| Challenge: | a novel visualisation approach for sentiment and stance analysis is proposed for large datasets. |
| Approach: | They propose a visualisation approach for scalable visualisation of sentiment and stance from large-scale data. |
| Outcome: | The proposed visualisation approach can be used on a 9,278 user comments with stance explicitly declared by the author. |
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| Challenge: | chit-chat neural models lacking specificity and coherence, argues a new study on stance-based personas . stancebased personal representations lack generalization capability, allowing agents to sustain personal points of view both within the same conversation and across different discussions. |
| Approach: | They propose to investigate stance-based persona representations and their impact on claim generation by using a conversational dataset. |
| Outcome: | The proposed dataset shows that stance-based personas grasp abstract and profound aspects of the author persona. |
-Stance: A Large-Scale Real World Dataset of Stances in Legal Argumentation (2025.acl-long)
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| Challenge: | Current tools for legal argument reasoning do not support this task. |
| Approach: | They propose to use a large-scale dataset to facilitate work on the legal argument stance classification task by evaluating whether a case summary strengthens or weakens a legal argument. |
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Contrastive Language Adaptation for Cross-Lingual Stance Detection (D19-1)
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| Challenge: | Current approaches to fact-checking are time-consuming and tedious. |
| Approach: | They propose a novel approach which leverages labeled data in one language to identify relative perspective of a document with respect to a claim in a different target language. |
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Aligning Large Language Models with Diverse Political Viewpoints (2024.emnlp-main)
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| Challenge: | Large language models such as ChatGPT exhibit striking political biases . a recent study shows that chatbots exhibit progressive, liberal, and proenvironmental biase . |
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The ParlaSent Multilingual Training Dataset for Sentiment Identification in Parliamentary Proceedings (2024.lrec-main)
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| Challenge: | The paper presents a new training dataset of sentences in 7 languages, manually annotated for sentiment, which is used in a series of experiments focused on training a robust sentiment identifier for parliamentary proceedings. |
| Approach: | They propose to use a dataset of sentences manually annotated for sentiment to train a robust sentiment identifier for parliamentary proceedings. |
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Investigating Online Community Engagement through Stancetaking (2023.findings-emnlp)
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| Challenge: | Large-scale computational work on stancetaking has explored community similarities in their preferences for stance markers without considering the stance-relevant properties of the contexts in which stance marker use is carried out. |
| Approach: | They propose to use stance-relevant properties of Reddit communities to capture community identity patterns distinct from textual or marker similarity measures. |
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TextBI: An Interactive Dashboard for Visualizing Multidimensional NLP Annotations in Social Media Data (2024.eacl-demo)
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Maxime Masson, Christian Sallaberry, Marie-Noelle Bessagnet, Annig Le Parc Lacayrelle, Philippe Roose, Rodrigo Agerri
| Challenge: | TextBI is a generic dashboard designed to present multidimensional text annotations on large volumes of multilingual social media data. |
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GPolS: A Contextual Graph-Based Language Model for Analyzing Parliamentary Debates and Political Cohesion (2020.coling-main)
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| Challenge: | Parliamentary debates are a valuable language resource for analyzing comprehensive options in a functional, free society. |
| Approach: | They propose a neural model for political speech sentiment analysis exploiting semantic representations and relations between debate transcripts, motions, and political party members. |
| Outcome: | The proposed model exploits semantic representations and relations between debate transcripts, motions, and political party members to predict political polarity and polarities. |
Dynamic Stance: Modeling Discussions by Labeling the Interactions (2023.findings-emnlp)
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| Challenge: | Stance detection is a popular task that has been modeled as a static task, but its limitations are strong topic-dependent. |
| Approach: | They propose to model stance as a dynamic task by focusing on interactions between a message and their replies. |
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Investigating Political Herd Mentality: A Community Sentiment Based Approach (P19-2)
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| Challenge: | polarities inherent in political speeches and debates pose an important problem today. |
| Approach: | They propose to use community-based graphs to augment hand-crafted features based on topic modeling and emotion detection on debate transcripts. |
| Outcome: | The proposed approach surpasses the benchmark results on the same dataset. |