Automatic translation, context, and supervised learning in comparative politics
Dados Bibliográficos
| ID | 12972134 |
|---|---|
| Autores | Michael Courtney (0000-0002-9790-6401), Michael Breen (0000-0002-5857-9938, Dublin City University, autor correspondente), Iain Mcmenamin (0000-0002-1704-390X), Gemma McNulty |
| Ano | 2020 |
| Volume | 17 |
| Fascículo | 3 |
| Páginas | 208-217 |
| Data de publicação | 2020-02-19 |
| Peer Reviewed | Sim |
| Open Access | Não |
| Tipo | ARTICLE |
| Periódico | Journal of Information Technology & Politics (JOURNAL) |
| Identificadores do periódico | ISSN: 1933-169X • E-ISSN: 1933-1681 |
| Editora | Routledge (PUBLISHER • GB) |
| DOI | 10.1080/19331681.2020.1731245 |
| OpenAlex | W3006851997 |
| Idioma | EN |
| Citações recebidas | 14 |
| Referências citadas | 21 |
This paper proves that automatic translation of multilingual newspaper documents deters neither human nor computer classification of political concepts. We show how theory-driven coding of newspaper text can be automated in several languages by monolingual researchers. Supervised machine learning is successfully applied to text in English from British, Spanish, and German sources. The paper has three main findings. First, results from human coding directly in a foreign language do not differ from coding computer-translated text. Second, humans can code translated text as well as they can code untranslated prose in their mother tongue. Third, machine learning based on translated Spanish and German training sets can reproduce human coding as accurately as a system learning from English training sets
Coding (social sciences · Foreign language · German · Linguistics · Machine translation · Natural language processing · Newspaper · Sociology · Computational and Text Analysis Methods · Computer Science · Media Influence and Politics · Social Media and Politics · Artificial Intelligence
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| Obras citantes distintas | 14 |
|---|---|
| Citações por ano | 2,33 |
| Intervalo de citações | 2020 - 2026 (7) |
| Velocidade de citação | current |
| Altamente citado | Não |
| Tipos de citação | Neutras: 13 |