What is it about computational communication science?

Flipping things upside-down in this episode, Emese Domahidi (TU Ilmenau) and Mario Haim (LMU Munich) discuss with Claudia Wagner (RWTH Aachen and GESIS) about whether and how computer science really needs the social sciences. Claudia's background as a trained computer scientist as well as her current role as Professor of Applied Computational Social Sciences allowed us to really dive into opposing expectations, clichés, hurdles, and especially the benefits of interdisciplinary work at the intersection between the computer and the social sciences. We also discuss the concepts of algorithmically infused societies as well as "up-ductive" feedback loops, to ultimately discuss best practices for the perfect interdisciplinary collaboration that is computational social science.  Reference Wagner, C., Strohmaier, M., Olteanu, A., Kıcıman, E., Contractor, N., & Eliassi-Rad, T. (2021). Measuring algorithmically infused societies. Nature, 595, 197-204. https://doi.org/10.1038/s41586-021-03666-1

In this episode Emese Domahidi (Assistant Professor at TU Ilmenau) and Mario Haim (Assistant Professor at the U of Leipzig) discuss with Juhi Kulshrestha (Assistant Professor at U Konstanz) what makes algorithms online a research object. We touch on topics like filter bubbles and echo chambers, biases, how to investigate algorithms, the role of platforms and companies, data sources and possible effects of algorithmic curation. Last but not least, we discuss how far this field of resesarch has come by now and which future directions might be fruitful. References Friedman, B., & Nissenbaum, H. (1996). Bias in computer systems. ACM Transactions on Information Systems (TOIS), 14(3), 330–347. Kulshrestha, J., Eslami, M., Messias, J., Zafar, M. B., Ghosh, S., Gummadi, K. P., & Karahalios, K. (2019). Search bias quantification: Investigating political bias in social media and web search. Information Retrieval Journal, 22(1), 188–227. Urman, A., Makhortykh, M., Ulloa, R., & Kulshrestha, J. (2021). Where the Earth is flat and 9/11 is an inside job: A comparative algorithm audit of conspiratorial information in web search results. arXiv preprint arXiv:2112.01278.

Together with Tetsuro Kobayashi (Associate Professor at City U of Hong Kong), Emese Domahidi (Assistant Professor at TU Ilmenau) and Mario Haim (Assistant Professor at the U of Leipzig) discuss the dilemma with social-media tech giants like Facebook or Tencent which undoubtedly have but are hesitant to share adequate data with independent research. We also discuss how varying types of data have changed with the rise of computational communication science. And we talk about possible ways to move forward in order to establish more independent data sources to conduct up-to-date social-scientific research with.  References Henrich, J. (2020). The WEIRDest people in the world: How the West became psychologically peculiar and particularly prosperous. Picador.

Together with Felicia Löcherbach (PhD candidate at VU Amsterdam), Emese Domahidi (Assistant Professor at TU Ilmenau) and Mario Haim (Assistant Professor at the U of Leipzig) discuss what research software is and why to code your own research software. Felicia gives unique insights into the topic using the example of a research software she developed from scratch. We also touch on topics like rewards and challenges, ethics, data security, systematic testing vs. quick and easy solutions and how to find support if you start your own research software project.   References Loecherbach, F., & Trilling, D. (2020). 3bij3 – Developing a framework for researching recommender systems and their effects. Computational Communication Research, 2(1), 53–79. https://doi.org/10.5117/CCR2020.1.003.LOEC https://github.com/FeLoe/3bij3

Emese Domahidi (Assistant Professor at TU Ilmenau) and Mario Haim (Assistant Professor at the U of Leipzig) interview Till Keyling (former Senior Data Scientist at ProSiebenSat.1 and now Team Lead Software Engineering Data Science at PAYBACK) on how to become a data scientist. After learning what data science is, we look at what communication scientists can bring to the table, what university is capable of equipping us with, and what it is that potential employers look for in future data scientists. Also, do not miss out on Till talking us through an application process. References Gamma, E., Helm, R., Johnson, R., & Vlissides, J. (1994). Design patterns: Elements of reusable object-oriented software. Addison-Wesley. Robinson, E., & Nolis, J. (2020). Build a career in data science. Manning. Martin, R.C. (2008). Clean code: A handbook of agile software craftsmanship. Prentice Hall. Martin, R.C. (2017). Clean architecture: A craftsman's guide to software structure and design. Prentice Hall. Links and Podcasts https://news.ycombinator.com/ https://towardsdatascience.com/ https://towardsdatascience.com/podcast/home

Today, Emese Domahidi (Assistant Professor at TU Ilmenau) and Mario Haim (Assistant Professor at the U of Leipzig) discuss together with Valerie Hase (Research and Teaching Assistant at the U of Zurich) ways, approaches, guidelines, and routes to get started with computational communication science (CCS). We talk learning materials, compare intrinsic and extrinsic motivation, provide ideas and suggestions on where and how to find help and companions, and we tell our very own stories of how we got started with CCS. Conferences, Divisions, & Working Groups http://ic2s2.org/ - https://twitter.com/IC2S2 https://www.icahdq.org/group/compmethds - https://twitter.com/ica_cm - Slack channel via https://twitter.com/fe_loe/status/1395020548019720193 https://www.dgpuk.de/de/methoden-der-publizistik-und-kommunikationswissenschaft.html - https://twitter.com/dgpuk_meth https://www.cssmethods.uzh.ch/en.html https://cssamsterdam.github.io/ https://tadapolisci.slack.com Journals https://computationalcommunication.org/ccr https://www.tandfonline.com/toc/hcms20/current References van Atteveldt, W., Trilling, D., & Arcila Calderon, C. (2021). Computational analysis of communication. Wiley Blackwell. https://cssbook.net/ Wickham, H., & Grolemund, G. (2017). R for Data Science: Import, tidy, transform, visualize, and model data. O'Reilly. Summer Schools https://github.com/chkla/css-schools https://essexsummerschool.com/ https://sicss.io/ https://wiki.digitalmethods.net/Dmi/DmiAbout Introductory Tutorials https://www.tidytextmining.com/ https://tutorials.quanteda.io/ https://content-analysis-with-r.com/ https://bookdown.org/joone/ComputationalMethods/ https://tm4ss.github.io/docs/ https://www.mzes.uni-mannheim.de/socialsciencedatalab/article/advancing-text-mining/ https://bookdown.org/ndphillips/YaRrr/ https://r4ds.had.co.nz/

In the second episode Emese Domahidi (Assistant Professor at TU Ilmenau) and Mario Haim (Assistant Professor at the U of Leipzig) discuss with Wouter van Atteveldt (Associate Professor at Vrije Universiteit Amsterdam) the role of communication science in the field. Main topics are the nature and role of data for the social sciences and challenges in collaborations with computer scientists. We touch on topics like open science, reproducibility and replicability for computational communication science and whether we need a cultural change to achieve these goals. Last but not least we talk about a new book Computational Analysis of Communication that Wouter co-edited with Damian Trilling and Carlos Arcila. References Lazer, D., Pentland, A. (Sandy), Adamic, L., Aral, S., Barabasi, A. L., Brewer, D., Christakis, N., Contractor, N., Fowler, J., Gutmann, M., Jebara, T., King, G., Macy, M., Roy, D., & Van Alstyne, M. (2009). Life in the network: The coming age of computational social science. Science (New York, N.Y.), 323(5915), 721–723. https://doi.org/10.1126/science.1167742 Roberts, M. E., Stewart, B. M., & Tingley, D. (2019). stm: An R Package for Structural Topic Models. Journal of Statistical Software, 91(2), 1–40. https://doi.org/10.18637/jss.v091.i02 van Atteveldt, W., Trilling, D., & Arcila, C. (in press). Computational Analysis of Communication. Wiley Blackwell. Book homepage: https://cssbook.net/

In this first-ever episode, Emese Domahidi (Assistant Professor at TU Ilmenau) and Mario Haim (Assistant Professor at the U of Leipzig) discuss the relevance of a social-scientific perspective in the computer-scientifically driven field of artificial intelligence. We briefly dig into Kate Crawford's recent book (https://www.katecrawford.net/) as well as the European Union's "Guidelines for Trustworthy AI." And we compare rather distinct understandings of relevance when it comes to a computational perspective within communication science. All of this accumulates in the introduction of our new podcast in which we will tackle the urgent questions of CCS.  References Crawford, K. (2021). Atlas of AI. Yale University Press. EU Ethics Guidelines for Trustworthy AI: https://digital-strategy.ec.europa.eu/en/library/ethics-guidelines-trustworthy-ai Fuchs, C., & Qiu, J.L. (2018). Ferments in the field: Introductory reflections on the past, present and future of communication studies. Journal of Communication, 68(2), 219-232. https://doi.org/10.1093/joc/jqy008 van Atteveldt, W., & Peng, T.-Q. (2018). When communication meets computation: Opportunities, challenges, and pitfalls in computational communication science. Communication Methods and Measures, 12(2–3), 81–92. https://doi.org/10.1080/19312458.2018.1458084

What is it about Computational Communication Science? As "big data" and "algorithms" affect our daily communication, lots of new research questions arise at the intersection between societies and technologies, asking for human wellbeing in times of permanent smartphone usage or the role of huge platforms for our news environment. The growing discipline of Computational Communication Science (CCS) takes on a combinatory perspective between social and computer science. In this podcast, Emese Domahidi (@MissEsi) and Mario Haim (@DrFollowMario) open this discussion for students and young scholars, one guest and one question at a time. Credits Artwork: Kristina Schneider (@kriesse) Sounddesign: Nico van Capelle Exciting background music in the beginning from musicfox.com