Papers by Gabriella Lapesa
Moderation in the Wild: Investigating User-Driven Moderation in Online Discussions (2024.eacl-long)
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| Challenge: | Effective content moderation is imperative for fostering healthy and productive discussions in online domains. |
| Approach: | They propose to document and release a dataset of comments in which users act as moderators. |
| Outcome: | The proposed dataset contains 1000 comment-reply pairs with crowdsourced annotations from a large annotator pool and fine-grained annotation schema targeting the functions of moderation, stylistic properties(aggressiveness, subjectivity, sentiment), constructiveness, and individual perspectives of the annotators on the task. |
Scaling up Discourse Quality Annotation for Political Science (2022.lrec-1)
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| Challenge: | Existing annotations on deliberative quality are time-consuming and suffer from class imbalance . ephd thesis: deliberation is not only the output of the decision making, but also the discussion that leads up to it. |
| Approach: | They propose to use data augmentation techniques to improve deliberative quality predictions in a standard dataset. |
| Outcome: | The proposed methods outperform classifiers based on linguistic features and argument quality annotations with or without data augmentation. |
DEbateNet-mig15:Tracing the 2015 Immigration Debate in Germany Over Time (2020.lrec-1)
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Gabriella Lapesa, Andre Blessing, Nico Blokker, Erenay Dayanik, Sebastian Haunss, Jonas Kuhn, Sebastian Padó
| Challenge: | a dataset for germany covering the public debate on immigration is annotated . a political science notion of a claim is used to represent the political discourse . |
| Approach: | They annotate a dataset for german public debate on immigration in 2015 using a political science notion of a claim . they identify claims in newspaper articles, assign them to actors and fine-grained categories and annotize their polarity and date. |
| Outcome: | The dataset is annotated by a political science framework and shows it captures political debate . it shows that political actors can change their positions and take a strong stand against them . |
Argument Quality Assessment in the Age of Instruction-Following Large Language Models (2024.lrec-main)
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Henning Wachsmuth, Gabriella Lapesa, Elena Cabrio, Anne Lauscher, Joonsuk Park, Eva Maria Vecchi, Serena Villata, Timon Ziegenbein
| Challenge: | Argument quality assessment is critical for opinion formation, decision making, writing education, and the like. |
| Approach: | They propose to use large language models to leverage knowledge across contexts to enable a much more reliable assessment. |
| Outcome: | The proposed approach improves the quality of argumentation and the ability to leverage knowledge across contexts. |
Node Placement in Argument Maps: Modeling Unidirectional Relations in High & Low-Resource Scenarios (2023.acl-long)
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| Challenge: | Argument maps structure discourse into nodes with each node being an argument that supports or opposes its parent argument. |
| Approach: | They propose a task of node placement: suggesting candidate nodes as parents for a new contribution. |
| Outcome: | The proposed method improves the quality of the argument maps and reduces redundancy. |
Towards a Perspectivist Turn in Argument Quality Assessment (2025.naacl-long)
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| Challenge: | Argument quality is a key aspect of computational argumentation (CA), but it still exhibits a high degree of subjectivity in perception. |
| Approach: | They propose to use a multi-layered classification to target two aspects of argument quality in a systematic review of NLP datasets. |
| Outcome: | The proposed model improves the quality of annotators and their ability to be used in perspectivist research. |
StoryARG: a corpus of narratives and personal experiences in argumentative texts (2023.acl-long)
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| Challenge: | Narratives and argumentation are deeply related, according to psychologists and social scientists. |
| Approach: | They annotated StoryARG from well-established corpora in computational argumentation and the Social Sciences, as well as comments to New York Times articles. |
| Outcome: | The dataset contains 2451 textual spans annotated at two levels . it reveals positive impact on effectiveness for stories which illustrate a solution to a problem and in general, annotator-specific preferences . |
Bridging Argument Quality and Deliberative Quality Annotations with Adapters (2023.findings-eacl)
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| Challenge: | Assessing the quality of an argument is a complex, highly subjective task . argument quality dimensions are complex and dependent on the context in which it is assessed . |
| Approach: | They propose a multi-task learning framework that incorporates knowledge about related dimensions into the learning process. |
| Outcome: | The proposed framework improves quality prediction in an extrinsic, out-of-domain task. |
Tell Me What You Know About Sexism: Expert-LLM Interaction Strategies and Co-Created Definitions for Zero-Shot Sexism Detection (2025.findings-naacl)
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| Challenge: | Large Language Models (LLMs) with chat interfaces are increasingly popular in various scientific fields, for a variety of tasks related to social science research questions. |
| Approach: | They propose to use large language models to combine human and machine expertise to improve their models' performance. |
| Outcome: | The proposed model performs better with co-created definitions than with expert-written definitions. |
It Is Not Only the Negative that Deserves Attention! Understanding, Generation & Evaluation of (Positive) Moderation (2025.naacl-long)
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| Challenge: | Moderation is essential for maintaining and improving the quality of online discussions. |
| Approach: | They annotate a dataset on 13 modes of discussion and use it to generate positive moderation. |
| Outcome: | The proposed model shows that professional moderation generates higher ratings than professional moderated moderation, but prefers professional moderate in pairwise comparison. |
Improving Neural Political Statement Classification with Class Hierarchical Information (2022.findings-acl)
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Erenay Dayanik, Andre Blessing, Nico Blokker, Sebastian Haunss, Jonas Kuhn, Gabriella Lapesa, Sebastian Pado
| Challenge: | skewed classification of fine-grained categories in text-based computational social science is challenging on the NLP side. |
| Approach: | They propose to use hierarchical relations among categories in codebooks to create constraints on the learned model. |
| Outcome: | The proposed model improves on two datasets and multiple languages. |
Mining the uncertainty patterns of humans and models in the annotation of moral foundations and human values (2025.acl-long)
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| Challenge: | disagreement in annotation (HLV) is considered a constitutive feature of subjective tasks. |
| Approach: | They investigate the relationship between disagreement in annotation and model uncertainty . they use linguistic features to calibrate models to HLV and uncertainty to analyze their impact on uncertainty. |
| Outcome: | The proposed model uncertainty is calibrated to human label variation (HLV) the proposed model is calibrate to human labels, the authors show . |
Self-reported Demographics and Discourse Dynamics in a Persuasive Online Forum (2024.lrec-main)
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| Challenge: | Research on language as interactive discourse demonstrates the deliberate use of demographic parameters such as gender, ethnicity, and class to shape social identities. |
| Approach: | They propose to investigate the role and effects of gender self-disclosures on online discourse dynamics by focusing on author gender. |
| Outcome: | The proposed dataset will provide a further impulse for research on the interplay between gender disclosures, community interaction, and persuasion in online discourse. |
Investigating Independence vs. Control: Agenda-Setting in Russian News Coverage on Social Media (2022.lrec-1)
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| Challenge: | a major challenge in the media industry has always been its targeted manipulation, says a new study . agenda-setting is a well-known phenomenon in political science . authors explore the relationship between economic indicators and mentions of foreign geopolitical entities . |
| Approach: | They investigate agenda-setting in the Russian social media landscape . they explore the relation between economic indicators and mentions of foreign geopolitical entities . |
| Outcome: | The authors examine the relationship between economic indicators and mentions of foreign geopolitical entities, as well as of Russia itself. |
Mining, Assessing, and Improving Arguments in NLP and the Social Sciences (2024.lrec-tutorials)
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| Challenge: | a tutorial on computational argumentation is updated to address the problem of argument quality . argument quality is a field of interdisciplinary research that connects natural language processing to social sciences . |
| Approach: | They present an updated version of the EACL 2023 tutorial on argument quality . they will focus on the notions of argument quality across disciplines . |
| Outcome: | The updated version of the EACL 2023 tutorial focuses on argument quality assessment . the authors will focus on the interface between Argument Mining and Deliberation Theory . |
Mining, Assessing, and Improving Arguments in NLP and the Social Sciences (2023.eacl-tutorials)
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| Challenge: | a tutorial on argument quality assessment will focus on what makes an argument good or bad . argument quality is a field encompassing varying tasks on the automated analysis and synthesis of natural language arguments. |
| Approach: | This tutorial will focus on the assessment of argument quality across disciplines . authors will involve participants in annotation studies on the quality assessment . |
| Outcome: | The tutorial will focus on the assessment of argument quality across disciplines . it will involve participants in two annotation studies on the quality assessment and the improvement of quality . |
From Emotion to Expression: Theoretical Foundations and Resources for Fear Speech (2026.eacl-long)
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| Challenge: | a new study of fear speech is under-resourced and fragmented. authors review existing definitions and propose a taxonomy that consolidates different dimensions of fear. |
| Approach: | They propose a taxonomy that consolidates different dimensions of fear for studying fear speech. |
| Outcome: | The proposed taxonomy consolidates different dimensions of fear for studying fear speech. |
An Environment for Relational Annotation of Political Debates (P19-3)
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| Challenge: | Scalable text analysis techniques can open corpora to new questions in computational social sciences and digital humanities. |
| Approach: | They describe a tool that allows annotating newspaper text with rich information about claims (demands) raised by politicians and other actors. |
| Outcome: | The MARDY tool realizes the complete workflow necessary for annotating a large newspaper text collection with rich information about claims (demands) raised by politicians and other actors. |
Towards Argument Mining for Social Good: A Survey (2021.acl-long)
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| Challenge: | Argument Mining is a social science-based approach to analysis and analysis of arguments. |
| Approach: | They propose a novel definition of argument quality which integrates the social science literature and the argument quality. |
| Outcome: | The proposed definition of argument quality integrates the social science literature and the argument quality debate. |
Reports of personal experiences and stories in argumentation: datasets and analysis (2022.acl-long)
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| Challenge: | Personal experiences and stories are important in argumentation, but they are not considered in the social sciences. |
| Approach: | They propose to use annotated documents to scale-up the analysis using existing annotations. |
| Outcome: | The proposed classifiers can identify documents containing personal experiences and reports . they can scale up to three domains and show that they perform well across domains. |
Toeing the Party Line: Election Manifestos as a Key to Understand Political Discourse on Twitter (2024.findings-emnlp)
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| Challenge: | Recent work on political positioning on Twitter has tended to focus on manifestos rather than social media since it is ambiguous and dependent on social context. |
| Approach: | They propose to use hashtags as a signal to fine-tune text representations for politicians' tweets using a hashtag-based method to predict pairwise positional similarities between parties from the manifesto case to the Twitter case. |
| Outcome: | The proposed method matches politicians' statements to official lines of the parties' tweets, even when only small subsets from shorter time periods are available. |
Stories and Personal Experiences in the COVID-19 Discourse (2024.lrec-main)
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| Challenge: | 'storytelling' is a human strategy to use personal experiences to back-up one's position in debates about controversial topics. |
| Approach: | They analyse the use of storytelling in the COVID-19 discourse by automatically annotating three publicly available Reddit datasets for a total of 367K comments. |
| Outcome: | The proposed analysis on three publicly available Reddit datasets shows that storytelling is a powerful argumentative tool. |
AI Argues Differently: Distinct Argumentative and Linguistic Patterns of LLMs in Persuasive Contexts (2025.emnlp-main)
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| Challenge: | Distinguishing LLM-generated text from human-written is a key challenge for safe and ethical NLP, especially in high-stake settings such as persuasive online discourse. |
| Approach: | They propose to use general-purpose linguistic features and domain-specific features related to argument quality to compare human- and LLM-authored arguments. |
| Outcome: | The proposed framework compares arguments by humans and three LLMs using two easily-interpretable feature sets. |
PerspectiveMod: A Perspectivist Resource for Deliberative Moderation (2025.emnlp-main)
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| Challenge: | Human moderators in online discussions face a heterogeneous range of tasks that go beyond content moderation, or policing. |
| Approach: | They propose a dataset of online comments annotated for the question "Does this comment require moderation?" they aim to improve discussion quality by analyzing annotator perspectives and annotating their views. |
| Outcome: | The proposed model is unique in its intentional variation across the level of moderation experience embedded in the source data, the annotator profiles and the individuality of the annnotator. |
How to Translate Your Samples and Choose Your Shots? Analyzing Translate-train & Few-shot Cross-lingual Transfer (2022.findings-naacl)
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| Challenge: | Recent studies have focused on zero-shot cross-lingual transfer of pretrained languages. |
| Approach: | They propose to use few-shot cross-lingual transfer to improve zero-shot performance of multilingual pretrained language models. |
| Outcome: | The proposed model can be scaled to high-quality samples and improves on zero-shot performance. |