The TTLab (Text Technology Lab), headed by Prof. Alexander Mehler, is part of the Department of Computer Science and Mathematics (Fachbereich Informatik und Mathematik) at the Goethe Universität in Frankfurt. It investigates formal, algorithmic models to deepen our understanding of information processing in the humanities. We examine diachronic, time-dependent as well as synchronic aspects of processing linguistic and non-linguistic, multimodal signs. The Lab works across several disciplines to bridge between computer science on the one hand and corpus-based research in the humanities on the other. To this end, we develop information models and algorithms for the analysis of texts, images, and other objects relevant to research in the humanities.
News
-
New publication accepted at ITC 2026
by
The following paper has been accepted for publication in the proceedings of the International Test Commission Conference (ITC) 2026 in Auckland, New Zealand:
Linguistic Features as Predictors of Students’ Performance in Domain-Specific Critical Online Reasoning Tasks
2026. Linguistic Features as Predictors of Students' Performance in Domain-Specific Critical Online Reasoning Tasks. International Test Commission Conference (ITC) 2026. accepted.BibTeX@inproceedings{Bisang:Mehler:2026, title = {Linguistic Features as Predictors of Students' Performance in Domain-Specific Critical Online Reasoning Tasks}, author = {Bisang, Walter and Mehler, Alexander}, booktitle = {International Test Commission Conference (ITC) 2026}, eventdate = {2026-06-30/2026-07-03}, location = {Auckland, New Zealand}, note = {accepted}, year = {2026}, keywords = {core,core_b05} } -
New publication accepted at WASSA
by
The following paper has been accepted for publication in the proceedings of the 15th Workshop on Computational Approaches to Subjectivity, Sentiment, & Social Media Analysis (WASSA):
Predicting Convincingness in Political Speech: How Emotional Tone Shapes Persuasive Strength
2026. Predicting Convincingness in Political Speech: How Emotional Tone Shapes Persuasive Strength. Proceedings of the 15th Workshop on Computational Approaches to Subjectivity, Sentiment, & Social Media Analysis. accepted.BibTeX@inproceedings{Verma:et:al:2026, title = {Predicting Convincingness in Political Speech: How Emotional Tone Shapes Persuasive Strength}, booktitle = {Proceedings of the 15th Workshop on Computational Approaches to Subjectivity, Sentiment, \& Social Media Analysis}, year = {2026}, author = {Verma, Bhuvanesh and Marreddy, Mounika and Mehler, Alexander}, keywords = {Argument Detection, Argument Quality Assessment,Topic Modelling, Persuasiveness, Convincingness, Emotion Analysis, Argument Mining}, abstract = {Emotional tone plays a central role in persuasion, yet its impact on computational assessments of political argument quality in real world election campaign speeches remains understudied. In this work, we investigate whether positive emotional framing correlates with higher perceived convincingness in political arguments. We fine-tune language models on argument quality datasets and test their ability to transfer convincingness predictions to real-world campaign speeches. Using a corpus of U.S. presidential campaign speeches, we analyze emotional polarity in relation to predicted persuasive strength to test whether positively framed arguments are judged more convincing than neutral or negative ones. Our empirical analysis shows that political parties rely heavily on argumentation during their election campaigns. Also, we found the evidence that politicians strategically employ emotional cues within their arguments during these campaign speeches, with positive emotions being more strongly associated with persuasive strength, for example in topics such as USMCA’s Effect on American Jobs and Agriculture, Border Control Policies, Progressive Tax Reforms. At the same time, we find that negative emotions have a weaker yet still non-negligible influence on voter persuasion in topics such as City Crime and Civil Unrest and White Supremacist Violence (Charlottesville Incident).}, note = {accepted} } -
New article accepted at SoftwareX
by
The following article is accepted in the journal SoftwareX:
DUUIgateway: A Web Service for Platform-independent, Ubiquitous Big Data NLP
2026. DUUIgateway: A Web Service for Platform-independent, Ubiquitous Big Data NLP. SoftwareX. accepted.BibTeX@article{Borkowski:et:al:2026, title = {DUUIgateway: A Web Service for Platform-independent, Ubiquitous Big Data NLP}, journal = {SoftwareX}, year = {2026}, issn = {2352-7110}, author = {Borkowski, Cedric and Abrami, Giuseppe and Terefe, Dawit and Baumartz, Daniel and Mehler, Alexander}, keywords = {duui, neglab}, abstract = {Distributed processing of unstructured text data is a challenge in the rapidly changing and evolving natural language processing (NLP) landscape. This landscape is characterized by heterogeneous systems, models, and formats, and especially by the increasing influence of AI systems. While many of these systems handle text data, there are also unified systems that process multiple input and output formats, while allowing for distributed corpus processing. However, there are hardly any user-friendly interfaces that allow existing NLP frameworks to be used flexibly and extended in a user-controlled manner. Due to this gap and the increasing importance of NLP for various scientific disciplines, there has been a demand for a web and API based flexible software solution for deploying, managing and monitoring NLP systems. Such a solution is provided by Docker Unified UIMA-gateway. We introduce DUUIgateway and evaluate its API and user-driven approach to encapsulation. We also describe how these features improve the usability and accessibility of the NLP framework DUUI. We illustrate DUUIgateway in the field of process modeling in higher education and show how it closes the latter gap in NLP by making a variety of systems for processing text and multimodal data accessible to non-experts.}, note = {accepted} }
Sign up to our mailing list to receive news updates.
Click here to see all recent news.
