What is it about computational communication science‪?‬ Emese Domahidi & Mario Haim

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

Explore the latest episode of #aBitOfCCS Podcast featuring Mar Castillo Campos, a research assistant at Loyola Andalucía University, as she delves into the use of computational methods, including GPT and CNNs, for automating media bias detection. In a conversation with host Jana Bernhard, Mar discusses the simplicity yet effectiveness of this method in uncovering biases by comparing media coverage from different sources on the same story.

Discover more in Mar's study titled "Natural Language Processing Methods Applied to the Study of Media Coverage" available at https://comunicacionymetodos.com/index.php/cym/article/view/171/123.

For additional information or inquiries, contact Mar at mcastillo@uloyola.es. Don't miss this episode for a concise exploration of how computational methods offer a unique perspective on media bias in the realm of communication research and journalism studies!

In this episode, we look at the question of how digital media affects the well-being of users - a question that researchers have been debating for a long time.

From a communication science perspective, there are many questions in this field of research and new approaches to solving them using computational methods. In this episode, we look in particular at the measurement of media use and the new opportunities presented by digital data and computational methods, as well as the associated challenges. Doug A. Parry (Senior Lecturer at Stellenbosch University) is one of the leading experts in this field and an expert in innovative data formats for measuring media use. He talks to Emese Domahidi (Professor at TU Ilmenau) and Mario Haim (Professor at LMU Munich) about the topic.

Parry, D.A., Davidson, B.I., Sewall, C.J.R. et al. (2021). A systematic review and meta-analysis of discrepancies between logged and self-reported digital media use. Nature Human Behaviour, 5, 1535–1547. https://doi.org/10.1038/s41562-021-01117-5

Tune in to #aBitOfCCS Podcast as we explore cross-cultural communication in a pandemic with Ofer Shinar, a research student and teaching assistant at Tel-Aviv University, currently at LMU Munich. Ofer shares insights from his study, "Semantic Network Analysis of Students' Confessions During a Global Pandemic: A Cross-National Study," delving into intercultural media usage and Semantic Network Analysis. Hosted by Jana Bernhard, this episode offers a brief yet insightful journey into the method of semantic network anlaysis. For further discussion or inquiries, connect with Ofer at ofershinar@mail.tau.ac.il. Find the study slides here (https://www.slideshare.net/ofershinar/semantic-network-analysis-of-student-confessions-during-a-global-pndemicpptx) for a deeper dive into this intriguing research!

Katya Ognyanova (Associate Professor at Rutgers U) is our guest and she is an expert on studying social networks. What's the societal problem with that, we hear you ask. Well, a lot of political knowledge and information and particularly mis- and disinformation spreading on the internet builds on social networking parameters such as strong and weak ties or partisanship among groups. Katya talks Emese (Professor at TU Ilmenau) and Mario (Professor at LMU Munich) through network essentials, the social aspects of (mis-)information, and the role of CCS in all of that.

In this episode we talk about platforms and their power. This includes the relevance of social media metrics to users, the gatekeeping function of platforms, and fragmentation trends. For these topics, our guest is the ideal expert to talk to: Subhayan Mukerjee (Assistant Professor at the National U of Singapore) is a computer scientist, mathematician and (computational) communication scholar. What's more, he also brings a global perspective on the use of news and the power of platforms, as Emese Domahidi (Professor at TU Ilmenau) and Mario Haim (Professor at LMU Munich) talk with him about the needs for adequate methodology and, maybe even more importantly, for adequate theory.