'Big Data'

The first session at the ACSPRI 2024 conference is on generative AI, and starts with Lachlan Watson. He is interested in the use of AI assistance to analyse public policy submissions, here in the context of Animal Welfare Victoria’s draft cat management strategy. Feedback could be in the form of written submissions, surveys, or both, and needed to be analysed using quantitative approaches given the substantial volume of submission.

The organisation chose Relevance AI as a tool for this – this is a low code AI solution not unlike ChatGPT, but data is hosted in a private environment and none …

From the AANZCA conference in Melbourne of the last few days I’ve moved on to the ACSPRI 2024 conference in Sydney for the rest of the week, which starts with a keynote by Maggie Walter, on methodologies for Indigenous statistics and quantitative research. Maggie is a Palawa woman from Tasmania. Data and population statistics have changed dramatically over the past decade or more; conventionally, Australian Indigenous people have been presented merely as average statistics that show what Maggie calls the Statistical Indigene: documenting prolonged disadvantage and inequality.

This is the case because these are the things we have data about …

The next session at the AANZCA 2024 conference starts with a paper by Terry Flew, Agata Stepnik, and Tim Koskie, who begin by noting the changing contours of Internet governance. There is increasing nation-state regulation in liberal democracies as well as authoritarian states, as well as renewed debate about the treatment of digital and social media platforms and a populist push towards greater regulation.

This regulatory turn has also been driven by significant shocks and scandals as well as growing regulatory activism, and is often directed at curbing the power of platforms, out of a general sense that governments should …

And the final speaker in this final AoIR 2024 conference session is the excellent Fabio Giglietto, whose focus is on coding Italian news data using Large Language Models. This worked with some 85,000 news articles shared on Facebook during the 2018 and 2022 Italian elections, and first classified such URLs as political or non-political; it then produced and clustered text embeddings for these articles, and used GPT-4-turbo to classify the dominant topics in these clusters.

This required considerable prompt crafting, especially also to ensure that prompts remained within the LLM’s token limits. Key challenges here included the choice of LLM …

The next speaker in this final AoIR 2024 conference session is the great Hendrik Meyer, whose interest is in detecting stances in climate change coverage. This focusses especially on climate change debates in German news media, focussing on climate protests, discussions about speed limits, and discussions about heating and heat pump regulations.

Here stances might be better understood as evaluations related to a given issue or policy, and Large Language Models can be useful tools in assessing this, but this also requires considerable prompt crafting in order to generate consistent results. Computational costs for doing so (especially with complex prompts) …

The next speaker in this session at the AoIR 2024 conference is my QUT colleague Tariq Choucair, whose focus is especially on the use of LLMs in stance detection in news content. A stance is a public act by a social actors, achieved dialogically through communication, which evaluates objects, positions the self and other subjects, and aligns with other subjects within a sociocultural field.

Here, the focus is broadly on stances towards issues, persons, groups, and organisations. There are some tools for doing so, but they mainly focus on English-language content, are designed for specific types of data, and tend …

The second speaker in this final session at the AoIR 2024 conference is Bruna Silveira de Oliveira, whose focus is on using LLMs to study content in the Brazilian manosphere. Extremist groups in this space seek legitimisation, and the question here is whether LLMs can be used productively to analyse their posts.

This analysis focusses on some 2,500 episodes of Brazilian masculinist podcasts across ten streaming platforms. It engaged in an assisted content analysis using OpenAI’s GPT-4 model, and explored whether this could identify detailed variables in the content. The podcast episodes were transcribed using automated tools, and 52 episodes …

The final (!) session at this wonderful AoIR 2024 conference is on content analysis, and starts with Ahrabhi Kathirgamalingam. Her interest is especially on questions of agreement and disagreement between content codings; the gold standard here has for a long time been intercoder reliability, but this tends to presume a single ground truth which may not exist in all coding contexts.

The concept of ‘constructs of marginalisation’ might be useful here: marginalised people are underrepresented; existing structural power defines who defines such constructs; they are historically and culturally shaped; and explicit as well as ambiguous and evasive language that discriminates …

I presented in and chaired the Saturday morning session at the AoIR 2024 conference, which was on polarisation in news publishing and engagement, so no liveblogging this time. However, here are the slides from the three presentations that our various teams and I were involved in.

We started with my QUT DMRC colleague Laura Vodden, who discussed our plans for manual and automated content coding of news content for indicators of polarisation, and especially highlighted the surprising difficulties in getting access to quality and comprehensive news content data:

I …