What is it about computational communication science?

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.

Continuing with political language online, we seek to understand the relevance and divergence of news on the internet. Sounds trivial? Well, unfortunately, it isn't: What is "contemporary" news is decided upon by many rather than a few, it contains journalistically verified messages as well as mis- and disinformation and fake news. Jo(sephine) Lukito (Assistant Professor at the U of Texas at Austin’s School of Journalism and Media) guides us, Emese Domahidi (Professor at TU Ilmenau) and Mario Haim (Professor at LMU Munich), through the exciting and "hybrid" online news environment as well as through her own research investigating particularly the malicious political language within online public spheres. Of course, CCS plays a large role in that too, as Jo is a strong advocate of computational methods and especially of multi-platform research.

It is not very hard to find dispute, also harsh dispute, online. A phenomenon also called digital contention, this raises several questions such as why are controversies more pronounced on the web? Have people turned into a rude mob in recent years or does the web help the quarrelsome to become more present? Also, what does this mean for our research, the theories and methods we apply? On that, Emese Domahidi (Professor at TU Ilmenau) and Mario Haim (Professor at LMU Munich) talk with Christian Baden (Associate Professor at the Department of Communication and Journalism and the Smart Institute at the Hebrew U of Jerusalem) who is not only interested in the topic for his own research but who is also heading the oft-mentioned EU-funded OPINION network (https://www.opinion-network.eu/) that brings together scholars working to automatically detect and extract opinions from unstructued data.

Guest Natali Helberger, Distinguished Professor of Law & Digital Technology, discusses the challenges of regulating new technologies, including AI. They also explore upcoming EU regulations such as the Digital Services Act, Digital Markets Act, and AI Act. The podcast delves into the influence of AI and platforms on society's digital infrastructure, the regulation of large online platforms, and the importance of transparency. It also examines the categorization of AI systems into different risk levels and the potential impact of regulation on academic freedom.

In this episode, Emese Domahidi (Professor at TU Ilmenau) and Mario Haim (Professor at LMU Munich) talk to Ágnes Emőke Horvát (Assistant Professor in Communication and Computer Science at Northwestern University where she leads the Lab on Innovation, Networks, and Knowledge, LINK) about what gender biases are, their origins and how prevalent these systematic misrepresantions are. Moving to Computational Communication Science, we then discuss how gender biases (and inequalities, more generally) affect our research, our data, tools, measures, and models. And we tackle the big question how potential routes forward could look like.

Measuring racism in news media using computational methods, including dictionary-based approaches. Discussion on the advantages of using dictionaries in computational communication science, and the challenges of identifying terms and validating data sources.