Tune in to the #aBitOfCCS Podcast as we explore how to measure something as abstract and slippery as uncertainty in political speech. Ella MacLaughlin, a PhD candidate at Utrecht University, joins us to discuss her ongoing research on how politicians in the US, UK, Germany, and the Netherlands express uncertainty in public communication.

In this episode, we dive into the challenges of capturing uncertainty in political language, how it differs from other domains like biomedical science, and how we can build a dictionary for latent novel contracts.. Rather than focusing on results, we reflect on the conceptual and methodological puzzles that come with studying highly normative political language through computational tools.

Reach out to Ella at e.j.maclaughlin@uu.nl for more on her work, and check out the project website at radiunce.org!

A brief note from Ella: At 17:52, I mistakenly attributed a paper to ‘Walters’ instead of the correct author ‘Walker’. Apologies for the error.

In this episode, we are joined by Prof. Helle Sjøvaag, journalism researcher and founding member of the OPINION Network. She shares how the network came to life and why it’s vital for studying how opinions form and spread online. We explore how digital spaces — from social media to news sites — shape what we think and how we express it. Helle unpacks the hidden influence of technology, power, and money on online discourse. Tune in to hear why building supportive networks is crucial in navigating these turbulent spaces — and how collective research can make a real difference. Further information here: https://www.opinion-network.eu/about

In this episode of #aBitOfCCS, Jana Bernhard-Harrer sits down with Denise Roth, a PhD student at the Strategic Communication Group at Wageningen University & Research. Denise’s research focuses on how science is communicated by political elites and the implications for the relationship between science and society.

Her study, "In the Crossfire: Online Hostility Towards Public Figures Amid Politicized Science Communication" , investigates how large language models (LLMs) can be leveraged to annotate training data for a classifier capable of distinguishing hateful language from other types of online comments. Together, we explore the intersection of AI, social science, and combating online hostility in the context of politicized science communication.

Don’t miss this thought-provoking discussion on the challenges and opportunities in understanding and addressing hostility towards public figures in today’s digital age. If you have any questions, you can connect with Denise here: Denise Roth - Wageningen University & Research

In the first episode, Wendo King'ang'i and Christian Baden dive into the concept of opinionated communication — what it is, how it shows up in our daily lives, and why it matters. They also touch on the current state of research and what the future holds for this fascinating topic.

In this podcast we aim to introduce and discuss the OPINION COST Action CA21129. The network convenes early- and mid-career researchers from over 35 European countries, Israel, and the US, integrating cutting-edge expertise from different disciplines (notably, communication science, computational linguistics, IT) while networking the many, hitherto largely disconnected language communities of textual researchers. Further information here: https://www.opinion-network.eu/about

Join us on the #aBitOfCCS Podcast as we dive into political agenda-setting with Daniel Sandvej Eriksen, Post-Doc at the University of Aarhus, Department of Political Science.

In this episode, we discuss Daniel’s latest research, "Initiate and Elevate! How Political Parties Can Set an Agenda." His study introduces The Issue Initiation Model, which explains how political parties proactively shape discussions . . Using computational methods, Daniel analyzes over 5.5 million tweets and 750,000 news articles from the UK and Denmark (2015-2022) to uncover how parties and MPs strategically set the agenda.

Hosted by Jana Bernhard-Harrer, this episode explores the intersection of computational social science and political communication, revealing how digital traces help us understand political strategy.

Preprint: https://osf.io/preprints/osf/yajsh_v1?view_only=

In this special episode of #aBitOfCCS, Jana Bernhard-Harrer sits down with Marvin Stecker, a PhD student at the Computational Communication Science Lab at the University of Vienna. Marvin is part of the AUTHLIB project, which focuses on illiberal challenges to democracy.

Unlike our usual focus on specific computational methods, this episode explores a study Marvin conducted with colleagues from OPTED: "Tools of the Trade – When Are Software Tools Mentioned in Computational Text Analysis Research?" The study examines how software tools are reported in computational communication science research and what this means for transparency and replicability.

We discuss:

• Key findings from a review of 406 journal articles published between 2016 and 2020.

• Patterns of software tool reporting across disciplines and over time.

• How factors like methodological validation and tool accessibility influence tool mentions.

• Implications for transparency, replicability, and the future of computational text analysis in communication science.

This episode provides valuable insights into the role of software tools in shaping computational research practices and offers a critical look at how we can improve transparency in the field.

For more on Marvin’s work, connect with him at: Marvin Stecker - marvin.stecker@univie.ac.at

In this episode of #aBitOfCCS, Jana Bernhard-Harrer chats with Hung Nguyen, a research fellow at the German Institute for Adult Education – the Leibniz Centre for Lifelong Learning. Hung shares insights from his study, "A Sentiment-Based Approach to Measuring Multidimensional Party Positions with Transformer."

The study introduces ContextScale, a framework that uses AI to analyze party positions by separating political sentiments from rhetorical styles. Built on the XLM-RoBERTa model, ContextScale offers new ways to understand policy intentions and party dynamics across languages and domains. Hung also discusses the dataset released through his research, featuring party positions on 11 topics across 22 countries.

Join us as we explore the use of transformer models in political communication and the potential for reshaping how we analyze party positions at scale.

For more on Hung’s work, connect with him at: Hung Nguyen - hung.nguyen@die-bonn.de

In this episode of #aBitOfCCS, Jana Bernhard-Harrer interviews Said Unger from the University of Münster about his research on combating disinformation through prebunking interventions. Said’s study, "Immunize the Public against Disinformation Campaigns: Developing a Framework for Analyzing the Macrosocial Effects of Prebunking Interventions," explores how Agent-Based Modeling (ABM) can help identify key turning points for preventing the spread of disinformation at a societal level. Don’t miss this conversation on the challenges and innovations in combating disinformation at scale!

Additional Resources:

• Study Link: Immunize the Public against Disinformation Campaigns

• Learn ABM with Python: ABM Python Tutorial by Mariuzka

For further insights, you can reach out to Said Unger at said.unger@uni-muenster.de.