Machine Translation as an Alternative to Language-Specific Dictionaries for LIWC

TY - CONF

T1 - Machine Translation as an Alternative to Language-Specific Dictionaries for LIWC

AU - Ye, Yuying

AU - Boot, P.

PY - 2020

Y1 - 2020

N2 - 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.

AB - 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.

KW - LIWC

KW - machine translation

KW - text analysis

KW - tooling

KW - digital humanities

U2 - 10.5281/zenodo.3874671

DO - 10.5281/zenodo.3874671

M3 - Paper

T2 - DH Benelux 2020

Y2 - 3 June 2020 through 5 June 2020

ER -