Daniel Angus
Biographic Data
| ID | 110788 |
|---|---|
| NAME | Daniel Angus |
| GIVEN NAMES | Daniel |
| FAMILY NAME | Angus |
| SIGNATURE | ANGUS D |
| AFFILIATIONS | Queensland University of Technology |
| ORCID | 0000-0002-1412-5096 |
| VERIFIED | Yes |
| TOTAL WORKS | 42 |
| TOTAL CITATIONS | 65 |
| AUTHOR COUNT | 42 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2013 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 4 |
Searching for the truth? search engines and their AI affordances’ responses to conspiratorial search practices
Search engines are a common pathway to conspiracy theories, and producers of conspiratorial narratives actively encourage users to search for particular terms. Understanding how search engines respond to different information-seeking practices is therefore essential for explaining the dynamics of online conspiracy theories. Existing audits of search engines rarely account for systematic variation in query formulation arising from users’ differing…
Social Media in Elections: Evidence From the United States, Germany, and Australia
The year 2024 was marked by an unprecedented confluence of elections around the world, with more than 50% of the world’s population called upon to vote on the future of their governments; perhaps most important of these was the presidential election in the United States in November 2024, which saw Donald Trump returned to the Presidency – an outcome whose immense consequences are already being felt strongly around the world, mere months into the …
"Just Asking Questions": Doing Our Own Research on Conspiratorial Ideation by Generative AI Chatbots
Interactive chat systems that build on generative artificial intelligence frameworks - such as ChatGPT or Copilot - are increasingly embedded into search engines, Web browsers, operating systems, or available as standalone sites and apps. In a communication ecosystem where information disorder is a persistent threat (Wardle & Derakhshan, 2017), there is the potential for users to utilise chat systems to seek information about conspiracy theories …
Framing the future of search: A discourse analysis of Google’s AI Overviews
This study investigates how Google’s AI Overviews (AIOs) – a major shift in the search engine landscape – are discursively framed by three key actors: Google, tech journalists, and Search Engine Optimisation (SEO) marketers. Drawing on platform studies and discourse theory, we combine Leximancer concept mapping with Critical Discourse Analysis to examine how these stakeholders construct, legitimise, and contest the meaning of AIOs across a broad …
“Just Asking Questions”: Doing Our Own Research on Conspiratorial Ideation by Generative AI Chatbots
Interactive chat systems that build on artificial intelligence (AI) frameworks are increasingly ubiquitous and embedded into search engines, Web browsers, and operating systems, or as standalone websites and apps. Researcher efforts have sought to understand the limitations and potential for harm of chatbots powered by generative AI, which we contribute to here. Conducting a systematic review of seven AI-powered chat systems (ChatGPT 3.5 Turbo; C…
Unhealthy food advertising on social media: Policy lessons from the Australian Ad Observatory
The World Health Organization and public health experts are calling for urgent restrictions on the online marketing of unhealthy food. The harmful effects of exposure to advertising for ‘unhealthy foods’, including discretionary foods high in fat, salt or sugar, particularly for children, has prompted a proposed policy action in Australia to prohibit all online unhealthy food marketing. We used a novel data donation infrastructure, the Australian…
Analysing News Polarisation: From Production to Engagement and Beyond
Political polarisation – at the level of individual issues or broader ideologies, and expressed through differences of opinion on policies, divergent affective attachments, contrary interpretations of available information, or distinct patterns of interaction with other partisans – is necessarily always closely related to the information that individuals and groups engage with as they form and reinforce their own opinions about a given issue or t…
Multimodal narratives of climate denial: A novel, visual-first methodology for analysing conspiracy theory discourse on Instagram
climate denial discourse is represented on social media multimodally. • dominant visual signatures are isolated using an unsupervised machine learning technique. • the chemtrails conspiracy theory describes the most prevalent visual signature. • chemtrails conspiracy and climate denial discourses intertwine with other conspiratorial discourses through visuals, hashtags, and text. Problematic information about climate change in online spaces can i…
The discursive function of Meta’s Newsroom: How Meta frames the problem of problematic online content
This article examines the social technology company Meta’s public communication on problematic content, via their official ‘Meta Newsroom’, within the context of growing regulatory scrutiny. For nearly a decade, the Meta Newsroom has been a major outlet for Meta company announcements, and since 2016, the Newsroom has increasingly become a key source for company responses to concerns regarding mis/disinformation and other kinds of problematic cont…
Observing “tuned” advertising on digital platforms
The hyper-targeted advertising that emerged on digital platforms over the past two decades is now more productively understood as tuned advertising, a dynamic and unfolding process where ads are continuously algorithmically "optimised" to users in real time. Following Rieder and Hofmann (2020), we aim to develop a framework for the "conditions for the practice of observing" algorithmically-tuned digital advertising. We draw on our research across…
Finding the future in digitally mediated ruin: Nostalgiacores and the Algorithmic Culture of Digital Platforms
The #nostalgiacores are a series of interrelated hashtags on Instagram and TikTok where users recirculate content from the digital and consumer cultures of the 1990s and 2000s – childhood play centres, dead malls, long-gone toys, and superseded game consoles and phones. In this article, we explore these digital cultures using a critical platform studies approach that involves a combination of network analysis and close textual analysis augmented …
Computational Methods for Improving the Observability of Platform-Based Advertising
The advertising ecosystem has been progressively reshaped by computational advertising models facilitated and controlled by digital media platforms. Meta and Alphabet, two of the dominant players in this ecosystem, have contributed significantly to industry disintermediation via the design and market dominance of their advertising systems, which in turn are symbiotic with their own business models, and feed on large amounts of consumer data gener…
Topic Diversity in Social Media Campaigning: A Study of the 2022 Australian Federal Election
This study explores the diversity of topics in political campaign communication on social media during the 2022 Australian federal election. While political campaigns on social media are often associated with both persuasive and mobilising appeals, this research focuses on understanding the differences in persuasive content by comparing organic (non-targeted) and paid (targeted) political communication. Analysing the Australian context, which fol…
Why Am I Seeing This Ad? The affordances and limits of automated user-level explanation in Meta’s advertising system
Against the backdrop of calls for greater platform transparency, this exploratory article investigates Meta’s ‘Why Am I Seeing This Ad’ (WAIST) feature, which is positioned as a consumer-level explanation of Meta’s advertising model. Drawing on our own walkthroughs of Facebook and Instagram and data from the Australian Ad Observatory, we find the feature falls short in two ways. First, the explanations do not always align with how the system and …
Big Lies: Understanding the Role of Political Actors and Mainstream Journalists in the Spread of Disinformation
Much of the scholarly attention on disinformation has focussed on the role of social media, thus overlooking the political actors who themselves propagate disinformation and the mainstream news outlets that report on them. In this article we argue that disinformation has now become so widespread because outright lies are an effective way for political actors to attract and manage public attention. Political strategists have likewise worked out th…
Mandatory age verification for pornography access: Why it can't and won't 'save the children
Age verification is currently gaining traction among some western democracies as a means to restrict minors' access to online pornography. In this article we consider the ramifications of applying age estimation software to this task. We analyse a public dataset of 10,139 facial images processed through a commonly used high-performance convolutional neural network approach and find significant inconsistencies in classification performance. Notabl…
Pandemic Politics: The 2021 and 2022 German and Australian Federal Election Campaigns on Social Media
One of the effects of the continuing COVID-19 pandemic has been to further accelerate the incorporation of social media activities into political and electoral campaigning. Especially as a result of lockdowns and other restrictions to offline public life, overall social media use has increased in many countries; health concerns have severely curtailed conventional in-person political campaigning activities, from doorknocking to mass rallies (even…
Cottagecore, #Futurecore, #Sadcore: Using Critical Simulation to Explore the Interplay Between Machine Vision and Vernacular Instagram Aesthetics
This paper uses a novel combination of computational and qualitative methods called ‘critical simulation’ to explore the interplay between everyday image-making practices and the algorithmic architecture of Instagram. The paper aims to understand the capacity of machine vision systems to recognise and reproduce the diverse vernacular aesthetics and affects associated with particular scenes on Instagram - in this case, drawing on a case study of I…
Memes, Multimodalities, and Machines: Assembling Multimodal Patterns in Meme Classification Study
Memes are an important facet of current online communication on social media, with rich social, political, and cultural significance and power. This present work focuses on developing computational frameworks to support textual and visual content analysis of online memes, assisting the profiling of the unique contents and interrelationships of different meme characteristics. The framework focusses on decomposing the multimodal subcomponents of on…
Exploring Facebook’s “Why Am I Seeing This Ad” Feature: Meaningful Transparency or Further Obfuscation
For more than a decade, digital advertising has been the primary means of funding online content and services. The evolution of digital advertising towards algorithmically targeted advertising, believed to be highly personalized and tailored to the individual, has presented new challenges for public oversight. Whereas previously, public concern centred on the content of ads and their exposure to audiences, the rise of platform-based advertising m…
Addressing the accountability gap: Gambling advertising and social media platform responsibilities
This commentary reports on gambling advertisements served to Australians on Facebook in 2021-2022 that we discovered through a research project that uses novel data donation infrastructure to improve the observability of platform-based advertising. Preliminary findings show that advertisements for online casinos appear on social media and are served to people tagged as located in Australia despite laws that prohibit both the operation and adverti…
Computational Communication Methods for Examining Problematic News-Sharing Practices on Facebook at Scale
Social media, in general, and Facebook in particular, have been clearly identified as important platforms for the dissemination of mis- and disinformation and related problematic content. However, the patterns and processes of such dissemination are still not sufficiently understood. We detail a novel computational methodology that focusses on the identification of high-profile vectors of 'fake news' and other problematic information in public Fa…
Connected and consuming: Applying a deep learning algorithm to quantify alcoholic beverage prevalence in user-generated instagram images
Determining the prevalence of alcohol-related content on social media is important to guide education initiatives and interventions in this space. We aimed to assess the performance of the pre-developed alcoholic beverage identification deep learning algorithm (ABDILA) to automatically quantify alcoholic beverage prevalence in user-generated Instagram images. 6,121 images were gathered from Instagram using ‘Splendour in the Grass’ related hashtag…
Tuning machines: An approach to exploring how Instagram’s machine vision operates on and through digital media’s participatory visual cultures
The work of training machine vision systems is diffused into the participatory cultures of social media. As we use social media platforms to express ourselves we assemble databases and train algorithms; and these algorithms in turn shape our everyday cultural practices. In this article, we describe a machine vision system that we built to undertake an unsupervised classification of 13,000 images posted to Instagram from Splendour in the Grass, a …
Language and Social Psychology Approaches to Race, Racism, and Social Justice: Analyzing the Past and Revealing Ways Forward
Issues of race, racism, and social justice are under-studied topics in this journal. This Prologue, and our Special Issue (S.I.) more broadly, highlights ways that language and social psychology (LSP) approaches can further our understanding of race, racism, and social justice, while suggesting more inclusive directions for their theoretical development. Acknowledging the inspiration from the Black Lives Matter (BLM) movement, we begin by discuss…
Making sense of big text: A visual-first approach for analysing text data using Leximancer and Discursis
This article reports on Leximancer and Discursis, two visual text analytic software tools developed at the University of Queensland. Both analyse spatial and temporal relationships in text data, but in complementary ways: Leximancer focuses on thematic analysis, while Discursis focuses on sequential analysis. Our report explains how they work, how to work with them and how visual concepts are relevant to all stages of their use in analytic decisi…
Algorithmic brand culture: Participatory labour, machine learning and branding on social media
Social media platforms like Facebook and Instagram have transformed how brands operate as cultural processes. Over the past decade, these platforms have engineered an algorithmic brand culture that combines the participatory affordances and data-processing power of digital media. In the brand culture of social media, the creative narration of cultural experience doubles as data that trains platform algorithms. We develop an account of the algorit…
Visual Mis/disinformation in Journalism and Public Communications: Current Verification Practices, Challenges, and Future Opportunities
Social media platforms and news organisations alike are struggling with identifying and combating visual mis/disinformation presented to their audiences. Such processes are complicated due to the enormous number of media items being produced, how quickly media items spread, and the often-subtle or sometimes invisible-to-the-naked-eye nature of deceptive edits. Despite knowing little about the provenance and veracity of the visual content they enc…
IStandWithDan versus #DictatorDan: The polarised dynamics of Twitter discussions about Victoria’s Covid-19 restrictions
In this article, we examine two interrelated hashtag campaigns that formed in response to the Victorian State Government’s handling of Australia’s most significant COVID-19 second wave of mid-to-late 2020. Through a mixed-methods approach that includes descriptive statistical analysis, qualitative content analysis, network analysis, computational sentiment analysis and social bot detection, we reveal how a small number of hyper-partisan pro- and …
Mandatory age verification for pornography access: Why it can't and won't 'save the children
Age verification is currently gaining traction among some western democracies as a means to restrict minors' access to online pornography. In this article we consider the ramifications of applying age estimation software to this task. We analyse a public dataset of 10,139 facial images processed through a commonly used high-performance convolutional neural network approach and find significant inconsistencies in classification performance. Notabl…
Twitter Campaigning Strategies in Australian Federal Elections 2013-2019
This special issue of Social Media + Society develops a cross-national, longitudinal perspective on the use of social media in election campaigns. Australia, where leading social media platforms such as Facebook and Twitter were adopted early and widely by the general population, and where federal election cycles are unusually short (often less than 3 years), provides a particularly suitable environment for observing the evolution of social media…
Ripples of mediatization: Social media and the exposure of the pool interview
Visualising conversations between care home staff and residents with dementia
People with dementia living in residential care often face the dual disadvantage of increasing difficulty with communication and reduced opportunities for conversation. Social interaction is central to wellbeing of residents with dementia, so it is important that care staff have the skills to engage in conversation with them. We studied conversations in 20 care staff–resident dyads, to examine conversation structure and content, patterns of engag…
Topic Diversity in Social Media Campaigning: A Study of the 2022 Australian Federal Election
This study explores the diversity of topics in political campaign communication on social media during the 2022 Australian federal election. While political campaigns on social media are often associated with both persuasive and mobilising appeals, this research focuses on understanding the differences in persuasive content by comparing organic (non-targeted) and paid (targeted) political communication. Analysing the Australian context, which fol…
Computational Communication Methods for Examining Problematic News-Sharing Practices on Facebook at Scale
Social media, in general, and Facebook in particular, have been clearly identified as important platforms for the dissemination of mis- and disinformation and related problematic content. However, the patterns and processes of such dissemination are still not sufficiently understood. We detail a novel computational methodology that focusses on the identification of high-profile vectors of 'fake news' and other problematic information in public Fa…
Online self-expression and experimentation as 'reflectivism: Using text analytics to examine the participatory forum Hello Sunday Morning
Hello Sunday Morning is an online health promotion organisation that began in 2009. Hello Sunday Morning asks participants to stop consuming alcohol for a period of time, set a goal and document their progress on a personal blog. Hello Sunday Morning is a unique health intervention for three interrelated reasons: (1) it was generated outside a clinical setting, (2) it uses new media technologies to create structured forms of participation in an i…
Making sense of big text: A visual-first approach for analysing text data using Leximancer and Discursis
This article reports on Leximancer and Discursis, two visual text analytic software tools developed at the University of Queensland. Both analyse spatial and temporal relationships in text data, but in complementary ways: Leximancer focuses on thematic analysis, while Discursis focuses on sequential analysis. Our report explains how they work, how to work with them and how visual concepts are relevant to all stages of their use in analytic decisi…
Communication in open disclosure conversations about adverse events in hospitals
Using visual text analytics to examine broadcast interviewing
Ripples of mediatization: Social media and the exposure of the pool interview
Visualising conversations between care home staff and residents with dementia
People with dementia living in residential care often face the dual disadvantage of increasing difficulty with communication and reduced opportunities for conversation. Social interaction is central to wellbeing of residents with dementia, so it is important that care staff have the skills to engage in conversation with them. We studied conversations in 20 care staff–resident dyads, to examine conversation structure and content, patterns of engag…
Theme Detection in Social Media
Visual text analytics is an emerging field that blends and extends upon information visualisation and computational linguistics. This chapter introduces a range of visual text analytic methods which are suitable for analysing thematic trends in text-based social media data. The chapter introduces the Discursis (Angus, Smith, & Wiles, 2012a; Angus, Smith, & Wiles, 2012b) and Leximancer (Smith, 2000; Smith & Humphreys, 2006) technologies, and expla…
Online self-expression and experimentation as 'reflectivism: Using text analytics to examine the participatory forum Hello Sunday Morning
Hello Sunday Morning is an online health promotion organisation that began in 2009. Hello Sunday Morning asks participants to stop consuming alcohol for a period of time, set a goal and document their progress on a personal blog. Hello Sunday Morning is a unique health intervention for three interrelated reasons: (1) it was generated outside a clinical setting, (2) it uses new media technologies to create structured forms of participation in an i…
Algorithmic brand culture: Participatory labour, machine learning and branding on social media
Social media platforms like Facebook and Instagram have transformed how brands operate as cultural processes. Over the past decade, these platforms have engineered an algorithmic brand culture that combines the participatory affordances and data-processing power of digital media. In the brand culture of social media, the creative narration of cultural experience doubles as data that trains platform algorithms. We develop an account of the algorit…
Microphone pokes as prank or political action: Challenges to politicians’ visibility in the age of web TV
The production of political talk is changing in response to ongoing changes in the overall media ecology. The rise of web TV challenges the previously dominant mediated politics of traditional broadcasting. In this paper we examine the practices of the mediatization of politics in the web TV environment via a humorous encounter between a self-declared “prankster” posing as a web TV broadcaster, and several Swedish politicians. The discussion refl…
Investigating Bots and Coordinated Influence Campaigns in Twitter Discussions of the 2019-20 Iran Protests
Twitter has been a vital platform for organizing, coordinating, and amplifying voices during protests, especially in non-democratic countries. Although it is a globally used platform for protest movements, many studies focus on English-speaking and democratic countries. We overcome this research gap by investigating Persian, English, and Arabic tweets during the 2019-2020 protests in Iran. In this work-in-progress paper, we collected approximatel…
Visual Mis/disinformation in Journalism and Public Communications: Current Verification Practices, Challenges, and Future Opportunities
Social media platforms and news organisations alike are struggling with identifying and combating visual mis/disinformation presented to their audiences. Such processes are complicated due to the enormous number of media items being produced, how quickly media items spread, and the often-subtle or sometimes invisible-to-the-naked-eye nature of deceptive edits. Despite knowing little about the provenance and veracity of the visual content they enc…
Managing problematic visual media in natural hazard emergencies
In natural hazard emergencies, visual media (images, videos) document and convey the possible risk, impact, and severity of the hazard. Issues arise when the visuals being circulated, at scale and speed, are manipulated, fake, or are from an unrelated event or location. These problematic visuals can impact how communities interpret the risk of an emergency. Further, when visual media present information (i.e. a cue) in conflict with what an emerg…
‘Fake News’ and Other Problematic Information: Studying Dissemination and Discourse Patterns
Encompassed by the disputed term ‘fake news’, a variety of overtly or covertly biased, skewed, or falsified reports claiming to present factual information are now seen to constitute a critical challenge to the effective dissemination of news and information across established and emerging democratic societies. Such content – variously also classifiable as propaganda, selective reporting, conspiracy theory, inadvertent misinformation, and deliber…
Australia’s Big Gamble: The News Media Bargaining Code and the Responses From Google and Facebook
Responding rapidly to extraordinary developments in early 2021, this panel examines the background, development, implementation, and consequences of the latest Australian regulatory intervention in the engagement between content platforms and domestic media organisations: the News Media Bargaining Code (NMBC). The Australian federal government envisioned the NMBC as “a mandatory code of conduct to address bargaining power imbalances between Austr…
Prologue: History, Themes, Analysis, and Rationale
In this Special Issue, we commemorate 40 years of publishing research in the Journal of Language & Social Psychology (JLSP). We first provide a brief glimpse of the history of the field of language and social psychology and the emergence of JLSP within it. This is then developed further by exploring the themes—and the relationships between them—arising over the four decades of the journal, by means of a Leximancer analysis of the titles and abstr…
IStandWithDan versus #DictatorDan: The polarised dynamics of Twitter discussions about Victoria’s Covid-19 restrictions
In this article, we examine two interrelated hashtag campaigns that formed in response to the Victorian State Government’s handling of Australia’s most significant COVID-19 second wave of mid-to-late 2020. Through a mixed-methods approach that includes descriptive statistical analysis, qualitative content analysis, network analysis, computational sentiment analysis and social bot detection, we reveal how a small number of hyper-partisan pro- and …
Twitter Campaigning Strategies in Australian Federal Elections 2013-2019
This special issue of Social Media + Society develops a cross-national, longitudinal perspective on the use of social media in election campaigns. Australia, where leading social media platforms such as Facebook and Twitter were adopted early and widely by the general population, and where federal election cycles are unusually short (often less than 3 years), provides a particularly suitable environment for observing the evolution of social media…
Connected and consuming: Applying a deep learning algorithm to quantify alcoholic beverage prevalence in user-generated instagram images
Determining the prevalence of alcohol-related content on social media is important to guide education initiatives and interventions in this space. We aimed to assess the performance of the pre-developed alcoholic beverage identification deep learning algorithm (ABDILA) to automatically quantify alcoholic beverage prevalence in user-generated Instagram images. 6,121 images were gathered from Instagram using ‘Splendour in the Grass’ related hashtag…
Tuning machines: An approach to exploring how Instagram’s machine vision operates on and through digital media’s participatory visual cultures
The work of training machine vision systems is diffused into the participatory cultures of social media. As we use social media platforms to express ourselves we assemble databases and train algorithms; and these algorithms in turn shape our everyday cultural practices. In this article, we describe a machine vision system that we built to undertake an unsupervised classification of 13,000 images posted to Instagram from Splendour in the Grass, a …
Language and Social Psychology Approaches to Race, Racism, and Social Justice: Analyzing the Past and Revealing Ways Forward
Issues of race, racism, and social justice are under-studied topics in this journal. This Prologue, and our Special Issue (S.I.) more broadly, highlights ways that language and social psychology (LSP) approaches can further our understanding of race, racism, and social justice, while suggesting more inclusive directions for their theoretical development. Acknowledging the inspiration from the Black Lives Matter (BLM) movement, we begin by discuss…
Pandemic Politics: The 2021 and 2022 German and Australian Federal Election Campaigns on Social Media
One of the effects of the continuing COVID-19 pandemic has been to further accelerate the incorporation of social media activities into political and electoral campaigning. Especially as a result of lockdowns and other restrictions to offline public life, overall social media use has increased in many countries; health concerns have severely curtailed conventional in-person political campaigning activities, from doorknocking to mass rallies (even…
Cottagecore, #Futurecore, #Sadcore: Using Critical Simulation to Explore the Interplay Between Machine Vision and Vernacular Instagram Aesthetics
This paper uses a novel combination of computational and qualitative methods called ‘critical simulation’ to explore the interplay between everyday image-making practices and the algorithmic architecture of Instagram. The paper aims to understand the capacity of machine vision systems to recognise and reproduce the diverse vernacular aesthetics and affects associated with particular scenes on Instagram - in this case, drawing on a case study of I…
Memes, Multimodalities, and Machines: Assembling Multimodal Patterns in Meme Classification Study
Memes are an important facet of current online communication on social media, with rich social, political, and cultural significance and power. This present work focuses on developing computational frameworks to support textual and visual content analysis of online memes, assisting the profiling of the unique contents and interrelationships of different meme characteristics. The framework focusses on decomposing the multimodal subcomponents of on…
Exploring Facebook’s “Why Am I Seeing This Ad” Feature: Meaningful Transparency or Further Obfuscation
For more than a decade, digital advertising has been the primary means of funding online content and services. The evolution of digital advertising towards algorithmically targeted advertising, believed to be highly personalized and tailored to the individual, has presented new challenges for public oversight. Whereas previously, public concern centred on the content of ads and their exposure to audiences, the rise of platform-based advertising m…
Addressing the accountability gap: Gambling advertising and social media platform responsibilities
This commentary reports on gambling advertisements served to Australians on Facebook in 2021-2022 that we discovered through a research project that uses novel data donation infrastructure to improve the observability of platform-based advertising. Preliminary findings show that advertisements for online casinos appear on social media and are served to people tagged as located in Australia despite laws that prohibit both the operation and adverti…
Computer Science (27 works) · Sociology (22 works) · Political science (20 works) · Social media (18 works) · Law (15 works) · Politics (13 works) · Social Media and Politics (13 works) · Public relations (12 works) · Business (11 works) · Misinformation and Its Impacts (11 works)