Publication

New publication accepted at WASSA

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}
}

New article published at SoftwareX

The following article is published in the journal SoftwareX:

DUUIgateway: A Web Service for Platform-independent, Ubiquitous Big Data NLP

Cedric Borkowski, Giuseppe Abrami, Dawit Terefe, Daniel Baumartz and Alexander Mehler. 2026. DUUIgateway: A Web Service for Platform-independent, Ubiquitous Big Data NLP. SoftwareX, 34:102549.
BibTeX
@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.}
}

New publication in the proceedings of SuB 30:

The following paper has been accepted for publication in the proceedings of Sinn und Bedeutung, Special Session: Philosophical and Linguistic Approaches to Negation (PhilLingNeg).

Andy Lücking, Leon Hammerla and Alexander Mehler. 2026. Not every quantifier can be negated. Proceedings of Sinn und Bedeutung, Special Session “Philosophical and Linguistic Approaches to Negation (PhilLingNeg)”. accepted.
BibTeX
@inproceedings{Luecking:Hammerla:Mehler:2026,
  author    = {Lücking, Andy and Hammerla, Leon and Mehler, Alexander},
  title     = {Not every quantifier can be negated},
  booktitle = {Proceedings of \textit{Sinn und Bedeutung}, Special Session ``Philosophical
               and Linguistic Approaches to Negation (PhilLingNeg)''},
  series    = {SuB'30},
  location  = {Frankfurt am Main},
  year      = {2026},
  pubstate  = {forthcoming},
  keywords  = {neglab},
  note      = {accepted}
}

Two publications accepted at IJCNLP-AACL

The following publications were accepted at the International Joint Conference on Natural Language Processing & Asia-Pacific Chapter of the Association for Computational Linguistics (IJCNLP-AACL):

Leon Hammerla, Alexander Mehler and Giuseppe Abrami. December, 2025. Standardizing Heterogeneous Corpora with DUUR: A Dual Data- and Process-Oriented Approach to Enhancing NLP Pipeline Integration. Proceedings of the 14th International Joint Conference on Natural Language Processing and the 4th Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics, 1410–1425.
BibTeX
@inproceedings{Hammerla:et:al:2025a,
  author    = {Hammerla, Leon and Mehler, Alexander and Abrami, Giuseppe},
  title     = {Standardizing Heterogeneous Corpora with {DUUR}: A Dual Data-
               and Process-Oriented Approach to Enhancing NLP Pipeline Integration},
  editor    = {Inui, Kentaro and Sakti, Sakriani and Wang, Haofen and Wong, Derek F.
               and Bhattacharyya, Pushpak and Banerjee, Biplab and Ekbal, Asif and Chakraborty, Tanmoy
               and Singh, Dhirendra Pratap},
  booktitle = {Proceedings of the 14th International Joint Conference on Natural
               Language Processing and the 4th Conference of the Asia-Pacific
               Chapter of the Association for Computational Linguistics},
  month     = {dec},
  year      = {2025},
  address   = {Mumbai, India},
  publisher = {The Asian Federation of Natural Language Processing and The Association for Computational Linguistics},
  url       = {https://aclanthology.org/2025.findings-ijcnlp.87/},
  pages     = {1410--1425},
  isbn      = {979-8-89176-303-6},
  abstract  = {Despite their success, LLMs are too computationally expensive
               to replace task- or domain-specific NLP systems. However, the
               variety of corpus formats makes reusing these systems difficult.
               This underscores the importance of maintaining an interoperable
               NLP landscape. We address this challenge by pursuing two objectives:
               standardizing corpus formats and enabling massively parallel corpus
               processing. We present a unified conversion framework embedded
               in a massively parallel, microservice-based, programming language-independent
               NLP architecture designed for modularity and extensibility. It
               allows for the integration of external NLP conversion tools and
               supports the addition of new components that meet basic compatibility
               requirements. To evaluate our dual data- and process-oriented
               approach to standardization, we (1) benchmark its efficiency in
               terms of processing speed and memory usage, (2) demonstrate the
               benefits of standardized corpus formats for NLP downstream tasks,
               and (3) illustrate the advantages of incorporating custom formats
               into a corpus format ecosystem.},
  keywords  = {neglab,duui}
}
Leon Hammerla, Andy Lücking, Carolin Reinert and Alexander Mehler. December, 2025. D-Neg: Syntax-Aware Graph Reasoning for Negation Detection. Proceedings of the 14th International Joint Conference on Natural Language Processing and the 4th Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics, 1432–1454.
BibTeX
@inproceedings{Hammerla:et:al:2025b,
  author    = {Hammerla, Leon and Lücking, Andy and Reinert, Carolin and Mehler, Alexander},
  title     = {{D}-Neg: Syntax-Aware Graph Reasoning for Negation Detection},
  editor    = {Inui, Kentaro and Sakti, Sakriani and Wang, Haofen and Wong, Derek F.
               and Bhattacharyya, Pushpak and Banerjee, Biplab and Ekbal, Asif and Chakraborty, Tanmoy
               and Singh, Dhirendra Pratap},
  booktitle = {Proceedings of the 14th International Joint Conference on Natural
               Language Processing and the 4th Conference of the Asia-Pacific
               Chapter of the Association for Computational Linguistics},
  month     = {dec},
  year      = {2025},
  address   = {Mumbai, India},
  publisher = {The Asian Federation of Natural Language Processing and The Association for Computational Linguistics},
  url       = {https://aclanthology.org/2025.findings-ijcnlp.89/},
  pages     = {1432--1454},
  isbn      = {979-8-89176-303-6},
  abstract  = {Despite the communicative importance of negation, its detection
               remains challenging. Previous approaches perform poorly in out-of-domain
               scenarios, and progress outside of English has been slow due to
               a lack of resources and robust models. To address this gap, we
               present D-Neg: a syntax-aware graph reasoning model based on a
               transformer that incorporates syntactic embeddings by attention-gating.
               D-Neg uses graph attention to represent syntactic structures,
               emulating the effectiveness of rule-based dependency approaches
               for negation detection. We train D-Neg using 7 English resources
               and their translations into 10 languages, all aligned at the annotation
               level. We conduct an evaluation of all these datasets in in-domain
               and out-of-domain settings. Our work represents a significant
               advance in negation detection, enabling more effective cross-lingual
               research.},
  keywords  = {neglab}
}