Data Analysis
Researching complex social and computational systems
Why are misinformation and conspiracy theories spreading at an unprecedented rate? What can citizens do to combat hate online? And how can we design social media platforms in such a way that they are conducive to civic discourse? These are questions that we want to answer in our research group. In the past, we have looked at what measures can most effectively prevent coronavirus outbreaks in schools, how resilient the Austrian healthcare system is to disruption, and how a changing understanding of "honesty" can explain why politicians in the US are increasingly spreading misinformation.
In our research, we rely on computational approaches: we use machine learning to identify patterns in large amounts of data, statistical models help us to establish correlations between observations, and computer simulations allow us to run through various scenarios and make policy recommendations. To do this, we often use huge data sets of "digital traces", i.e. data such as posts or reactions on social media platforms that people leave behind when they use the internet.
In order to answer the important social questions of our time at the interface between society and technology, researchers from many different scientific disciplines must come together. That is why we are an interdisciplinary team with expertise ranging from computer science, sociology and psychology to physics. We welcome people with a technical background who are interested in social issues as well as students and researchers from the humanities and social sciences who are enthusiastic about computational methods!
Univ.-Prof. Dr. Jana Lasser
Head of Data Analysis
E-Mail: jana.lasser(at)uni-graz.at
Telefon: +43 316 380 - 1633
Website: https://www.janalasser.at/
ORCID iD: https://orcid.org/0000-0002-4274-4580
Github: https://github.com/JanaLasser/
Google Scholar: https://scholar.google.de/citations?user=vVrhda0AAAAJ&hl=en&oi=ao
Elisabeth Höldrich, BSc MSc
Doctoral Researcher
Elisabeth Höldrich is a PhD candidate at the IDea_Lab since 2024, researching the rise and spread of conspiracy theories in online environments within the Orientation in Conspiration project (ORION). Through the application of Natural Language Processing and topic modeling Elisabeth hopes to measure different characteristics of individual conspiracy theories and identify which of these characteristics contribute most to the popularity of a conspiracy theory.
With a bachelor’s and master’s degree in physics, focusing on theoretical and computational physics, from the Technical University of Graz, Elisabeth conducted her Master's thesis in the broad field of computational social science. She investigated political speech of US politicians before the Midterm elections of 2022 using statistical models and time series analysis to model their discourse in online environments, with a focus on analyzing how political speech influences public voting behavior. With a strong interest for social issues, political polarization and democracy, Elisabeth continues to apply computational and mathematical modeling, data analysis and network science to understand real-world social and political phenomena.
E-Mail: elisabeth.hoeldrich(at)uni-graz.at
Telefon: +43 316 380 - 1632
Dr. Joao Pinheiro Neto
Postdoctoral Researcher
I'm a physicist with experience in computational social science. I focus on comparing different social media platforms, trying to understand what makes them tick. I believe that data-driven toy models can help design social media platforms that are better, and more resilient to manipulation by bad actors. I also believe that timely research can influence decision-making and ultimately pressure platforms into design decisions that do more than blindingly chase engagement metrics.
My approach involves large-scale data collection, as well as analysis and modeling using techniques from physics, statistics, and machine learning. In particular, I currently focus on large language models as both object of research (their impact on social media) and as tools for simulating and analyzing social media content.
E-Mail: joaoxp(at)gmail.com
Mathias Angermaier, M.Sc.
Doctoral Researcher
Mathias is a PhD student at IDea_Lab and at Graz University of Technology. He holds a Bachelor's degree in Business Informatics from the University of Regensburg and a Master's degree in Computational Social Systems from the University of Graz and Graz University of Technology.
In his master's thesis, he dealt with the algorithmic detection and differentiation of conspiracy theory topics in Telegram chats. He also investigated the dynamics of engagement and conversation patterns that are characteristic of the milieu of conspiratorial conversations.
For his doctoral thesis, Mathias is researching dynamics in collective adaptation. To this end, opinions are modeled as networks, whereby topics that are often expressed in similar contexts are particularly close to each other. These opinion networks can be very characteristic for individual people and also aggregated for groups. Changes in these networks due to new group constellations can provide indications of the extent to which people are influenced in their decisions by their social environment. In addition to agent-based modeling approaches, data from social networks is used to depict such opinion networks and look at their patterns of change. In the context of conspiracy theories, too, the aim is to identify trends that allow conclusions to be drawn about the collective extremization of people and provide new starting points for detailed qualitative social research in this area.
