By Emese Domahidi & Mario Haim
The podcast currently has 35 episodes available.
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 [email protected]. 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 [email protected]. 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 ([email protected]) and Mykola Makhortykh from the Institute of Communication and Media Studies at the University of Bern ([email protected]).
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 [email protected]. 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 [email protected]. 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.
The podcast currently has 35 episodes available.