Max Pellert has a background in computer science, the social sciences, cognitive science and economics (University of Vienna, Austria and University of Ljubljana, Slovenia). He was a doctoral researcher in Computational Social Science affiliated to Complexity Science Hub Vienna and Medical University of Vienna in the WWTF research group “Emotional Well-Being in the Digital Society” led by David Garcia (now University of Konstanz). His research during his PhD focused on analyzing the digital traces of individual and collective emotional behavior and affective expression on social media. After receiving his PhD, he gained industry experience as Assistant Researcher at Sony Computer Science Laboratories Rome. He worked at the Chair for Data Science in the Economic and Social Sciences at University of Mannheim as assistant professor. Currently, he is interim Professor for Social and Behavioural Data Science at the University of Konstanz. He is broadly interested in the social sciences and uses traditional and novel computational methods from domains such as Natural Language Processing to study belief updates, emotional decay on social media, polarization, psychometric aspects of large language models, emotional well-being measured from textual data, semantic embeddings as complements to human ratings and many other interesting phenomena.


2024/04/01 I am interim Professor for Social and Behavioural Data Science at the University of Konstanz for the summer semester 2024.
2024/01/02 “AI Psychometrics: Assessing the Psychological Profiles of Large Language Models Through Psychometric Inventories” was published in Perspectives on Psychological Science.
2023/07/13 “Unpacking polarization: Antagonism and Alignment in Signed Networks of Online Interaction” under the lead of Emma Fraxanet is available as a preprint.
2022/12/23 Check out our preprint “AI Psychometrics: Using psychometric inventories to obtain psychological profiles of large language models”!
2022/11/01 I started as an assistant professor at University of Mannheim.


How psychometric tests could be administered to large language
models. AI Psychometrics: Assessing the Psychological Profiles of Large Language Models Through Psychometric Inventories
Max Pellert, Clemens M. Lechner, Claudia Wagner, Beatrice Rammstedt & Markus Strohmaier
Perspectives on Psychological Science (2024)
[abs] [cite] [bibtex] [link] [code]
setup for in silico longitudinal surveys as demonstrated in our initial
implementation. Britain’s Mood, Entailed Weekly: In Silico Longitudinal Surveys with Fine-Tuned Large Language Models
Georg Ahnert, Max Pellert, David Garcia & Markus Strohmaier
Companion Proceedings of the 16th ACM Web Science Conference (2024)
[abs] [cite] [bibtex] [link]
of our analysis framework for antagonism, alignment, cohesiveness, and
divisiveness. Unpacking polarization: Antagonism and Alignment in Signed Networks of Online Interaction
Emma Fraxanet, Max Pellert, Simon Schweighofer, Vicenç Gómez & David Garcia
ArXiv (2023)
[abs] [cite] [bibtex] [link]
series of the level of anxiety, anger, sadness and positive emotion
expression compared to the baseline in four selected
countries. Collective Emotions during the COVID-19 Outbreak
Hannah Metzler, Bernard Rimé, Max Pellert, Thomas Niederkrotenthaler, Anna Di Natale & David Garcia
Emotion (2022)
[abs] [cite] [bibtex] [link]
series and scatter plots of the daily percentage of positive emotions
reported in the survey and the aggregated sentiment of user-generated
text on (as well as changes for both
variables). Validating daily social media macroscopes of emotions
Max Pellert, Hannah Metzler, Michael Matzenberger & David Garcia
Scientific Reports (2022)
[abs] [cite] [bibtex] [link]
of chapter. Using Social Media Data to Capture Emotions Before and During COVID-19
Hannah Metzler, Max Pellert & David Garcia
World Happiness Report 2022 (2022)
[abs] [cite] [bibtex] [link]
collection and inclusion process of robotic technology comments in
Reddit. Emotional talk about robotic technologies on Reddit: Sentiment analysis of life domains, motives, and temporal themes
Nina Savela, David Garcia, Max Pellert & Atte Oksanen
New Media & Society (2021)
[abs] [cite] [bibtex] [link]
series of weekly proportion of sad and scared responses in YouGov and
gender-rescaled sadness and anxiety score on Twitter based on dictionary
analysis. Social media emotion macroscopes reflect emotional experiences in society at large
David Garcia, Max Pellert, Jana Lasser & Hannah Metzler
arXiv:2107.13236 [cs] (2021)
[abs] [cite] [bibtex] [link]
cloud generated from experimental condition participants’ negative
texts. Emotional reactions to robot colleagues in a role-playing experiment
Nina Savela, Atte Oksanen, Max Pellert & David Garcia
International Journal of Information Management (2021)
[abs] [cite] [bibtex] [link]
of a colexification network. Colexification Networks Encode Affective Meaning
Anna Di Natale, Max Pellert and David Garcia
Affective Science (2021)
[abs] [cite] [bibtex] [link]
Social Media Data in Affective Science
Max Pellert, Simon Schweighofer and David Garcia
Handbook of Computational Social Science, Volume 1: Theory, Case Studies and Ethics (2021)
[abs] [cite] [bibtex] [link]
for posts on showing the matched words in each
category. Dashboard of sentiment in Austrian social media during COVID-19
Max Pellert, Jana Lasser, Hannah Metzler and David Garcia
Frontiers in Big Data (2020)
[abs] [cite] [bibtex] [link]
in expressed valence and arousal on different timescales. The individual dynamics of affective expression on social media
Max Pellert, Simon Schweighofer & David Garcia
EPJ Data Science (2020)
[abs] [cite] [bibtex] [link]
probabilities prescribed by JC when the coin is fair (H5 ) and the
certainty of evidence is constantly at 0.8 in a randomly selected
simulation. Inference to the Best Explanation in Uncertain Evidential Situations
Borut Trpin and Max Pellert
The British Journal for the Philosophy of Science (2018)
[abs] [cite] [bibtex] [link]
plot shows the replication of an earlier finding (Douven, 2013, p. 433):
The explanationist is faster in assigning high subjective probability to
the true bias. Collective Dynamics of Multi-Agent Networks: Simulation Studies in Probabilistic Reasoning
Max Pellert
Proceedings of the MEi: CogSci Conference 2017 (2017)
[abs] [cite] [bibtex] [link]
figure shows variations of parameter λ. Are Heterogeneous Expectations a Viable Alternative to Rational Expectations in Economics?
Max Pellert
Proceedings of the MEi: CogSci Conference 2016 (2016)
[abs] [cite] [bibtex] [link]

Selected Media Reactions

Psychreg Research Finds That Psychometric Methods Can Reveal Gender-Based Prejudices of AI Systems
DIGIT.FYI Study: AI Models Reflect Gender Bias in “Psychological” Traits
Deutschlandfunk Kultur Rollenspiele mit Large Language Models
Mannheimer Morgen Studie aus Mannheim: Warum KI in Bewerbungsprozessen Frauen benachteiligt
Business Insider Studie enthüllt: Sprachbasierte KIs haben verborgene Moralvorstellungen
Telepolis KI entlarvt: Was Maschinen wirklich über uns denken Können Psychologie-Tests Vorurteile von KI aufdecken?
SWR Können Psychotests problematische Vorstellungen von KI-Modellen aufdecken?
Tagesspiegel Background Sprachbasierte KI reproduziert genderspezifische Vorurteile
SWR3 Bewertung mit Vorurteilen: Wie Sprach-KIs bei Psychotests abschneiden
Westfälische Nachrichten Sprachbasierte KI reproduziert Vorurteile
SWR2 Journal am Mittag Interview AI Psychometrics
inf. Das Informatikmagazin KI: Nicht ohne Eigenschaften
DerStandard STANDARD-User kamen mehrheitlich ohne Stimmungstief durch den Lockdown


04/2024 - 09/2024

Professor (University of Konstanz)

Professor for Social and Behavioural Data Science (interim, W2)

11/2022 - Present

Assistant Professor (University of Mannheim)

Chair for Data-Science in the Economic and Social Sciences, Business School of the University of Mannheim

Member of Junior Faculty, Habilitand
(with Prof. Dr. Markus Strohmaier)

10/2021 - 10/2022

Assistant Researcher (Sony Computer Science Laboratories Rome)

Project “Information and social dialogue”

12/2017 - 30/04/2022

PhD (Medical University of Vienna)

Medical Informatics, Biostatistics & Complex Systems

Analysing the digital traces of individual and collective emotional behaviour
(PhD Thesis, supervised by Prof. David Garcia, Faculty of Computer Science and Biomedical Engineering, Graz University of Technology)


M.Sc. (with distinction) (University of Vienna & University of Ljubljana)

Middle European interdisciplinary master programme in Cognitive Science (MEi:CogSci)

Collective Dynamics of Multi-Agent Networks: Simulation Studies in Probabilistic Reasoning
(Master Thesis, supervised by Univ.-Lektor Dipl.-Ing. Dr. Paolo Petta, OFAI)


Bakk. rer. soc. oek. (University of Vienna)

Bachelor programme in Economics

Some Remarks on the Genesis of the Neoclassical Paradigm In Economics
(Bachelor Thesis I, supervised by ao. Univ.-Prof. Mag. Dr. Reinhard Pirker, Vienna University of Economics and Business)

Popper and McCloskey. Logic or Rhetoric of Science?
(Bachelor Thesis II, supervised by ao. Univ.-Prof. Mag. Dr. Karl Milford, University of Vienna)


“Analyzing the digital traces of individual and collective emotional behavior” (PhD Thesis)
“Collective Dynamics of Multi-Agent Networks: Simulation Studies in Probabilistic Reasoning” (Master Thesis)


Sep 2023 S+T+ARTS Prize 2023
Ars Electronica
Oct 2022 Mind the Gap Diversity Award 2022
Graz University of Technology

Additional Research Experience

Technical University of Graz

Affiliation to Computational Social Science Lab (CSS Lab)

Complexity Science Hub Vienna

During PhD studies located at Complexity Science Hub Vienna (CSH)

Research Stays

May 2022 Santa Fe Institute
Mirta Galesic & Henrik Olson
(Santa Fe, New Mexico, U.S.)
Invited research stay at SFI for research collaboration, networking and giving a talk


Feb - Oct 2022 TRACEWASTE
Susi Gutsche, SONY Computer Science Laboratories Rome, MAXXI – Museo nazionale delle arti del XXI secolo
The project is realized in the framing of the S+T+ARTS fellowship program “Repairing the Present”, Challenge Nr. 3 “BIG DATA AND THE CITY”. “Repairing the Present” is co-funded by the S+T+ARTS program of the European Union and co-comissioned by SONY CSL (Vittorio Loreto, Alessandro Londei, Bernardo Monechi and Matteo Bruno) in collaboration with MAXXI Roma.
Involvement in many steps of this Art and Science project, especially in data processing and visualization. Developed an interactive interface and map animation with the collected geospatial data on waste mobility using mapbox, and turf.js as part of the final project installation exhibited at MAXXI museo.

Supervision of Master Theses

Alexander Gerhold "Understanding the Ability of Large Language Models to Capture Information About Societies"
Henry Rogner "Analyzing emotions and ideology in user posts on a news platform using advanced text analysis methods"
Florian Siebels "Measuring and Validating Collective Emotions on a German Online Newspaper Platform in the course of the COVID-19 Pandemic"
ongoing: Maria Schlüter "Working Title: Validating synthetic data approaches"

Advisor to PhD Researchers

ongoing: Emma Fraxanet "Structural Analysis and Application of Antagonistic Interactions in Online Social Networks"


Apr - Sep 2024 Deep Learning for the Social Sciences
Max Pellert & Giordano De Marzo
(University of Konstanz)

This course offers a deep dive into advanced neural network architectures and their applications in the social sciences.

4 SWS (9 ECTS)
Apr - Sep 2024 Computational Modeling of Social Systems
Max Pellert & Giordano De Marzo
(University of Konstanz)

This introductory course on computational modelling will introduce the students to the question of explaining human behavior across levels of analysis. Following a complexity science approach, the course will illustrate the basics of computational modelling with models that explain various kinds of human behavior.

4 SWS (6 ECTS)
Apr - Sep 2024 Social Media Data Analysis
Max Pellert
(University of Konstanz)

Social media data analysis is introduced as a set of techniques to analyze human behaviour and social interaction through openly-available digital traces. The course focuses both on the fundamentals and applications of data science to social media, including technologies for data retrieval, processing, and analysis with the aim to derive insights that are interpretable from a wider theoretical perspective.

4 SWS (9 ECTS)
Sep - Dec 2023 IS 616 Large Scale Data Analysis and Visualization
Max Pellert
(University of Mannheim)

This course teaches students principles of scientific visualization of data using R and Python. Starting from introductory large scale data handling and basics of visualization, more advanced methods for visualization will also be covered. Important libraries and frameworks that are essential for data analysis and visualization are introduced.

4 SWS (6 ECTS)
Feb - Jun 2023 IS 809 Advanced Data Science Lab II (Text Mining)
Markus Strohmaier & Max Pellert
(University of Mannheim)

PhD course with a focus on Natural Language Processing (NLP) methods, ranging from simple dictionary-based approaches to advanced, state of art methods that are based on neural networks.

4 SWS (6 ECTS)
Feb - Sep 2023 Team Projects Data Science
Max Pellert & Tobias Schumacher
(University of Mannheim)

Hands-on research project for a group of 5 students on the topic “Biases in Football Discussions on Social Media” (Master’s level)

4 SWS (12 ECTS)
Feb - Jun 2023 IS 723 Seminar Data-Science II (Empirical Studies)
Max Pellert & Tobias Schumacher
(University of Mannheim)

Participants familiarize themselves with one topic in data science and embed it into the field (Master’s level)

2 SWS (6 ECTS)
Feb 2023 Workshop on computational text analysis - from basic to advanced techniques
Aleksandra Urman & Max Pellert
(Internal GESIS Workshop)

Intense 4 days block course teaching basic text analysis methods, sentiment analysis and advanced NLP methods using neural nets in R & Python.

32 hours
Feb - Sep 2023 Exercises in Computational Social Science using Python
(Summer Institute for Computational Social Science (SICSS) hosted in Aachen & Graz)

As part of the larger summer school program, teaching hands-on exercises in Python focusing on replicating data analysis pipelines from existing scientific publication and introducing transformer models for NLP.

4 SWS (12 ECTS)
Sep 2021/22/23 Introduction to Computational Social Science with Applications in R
Aleksandra Urman & Max Pellert
(GESIS Fall Seminar in Computational Social Science 2021/22/23)

Intense one week block course teaching text analysis methods, web scraping, visualization and ethics of CSS research in an hands-on approach using R.

40 hours


Feb 26 2024 KION Group

Invited talk for the internal “Global AI Expert Community”

Jan 22 2024 SWR KI-Stammtisch

Invited talk at recurring internal event on latest developments in AI for all editors and journalists at SWR

Nov 7 2023 Technical University of Graz
Graz, Austria

Invited guest talk: “Methods of Computational Affective Science”

July 17 – 20 2023 IC2S2 2023
Copenhagen (Denmark)

9th International Conference on Computational Social Science (Poster: “AI Psychometrics: Using psychometric inventories to obtain psychological profiles of large language models” & “Tracking the daily dynamics of emotions at scale with news discussions in Austria”)

May 9 2022 Santa Fe Institute
Santa Fe, New Mexico, US

Invited seminar talk: “Validating daily social media macroscopes of emotions”

December 14 – 14 2021 NeurIPS 2021
Virtual (Online)

Data Centric AI Workshop

November 16 – 17 2021 NATO Advanced Research Workshop
Rome (Italy)

Fighting disinformation in a pandemic world: the role of AI and cognitive sciences

July 27 – 30 2021 IC2S2 2021
Zürich (Switzerland)

7th International Conference on Computational Social Science (Talk: “Validating social media macroscopes of emotions”)

September 2 – 4 2019 Euro CSS 2019
Zürich (Switzerland)

European Symposium Series on Societal Challenges in Computational Social Science 2019: Polarization and Radicalization (Participant in the Science Slam)

July 17 – 20 2019 IC2S2 2019
Amsterdam (Netherlands)

5th International Conference on Computational Social Science (Poster: “Emotional expression dynamics in social media”)

July 10 – 13 2019 ISRE 2019
Amsterdam (Netherlands)

Conference organised by the “International Society for Research on Emotion” (Talk: “Analysing affective dynamics through sentiment in social media status updates”)

March 3 – 8 2019 Complexity Science Hub Vienna Winter School
Obergurgl (Austria)

One week intense winter school offering courses in network science, systemic risk, synthetic biology in complex systems and more

August 6 – 10 2018 Big Data Analysis in the Social Sciences
Budapest (Hungary)

Hands-on workshop by Pablo Barberá taking place at the European Consortium for Political Research (ECPR) Summer School

June 22 – 24 2017 MEi:CogSci Conference 2017
Budapest (Hungary)

(Pellert, 2017), presentation of the results of a 10 ECTS study project

June 6 – 9 2017 Summer School on Computational Methods and Simulation for Economics
Bochum (Germany)

Hands-on workshop with Marco Valente (University of L’Aquila) and Tommaso Ciarli (University of Sussex) on the “Laboratory for Simulation Development” (LSD,

January 25 – 26 2017 Workshop: Inferentialism, Bayesianism, and Scientific Explanation
Munich (Germany)

Talk: “Inference to the Best Explanation in Cases of Uncertain Evidence”

June 23 – 25 2016 MEi:CogSci Conference 2016
Vienna (Austria)

(Pellert, 2016), poster about the results of a 10 ECTS study project

June 2 – 5 2016 INET Workshop at Festival dell’Economia
Trento (Italy)

Seminar lectures by Barry Eichengreen (University of California, Berkeley)

March 4 – 11 2016 Interdisciplinary College
Günne (Germany)

Week-long, intense spring school on AI, Cognitive Science and beyond

May 29 – June 2 2015 INET Wokshop at Festival dell’Economia
Trento (Italy)

Seminar lectures by Joseph Stiglitz (Columbia University), Martin Guzman (Columbia University) and Steve Fazzari (Washington University of St. Louis)

August 8 – 10 2014 IMK-Workshop “Pluralismus in der Ökonomik”
Berlin (Germany)

Talk: “Popper und McCloskey: Konsequenzen der Kritik”

Last updated on 2024-07-03