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
Walter Bisang and Alexander Mehler. 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}
}
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
Bhuvanesh Verma, Mounika Marreddy and Alexander Mehler. 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, satek},
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}
}
@article{Borkowski:et:al:2026,
title = {{DUUIgateway}: A Web Service for Platform-independent, Ubiquitous Big Data NLP},
journal = {SoftwareX},
volume = {34},
pages = {102549},
year = {2026},
issn = {2352-7110},
doi = {https://doi.org/10.1016/j.softx.2026.102549},
url = {https://www.sciencedirect.com/science/article/pii/S2352711026000439},
author = {Borkowski, Cedric and Abrami, Giuseppe and Terefe, Dawit and Baumartz, Daniel
and Mehler, Alexander},
keywords = {duui, neglab, core, core_b05, core_c08, new-data-spaces, circlet},
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.}
}
Andy Lücking and Alexander Mehler have been invited to give a talk at the Web Conference for German Teachers 2026. The topic of the speech is: “Language-accompanying gestures, AI and virtual reality – multimodal communication research at the intersection of linguistics and computer science”.
@misc{Luecking:Mehler:2026,
author = {Lücking, Andy and Mehler, Alexander},
title = {{Sprachbegleitende Gesten, KI und Virtuelle Realität}},
subtitle = {{Multimodale Kommunikationsforschung im Schnittfeld von Linguistik und Computerwissenschaft}},
howpublished = {Invited talk at DaFWEBKON26, Webkonferenz für
Deutschlehrende},
date = {2026-01-28/2026-01-30},
url = {https://dafwebkon.com/events/sprachbegleitende-gesten/},
keywords = {talk, cosgrin-vr},
note = {Invited talk},
abstract = {Alltagskommunikation ist üblicherweise multimodal (d.h., nutzt
mehr als einen Informationskanal). Gesprochene Sprache wird beispielsweise
von manuellen Gesten begleitet. Diese Gesten wiederum können über
die linguistische Bedeutung hinausgehende Information beitragen.
Sie sind also semantisch interessant.<br><br>Der Vortrag skizziert
eine räumliche Gestensemantik und führt in KI-gestützte Gestenklassifikation
ein. Um multimodale Verhaltensdaten zu erfassen und auszuwerten,
werden zunehmend Methoden der Virtuellen Realität (VR) eingesetzt.
Das Frankfurter Va.Si.Li-Lab kombiniert KI und VR für Multimodalitätsforschung.
Auf diese Weise lassen sich z.B. mutlimodal, avatarbasierte VR-Interaktionen
untersuchen und mit Face-to-face-Interaktionen vergleichen. Der
Vortrag stellt erste Ergebnisse vor.}
}