What is it about computational communication science?

Anke Stoll developed a dictionary to detect German incivility using manual and automated approaches. The podcast discusses the challenges and potentials of using dictionaries in computational communication science, including the advantages of cost-effectiveness and scalability, difficulties in keyword collection, and the potential of incorporating machine learning. They also explore the evaluation of dictionaries, the importance of training models on relevant data, and the challenges of building dictionaries, recommending freely accessible dictionaries and coding schemes.

Frederic R. Hopp, Emese Domahidi, and Mario Haim discuss morality's impact on daily life and social cohesion. They explore how morality is tied to media content and the challenges of measuring it. The podcast also delves into the connection between morality and the brain, the role of neural representations, and bridging political divides. Lastly, it touches on media literacy, the spread of morally framed messages on social media, and the concept of moral reframing.

Jana Bernhard, a researcher studying algorithmic topic modeling for political communication analysis, discusses her approach to topic modeling using algorithmic embeddings to analyze political communication in Austria. She explains the need for more sophisticated methods, the challenges involved, and the importance of human validation. The podcast also emphasizes the need for simpler and more transparent techniques in topic modeling.

CCS researcher Waqas Ejaz discusses using topic modeling to analyze news coverage on climate change in Pakistan. They explore the challenges of data access and deciding the number of topics. The podcast also delves into the pros and cons of computational methods and manual sampling, compares global media coverage, and highlights the challenges of climate journalism in Pakistan.

Fabienne Lind, Emese Domahidi, and Mario Haim discuss the English centrism in academia and how it affects computational communication science research. They explore challenges and propose solutions for global survey research, analyze text data in different languages, and discuss the impact of new data types like images and videos. They emphasize the importance of geographical diversity, interdisciplinary collaboration, and gaining new perspectives in computational communication science.

What is it about Computational Communication Science -- and about big societal problems? We -- Emese Domahidi (@⁠⁠MissEsi⁠⁠) and Mario Haim (@⁠⁠DrFollowMario⁠⁠) -- are back with season 2 and with two exciting changes: First, we do not address "big data" and "algorithms" up front anymore but discuss societal problem that have been addressed by computational communication sciene recently. For that, we talk to several awesome scholars from a broad variety of sub fields. Second, we start a sub series entitled #aBitOfCCS in which individual papers from CCS are discussed in great detail and directly with the authors. And the best thing is that (while we already have recorded some of these episodes) you can become an active part of it!

The podcast discusses the evolution and challenges of computational communication science, including career opportunities and the intersection with other disciplines. It explores collaborative research projects and efforts to establish infrastructure in the field. The concept of communication science as a post-discipline is explored, and plans for a special series and listener participation are discussed.

David Lazer, a leading scholar on misinformation and computational social science, discusses the challenges in measuring human behavior, the conflict between data ownership and accountability, the problem of misinformation on platforms, and the issues of consent and privacy in research on Twitter data.

Emese Domahidi, Mario Haim, and Jacob T. Fisher discuss the role of coding for communication scholars. Topics include teaching coding skills, collaborating with computer scientists, programming languages for communication scholars, and using coding knowledge in business. They also explore the challenges of programming at different career levels and the value of coding in various industries.

Annie Waldherr, current vice chair of the ICA's Computational Methods division, joins the hosts to discuss networking in computational communication science. They explore the importance of networking in CCS, strategies for building connections, and the value of in-person networking opportunities at conferences. The chapter also highlights the role of online platforms like social media in networking and the value of interdisciplinary collaboration.