Hauke Licht
Biographic Data
| ID | 4371297 |
|---|---|
| NAME | Hauke Licht |
| GIVEN NAMES | Hauke |
| FAMILY NAME | Licht |
| SIGNATURE | LICHT H |
| AFFILIATIONS | Universität Innsbruck |
| ORCID | 0000-0002-4093-6263 |
| VERIFIED | Yes |
| TOTAL WORKS | 5 |
| TOTAL CITATIONS | 26 |
| WORKS AS AUTHOR | 5 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2023 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 2 |
Attributes, abstractions, and combinations
Research increasingly examines which social groups political actors refer to. Yet, existing approaches typically inherit classifications shaped by demand-side perspectives or conflate how groups are defined with how they are framed. We propose a novel, attribute-centred taxonomy of social group references that classifies groups by the attributes political actors invoke, organises these attributes along nested levels of abstraction, and captures a…
Validating open-source machine translation for quantitative text analysis
Machine translation (MT) is an essential tool in many multilingual computational text analysis applications. However, relying on commercial services like Google Translate or DeepL limits reproducibility and can be expensive. This paper assesses the viability of a reproducible, transparent, and affordable alternative: open-source MT models. We ask whether using open-source MT models instead of commercial services substantially changes the measurem…
Measuring and Understanding Parties’ Anti-elite Strategies
Detecting Group Mentions in Political Rhetoric A Supervised Learning Approach
Politicians appeal to social groups to court their electoral support. However, quantifying which groups politicians refer to, claim to represent, or address in their public communication presents researchers with challenges. We propose a supervised learning approach for extracting group mentions from political texts. We first collect human annotations to determine the passages of a text that refer to social groups. We then fine-tune a transformer…
Cross-Lingual Classification of Political Texts Using Multilingual Sentence Embeddings
Established approaches to analyze multilingual text corpora require either a duplication of analysts’ efforts or high-quality machine translation (MT). In this paper, I argue that multilingual sentence embedding (MSE) is an attractive alternative approach to language-independent text representation. To support this argument, I evaluate MSE for cross-lingual supervised text classification. Specifically, I assess how reliably MSE-based classifiers …
Cross-Lingual Classification of Political Texts Using Multilingual Sentence Embeddings
Established approaches to analyze multilingual text corpora require either a duplication of analysts’ efforts or high-quality machine translation (MT). In this paper, I argue that multilingual sentence embedding (MSE) is an attractive alternative approach to language-independent text representation. To support this argument, I evaluate MSE for cross-lingual supervised text classification. Specifically, I assess how reliably MSE-based classifiers …
Measuring and Understanding Parties’ Anti-elite Strategies
Detecting Group Mentions in Political Rhetoric A Supervised Learning Approach
Politicians appeal to social groups to court their electoral support. However, quantifying which groups politicians refer to, claim to represent, or address in their public communication presents researchers with challenges. We propose a supervised learning approach for extracting group mentions from political texts. We first collect human annotations to determine the passages of a text that refer to social groups. We then fine-tune a transformer…
Cross-Lingual Classification of Political Texts Using Multilingual Sentence Embeddings
Established approaches to analyze multilingual text corpora require either a duplication of analysts’ efforts or high-quality machine translation (MT). In this paper, I argue that multilingual sentence embedding (MSE) is an attractive alternative approach to language-independent text representation. To support this argument, I evaluate MSE for cross-lingual supervised text classification. Specifically, I assess how reliably MSE-based classifiers …
Measuring and Understanding Parties’ Anti-elite Strategies
Detecting Group Mentions in Political Rhetoric A Supervised Learning Approach
Politicians appeal to social groups to court their electoral support. However, quantifying which groups politicians refer to, claim to represent, or address in their public communication presents researchers with challenges. We propose a supervised learning approach for extracting group mentions from political texts. We first collect human annotations to determine the passages of a text that refer to social groups. We then fine-tune a transformer…
Attributes, abstractions, and combinations
Research increasingly examines which social groups political actors refer to. Yet, existing approaches typically inherit classifications shaped by demand-side perspectives or conflate how groups are defined with how they are framed. We propose a novel, attribute-centred taxonomy of social group references that classifies groups by the attributes political actors invoke, organises these attributes along nested levels of abstraction, and captures a…
Validating open-source machine translation for quantitative text analysis
Machine translation (MT) is an essential tool in many multilingual computational text analysis applications. However, relying on commercial services like Google Translate or DeepL limits reproducibility and can be expensive. This paper assesses the viability of a reproducible, transparent, and affordable alternative: open-source MT models. We ask whether using open-source MT models instead of commercial services substantially changes the measurem…
Computational and Text Analysis Methods (4 works) · Politics (3 works) · Artificial Intelligence (2 works) · Computer Science (2 works) · Law (2 works) · Law (2 works) · Machine translation (2 works) · Natural language processing (2 works) · Natural Language Processing Techniques (2 works) · Political science (2 works)