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Abstract
This research presents an alternative approach for applying the text analysis program, Linguistic Inquiry and Word Count (LIWC) to non-English text: using machine translation (MT) to translate the text into English and then apply the English LIWC dictionary, rather than applying a translated LIWC dictionary to the original texts. We evaluate the alternative method using the output from two open-source MT systems and Google Translation on a set of TED Talk subtitle data. The method is tested on three language pairs: Dutch-English, German-English and Spanish-English. Provisionally, MT seems to lead to better results in the three language pairs than language-specific dictionaries.
Original language | English |
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DOIs | |
Publication status | Published - 2020 |
Event | DH Benelux 2020 - Cloud Duration: 03 Jun 2020 → 05 Jun 2020 https://www.universiteitleiden.nl/en/events/2020/06/dhbenelux-leiden-3-5-june-2020 |
Conference
Conference | DH Benelux 2020 |
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Period | 03/06/2020 → 05/06/2020 |
Internet address |
Keywords
- LIWC
- machine translation
- text analysis
- tooling
- digital humanities
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Dive into the research topics of 'Machine Translation as an Alternative to Language-Specific Dictionaries for LIWC'. Together they form a unique fingerprint.Activities
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DH Benelux 2020
P. Boot (Participant)
03 Jun 2020 → 05 Jun 2020Activity: Participating in or organising an event › Conference › Academic