What is it about computational communication science?

• #aBitOfCCS on strategic political communication on twitter with Daniel Sandvej Eriksen hosted by Jana Bernhard-Harrer

  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= 

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• #aBitOfCCS on the Role of Software Tools in Computational Text Analysis with Marvin Stecker hosted by Jana Bernhard-Harrer

  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 - [email protected]

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• #aBitOfCCS on neural network for scaling party positions with Hung H.V. Nguyen hosted by Jana Bernhard-Harrer

  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 - [email protected]

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• #aBitOfCCS on ABM with Said Unger hosted by Jana Bernhard-Harrer

  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 [email protected].

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• #aBitOfCCS on Misinformation Detection with Lotte Schrijver hosted by Jana Bernhard-Harrer

  Tune in to the #aBitOfCCS Podcast as we discuss misinformation during the COVID-19 pandemic with Lotte Schrijver, a PhD candidate in Strategic Communication at Wageningen University and the Pandemic and Disaster Preparedness Center. In her study, "In Search of Truth: A Refined Approach to Collecting and Annotating Data for BERT-Based Misinformation Detection," Lotte explores the challenges of training machine learning models to detect nuanced misinformation. This episode, hosted by Jana Bernhard-Harrer, delves into the complexities of annotation choices and the limitations of models like BERT in capturing subtle forms of misinformation, such as conspiracy theories. Reach out to Lotte at [email protected] for further insights, and stay tuned for the DOI link to her study, coming soon!

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