What is it about computational communication science?

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.

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 lotte.schrijver@wur.nl for further insights, and stay tuned for the DOI link to her study, coming soon!

Tune in to the #aBitOfCCS Podcast as we explore state communication and public trust during the COVID-19 pandemic with Christian Schwaderer, a PhD candidate at the University of Innsbruck, Austria. Christian’s study, Navigating Trust: Comparative Insights into Crisis Communication Strategies and Public Perception, examines how government communication strategies on social media and in press conferences influenced public perception and trust in crisis management. In this conversation, hosted by Jana Bernhard-Harrer, we dive into Christian’s analysis of nearly 400 government press conferences across nine OECD countries, alongside real-time public reactions on social media. Using both manual coding and quantitative methods, his research reveals patterns in communication that shaped public trust and offers valuable insights for crisis response strategies. For further discussion, connect with Christian at Christian.Schwaderer@uibk.ac.at, and you can find his slides on a presentation of this study here: https://www.slideshare.net/secret/H7CADAky5sIVwK 

Credibility is a crucial concept in communication science and received severely increased attention, again, with CCS. That is, it serves everybody as a signpost to navigate the web whilst also being scrutinized by some via (AI-driven) signals that suggest trustworthiness. Cuihua (Cindy) Shen is Professor of Communication and Co-Director of the Computational Communication Research Lab at the Department of Communication at UC Davis. In this episode, she, Emese Domahidi (Professor at TU Ilmenau) and Mario Haim (Professor at LMU Munich) talk about the concept of credibility and its particular role with mis- and disinformation. Of course, we also talk AI and what credibility is worth when a machines can generate whatever we've learnt to be trustworthy. P.S.: We now also have a website for our podcast --> https://aboutccs.net/ P.P.S.: This is the last episode of this season. We're off to a (longer? ;-)) summer pause but look forward to being in touch soon!

Ethan Zuckerman, Associate Professor of Public Policy, Communication and Information at the U of Massachusetts Amherst, is our guest, and he is on a mission to fix platforms. Not because he thinks they are inherently bad, but because there are several things about platforms that research (not least CCS) tells us are flawed. Emese Domahidi (Professor at TU Ilmenau) and Mario Haim (Professor at LMU Munich) talk with Ethan about why social media seems to be broken, what possible ways to fix it might be, how different regions of the world are approaching this challenge, and whether suing Facebook might make a difference. P.S.: We now also have a website for our podcast --> https://aboutccs.net/

Join us in the newest episode of #aBitOfCCS Podcast featuring Dr. Mónika Simon, a Postdoctoral researcher at the UvA, unraveling Narratives of (Dis)Trust in the digital realm. In this episode, Dr. Simon discusses her research focused on tracing information flows in contemporary media, utilizing advanced computational methods and cross-platform analysis. Explore her paper "Linked in the dark: A network approach to understanding information flows within the Dutch Telegramsphere" co-authored with K. Welbers, A. C. Kroon, and D. Trilling. Access the paper at ⁠https://www.researchgate.net/publication/364452085_Linked_in_the_dark_A_network_approach_to_understanding_information_flows_within_the_Dutch_Telegramsphere For further inquiries or information, you can reach Dr. Mónika Simon atm.simon@uva.nl. Tune in to this episode for a captivating exploration of the intricate world of information flows, providing valuable insights into the digital age and the dynamics of trust and distrust in media.

Dive into the latest episode of #aBitOfCCS Podcast featuring Sean-Kelly Palicki, a PhD candidate at TU Munich, as he explores multilingual document sampling and the impact of keyword translation strategies on automated text analysis. In this engaging conversation with host Jana Bernhard, Sean discusses key findings from his study, "Selecting Relevant Documents for Multilingual Content Analysis," published in Computational Communication Research. Check out the full study at https://doi.org/10.5117/CCR2023.2.5.PALI. For further inquiries, reach out to Sean-Kelly at sean.palicki@tum.de. Don't miss this insightful episode on the nuances of document selection in computational communication research!

Everyone is talking about Artificial Intelligence (AI), so we want to bring some differentiation into the bigger picture. For this, Jean Burgess, Distinguished Professor of Digital Media in and founding director of the Digital Media Research Centre (DMRC) at Queensland University of Technology, is our guest. She has been focusing on social implications of digital media technologies, platforms, and cultures, as well as new and innovative digital methods for studying them, for quite some time and has recently become Associate Director of the national Australian Research Council Centre of Excellence for Automated Decision-Making and Society (ADMS). From that, she's perfect to discuss with us--Emese Domahidi (Professor at TU Ilmenau) and Mario Haim (Professor at LMU Munich)--about what AI really is and where the hype is coming from, what role different disciplines play and where methods come into play. P.S.: We now also have a website for our podcast --> https://aboutccs.net/ Links https://www.admscentre.org.au/ https://research.qut.edu.au/dmrc/

Step into the world of language model-based chatbots with our latest podcast episode! Join us for an in-depth exploration of the study titled "The Silence of the LLMs: Cross-Lingual Analysis of Political Bias and False Information Prevalence in ChatGPT, Google Bard, and Bing Chat." In this insightful episode, our host engages in a compelling interview with the researchers behind the study—Aleksandra Urman from the Department of Informatics at the University of Zurich (urman@ifi.uzh.ch) and Mykola Makhortykh from the Institute of Communication and Media Studies at the University of Bern (mykola.makhortykh@unibe.ch). Discover key findings from their groundbreaking research, offering a cross-lingual analysis of political bias and false information prevalence in large language model-based chatbots. Uncover the implications of their work on the trustworthiness of AI-driven chat systems. For further inquiries or to join the conversation, reach out to Aleksandra and Mykola via email. This episode provides a thought-provoking journey into the complexities of language models, political bias, and the prevalence of false information in the realm of contemporary chatbot technologies. Access the full study here: https://osf.io/q9v8f/download