Our kind of people? Detecting populist references in political debates (2023.findings-eacl)
Copied to clipboard
| Challenge: | Existing literature on populism has only limited agreement on its exact properties . |
| Approach: | They propose a cross-lingual dataset to identify populist rhetoric in text . they propose 'hierarchical' annotation procedure to annotate populist references . |
| Outcome: | The proposed dataset can be used to investigate how political actors talk about The Elite and The People and to study how populist rhetoric is used as a strategic device. |
Similar Papers
PopAut: An Annotated Corpus for Populism Detection in Austrian News Comments (2024.lrec-main)
Copied to clipboard
| Challenge: | Populism is a phenomenon that is noticeably present in political landscapes worldwide . prior work on populism analysis focused on analyzing populist content expressed by politicians . |
| Approach: | They present a corpus of news comments annotated for populism in the german language . they use machine learning to detect populist comments in text . |
| Outcome: | The proposed corpus outperforms existing dictionaries for populism detection in text . it features 1,200 comments collected between 2019-2021 . |
Us vs. Them: A Dataset of Populist Attitudes, News Bias and Emotions (2021.eacl-main)
Copied to clipboard
| Challenge: | Populist rhetoric has risen across the political sphere in recent years, but computational approaches to it have been scarce. |
| Approach: | They propose a dataset of 6861 reddit comments annotated for populist attitudes and a set of multi-task learning models that leverage emotion and group identification as auxiliary tasks. |
| Outcome: | The proposed models leverage emotion and group identification as auxiliary tasks to model populist rhetoric tasks. |
Identifying Fine-grained Forms of Populism in Political Discourse: A Case Study on Donald Trump’s Presidential Campaigns (2026.eacl-long)
Copied to clipboard
| Challenge: | Large Language Models excel in a wide range of instruction-following tasks, but their grasp of social science concepts remains underexplored. |
| Approach: | They evaluate pre-trained large language models to identify populist discourse . they use a RoBERTa classifier to analyze campaign speeches by Donald Trump . |
| Outcome: | The proposed model outperforms all new-era instruction-tuned LLMs on populist discourse analysis. |
Ideology Takes Multiple Looks: A High-Quality Dataset for Multifaceted Ideology Detection (2023.emnlp-main)
Copied to clipboard
| Challenge: | Existing datasets for the ID task only label a text as ideologically left- or right-leaning as a whole, regardless whether the text containing one or more different issues. |
| Approach: | They construct an ideological schema for a multifaceted ideology detection task using MITweet and an English Twitter dataset. |
| Outcome: | The proposed task uses a MITweet dataset with 12,594 English Twitter posts, each annotated with a Relevance and an Ideology label for all twelve facets. |
Voices in a Crowd: Searching for clusters of unique perspectives (2024.emnlp-main)
Copied to clipboard
| Challenge: | Proposed solutions aim to capture minority perspectives by either modelling annotator disagreements or grouping annotators based on shared metadata. |
| Approach: | They propose a framework that trains models without encoding annotator metadata and creates clusters of similar opinions, that are called voices. |
| Outcome: | The proposed framework captures minority perspectives based on demographic factors in two distinct datasets while also capturing majority perspectives. |
Uncovering Agendas: A Novel French & English Dataset for Agenda Detection on Social Media (2024.lrec-main)
Copied to clipboard
| Challenge: | a social media analysis of online influence campaigns can reveal the sources of agenda setting . annotated data is limited or nonexistent, but there are methods to detect agenda control . |
| Approach: | They propose a method for detecting instances of agenda control through social media . they use a modest corpus of tweets centered on the 2022 french presidential election . |
| Outcome: | The proposed method overcomes the requirement for large annotated training dataset. |
How to Do Politics with Words: Investigating Speech Acts in Parliamentary Debates (2024.lrec-main)
Copied to clipboard
| Challenge: | a new perspective on framing through the lens of speech acts investigates how politicians make use of different pragmatic speech act functions in political debates. |
| Approach: | They propose a new framework for framing through the lens of speech acts and an annotation scheme for political debates. |
| Outcome: | The proposed framework can predict speech acts with an avg. F1 of around 82.0% . the proposed framework is based on a dataset of German parliamentary debates . |
Introducing Rhetorical Parallelism Detection: A New Task with Datasets, Metrics, and Baselines (2023.emnlp-main)
Copied to clipboard
| Challenge: | Parallelism is a common stylistic tool in rhetorical structures, but it is rarely investigated in the field of natural language processing. |
| Approach: | They propose a task of rhetorical parallelism detection to investigate its structure and meaning . they use a Latin and adapted Chinese dataset to define parallelise and define it using a family of metrics . |
| Outcome: | The proposed method achieves F1 scores on Latin and Chinese datasets. |
Machine-Aided Annotation for Fine-Grained Proposition Types in Argumentation (2020.lrec-1)
Copied to clipboard
| Challenge: | a corpus of 2016 debates and commentary contains 4,648 argumentative propositions annotated with fine-grained proposition types. |
| Approach: | They propose a machine learning-human workflow for annotating for four complex proposition types . they demonstrate with preliminary analysis of rhetorical strategies and structure in presidential debates . |
| Outcome: | The proposed method can be used by technical researchers seeking more nuanced representations of argument . it can also be used to analyze rhetorical strategies and structure in presidential debates . |
Who’s in, who’s out? Predicting the Inclusiveness or Exclusiveness of Personal Pronouns in Parliamentary Debates (2022.lrec-1)
Copied to clipboard
| Challenge: | clusivity properties of personal pronouns are captured in context, including/excluding audience and/or non-speech act participants. |
| Approach: | They propose a compositional annotation scheme to capture the clusivity properties of personal pronouns in context, which is their ability to construct and manage in-groups and out-group. |
| Outcome: | The proposed schema achieves high inter-annotator agreement with a Cohen’s in the range of 89.7-93.2 and a percentage agreement of > 96%. |