- New publication accepted at ITC 2026by Giuseppe Abrami
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} } - New publication accepted at WASSAby Giuseppe Abrami
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}, 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} }