourse in Kuwait. The advent of Twitter as a dominant platform for political discourse deserves scholarly investigation, especially in linguistically diverse settings such as Kuwait. This research aims to fill a crucial gap in the existing literature on Virtual Linguistic Landscapes (VLL) by focusing on the interplay of language, power, and ideology within Kuwait's Twitter discourse on politics. Employing a mixed-method approach that integrates Critical Discourse Analysis with qualitative and quantitative data analysis, the study scrutinizes a sample of 116 posts concerning Kuwaiti politics. The results reveal that Arabic remains the predominant language, used primarily in discussions of local political issues and power structures. In contrast, English gains prominence in global and modernity-themed conversations. Additionally, bilingualism and code-switching emerge as significant practices, reflecting the complex ideological landscape of Kuwaiti politics. The study contributes to the academic discourse on VLLs by offering nuanced insights specific to Kuwait's sociopolitical and linguistic context. It also has broader policy implications for fostering an inclusive digital public sphere. Keywords: Sociolinguistics, Virtual linguistic landscape, Discourse analysis, Twitter, Kuwait, Ideology.

The new town square: Twitter discourses about balconies during the 2020 lockdown in Spain

The COVID-19 pandemic and lockdown in Spain during Spring 2020 resulted in a ban on most uses of public space, producing a social redefinition of not only public spaces, but also private spaces such as homes. This paper examines the discourses related to balconies that appeared at this time on Twitter (X), an intermediate microspace and hybrid between the public and private. The study uses data from tweets posted in Spain during the strictest phase of the lockdown (from 15 March to 1 May 2020). Based on a descriptive analytical approach – both quantitative and textual – the study applies text content analysis and natural language processing to identify and analyse the main topics of conversation related to the use of balconies. The study brought to light two primary and complementary results. Firstly, the balcony during the pandemic became a revitalized space in an exceptional situation, partially adapting to the most common practices characteristic of public space and thus reaffirming the importance of the existence of public spaces for citizen encounters. Secondly, the various uses of balconies received different types of attention and generated stronger or weaker interactions on social networks, demonstrating the complexity and diversity of relationships with public spaces.

A tale of two scandals: scale shift and the inefficacy of crisis communication management in Olympic scandals

IntroductionMega sporting events, such as the Olympic Games, provide niche sports with unique opportunities to attract public attention. However, scandals during these events can pose serious threats to these sports. In particular, if a sport scandal enables hostile stakeholders to achieve a scale shift, it becomes almost impossible for a niche sport organization to manage the scandal.MethodsThe article employs a comparative research design that examines the trajectory of two scandals related to the German Olympic team that differ with regard to the occurrence of a scale shift. The first scandal involved a racist slur made by a German official during a cycling event; the second scandal was a case of animal cruelty during the modern pentathlon's equestrian event. Research relies on a mix of qualitative document analyses and quantitative analyses of the German Twitter discourse on both scandals. The analyses focus on the vulnerability to scandals, the potential for contentious politics, the scandal triggering events, the crisis communication, the reception, and the outcomes of both scandals.Results and discussionOur results show the detrimental impact of a scale shift on niche sports. The animal cruelty scandal put the future of the modern pentathlon at the Olympics at risk and triggered far-reaching reforms. The case supports the idea that a scale shift becomes more likely if there exists an effective collective action frame. In contrast, the German sports organizations effectively ended the racist slur scandal by imposing a limited sanction on the offender.