The Sound of Populism: Distinct Linguistic Features Across Populist Variants
- URL: http://arxiv.org/abs/2505.07874v1
- Date: Sat, 10 May 2025 03:18:19 GMT
- Title: The Sound of Populism: Distinct Linguistic Features Across Populist Variants
- Authors: Yu Wang, Runxi Yu, Zhongyuan Wang, Jing He,
- Abstract summary: This study explores the sound of populism by integrating the classic Linguistic Inquiry and Word Count features.<n>We examine how four key populist dimensions (i.e., left-wing, right-wing, anti-elitism, and people-centrism) manifest in the linguistic markers of speech.
- Score: 9.195542120893293
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: This study explores the sound of populism by integrating the classic Linguistic Inquiry and Word Count (LIWC) features, which capture the emotional and stylistic tones of language, with a fine-tuned RoBERTa model, a state-of-the-art context-aware language model trained to detect nuanced expressions of populism. This approach allows us to uncover the auditory dimensions of political rhetoric in U.S. presidential inaugural and State of the Union addresses. We examine how four key populist dimensions (i.e., left-wing, right-wing, anti-elitism, and people-centrism) manifest in the linguistic markers of speech, drawing attention to both commonalities and distinct tonal shifts across these variants. Our findings reveal that populist rhetoric consistently features a direct, assertive ``sound" that forges a connection with ``the people'' and constructs a charismatic leadership persona. However, this sound is not simply informal but strategically calibrated. Notably, right-wing populism and people-centrism exhibit a more emotionally charged discourse, resonating with themes of identity, grievance, and crisis, in contrast to the relatively restrained emotional tones of left-wing and anti-elitist expressions.
Related papers
- Language-Dependent Political Bias in AI: A Study of ChatGPT and Gemini [0.0]
This study investigates the political tendency of large language models and the existence of differentiation according to the query language.<n>ChatGPT and Gemini were subjected to a political axis test using 14 different languages.<n>A comparative analysis revealed that Gemini exhibited a more pronounced liberal and left-wing tendency compared to ChatGPT.
arXiv Detail & Related papers (2025-04-08T21:13:01Z) - ChatGPT for President! Presupposed content in politicians versus GPT-generated texts [0.0]
This study examines ChatGPT-4's capability to replicate linguistic strategies used in political discourse.<n>Using a corpus-based pragmatic analysis, this study assesses how well ChatGPT can mimic these persuasive strategies.
arXiv Detail & Related papers (2025-03-03T07:48:04Z) - Classifying populist language in American presidential and governor speeches using automatic text analysis [0.0]
We develop a pipeline to train and validate an automated classification model to estimate the use of populist language.
We find that these models classify most speeches correctly, including 84% of governor speeches and 89% of presidential speeches.
arXiv Detail & Related papers (2024-08-27T17:19:57Z) - What Do Dialect Speakers Want? A Survey of Attitudes Towards Language Technology for German Dialects [60.8361859783634]
We survey speakers of dialects and regional languages related to German.
We find that respondents are especially in favour of potential NLP tools that work with dialectal input.
arXiv Detail & Related papers (2024-02-19T09:15:28Z) - Quantifying the Uniqueness of Donald Trump in Presidential Discourse [51.76056700705539]
This paper introduces a novel metric of uniqueness based on large language models.
We find considerable evidence that Trump's speech patterns diverge from those of all major party nominees for the presidency in recent history.
arXiv Detail & Related papers (2024-01-02T19:00:17Z) - Task-Agnostic Low-Rank Adapters for Unseen English Dialects [52.88554155235167]
Large Language Models (LLMs) are trained on corpora disproportionally weighted in favor of Standard American English.
By disentangling dialect-specific and cross-dialectal information, HyperLoRA improves generalization to unseen dialects in a task-agnostic fashion.
arXiv Detail & Related papers (2023-11-02T01:17:29Z) - PopBERT. Detecting populism and its host ideologies in the German
Bundestag [0.0]
This paper aims to provide a reliable, valid, and scalable approach to measure populist stances.
We label moralizing references to the virtuous people or the corrupt elite as core dimensions of populist language.
To identify, in addition to how the thin ideology of populism is thickened, we annotate how populist statements are attached to left-wing or right-wing host ideologies.
arXiv Detail & Related papers (2023-09-22T14:48:02Z) - The Face of Populism: Examining Differences in Facial Emotional Expressions of Political Leaders Using Machine Learning [50.24983453990065]
We use a deep-learning approach to process a sample of 220 YouTube videos of political leaders from 15 different countries.
We observe statistically significant differences in the average score of negative emotions between groups of leaders with varying degrees of populist rhetoric.
arXiv Detail & Related papers (2023-04-19T18:32:49Z) - Cross-Lingual Speaker Identification Using Distant Supervision [84.51121411280134]
We propose a speaker identification framework that addresses issues such as lack of contextual reasoning and poor cross-lingual generalization.
We show that the resulting model outperforms previous state-of-the-art methods on two English speaker identification benchmarks by up to 9% in accuracy and 5% with only distant supervision.
arXiv Detail & Related papers (2022-10-11T20:49:44Z) - Perception Point: Identifying Critical Learning Periods in Speech for
Bilingual Networks [58.24134321728942]
We compare and identify cognitive aspects on deep neural-based visual lip-reading models.
We observe a strong correlation between these theories in cognitive psychology and our unique modeling.
arXiv Detail & Related papers (2021-10-13T05:30:50Z) - Us vs. Them: A Dataset of Populist Attitudes, News Bias and Emotions [10.112779201155005]
We present the new Us vs. Them dataset, consisting of 6861 Reddit comments annotated for populist attitudes.
We investigate the relationship between populist mindsets and social groups, as well as a range of emotions typically associated with these.
We present a set of multi-task learning models that leverage and demonstrate the importance of emotion and group identification as auxiliary tasks.
arXiv Detail & Related papers (2021-01-28T12:18:19Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.