# Empirical Analysis of Parallel Corpora and In-Depth Analysis Using LIWC
## 3 Analyzing the AI Hub Corpus Using LIWC
### Korean-English Parallel Corpus (Technology)  
**Corpus Description**. AI Hub released the technology-science domain-specialized Korean-English translation corpus ([[https://aihub.or.kr/aidata/30719](https://aihub.or.kr/aidata/30719)]([https://aihub.or.kr/aidata/30719](https://aihub.or.kr/aidata/30719)), accessed on 25 May 2022) in 2021 through the cooperation of Twigfarm ([[https://twigfarm.net/](https://twigfarm.net/)]([https://twigfarm.net/](https://twigfarm.net/)), accessed on 25 May 2022), Lexcode ([[https://lexcode.co.kr/](https://lexcode.co.kr/)]([https://lexcode.co.kr/](https://lexcode.co.kr/)), accessed on 25 May 2022), Naver ([[https://www.naver.com](https://www.naver.com)]([https://www.naver.com](https://www.naver.com)), accessed on 25 May 2022), the Korean telecommunications technology association (TTA) ([[https://www.tta.or.kr/](https://www.tta.or.kr/)]([https://www.tta.or.kr/](https://www.tta.or.kr/)), accessed on 25 May 2022), and the Fun & Joy company (FNJ) ([[http://www.fnj.or.kr/home/index.html](http://www.fnj.or.kr/home/index.html)]([http://www.fnj.or.kr/home/index.html](http://www.fnj.or.kr/home/index.html)), accessed on 25 May 2022). The corresponding corpus was constructed for the support of ICT companies with respect to the translation of technical documents or product localization. The number of sentence pairs in the entire corpus is 1.5M, which comprises five domains, as shown in Figure 3: 350K instances of ICT domain data, 150K instances of electricity domain data, 150K instances of electronic domain data, 350K instances of mechanical domain data, and 500K instances of medical domain data. For the construction of the high-quality corpus, expert-level revision by ICT professionals and several professors in translation fields was conducted after the initial corpus was compiled using a computer system. In this study, we partially leveraged 788K sentence pairs (ICT (35.2%), mechanic (31.2%), electricity (13.8%), electronic (11.2%), and medical (8.6%)) because all the data is yet to be released. **Corpus Analysis**. The entire corpus comprises training and validation datasets, and the LIWC results are shown in Table 3.  
The LIWC results show that there exist small differences between the training and validation datasets in terms of each feature value. We can also establish that the corresponding corpus contains more adverbs than other parallel corpora, and few personal pronouns have been used to the extent that impersonal pronouns ('ipron') have been used approximately 10 times more than personal pronouns. This allows us to identify the characteristics of the corpus that describe technology and phenomena compared to the corpora of other fields that explore people and culture. Because the 'Sixltr' rate is relatively high, whereas 'WPS' is low, we can infer that short sentences, each of which consist long words, are mainly contained in the corpus. Furthermore, the corpus shows low 'authentic' and emotional tone ('tone') rates. This indicates that by considering the characteristics of the technology domain, the representationsof each sentence are concise. The present tense appears more frequently than the past or future tenses, thereby supporting the attributes of the technology domain that are mainly targeted to describe current technology, future complementary points, and expectations. Compared to other corpora, the prevalence of the drive category, which represents the motivation of a sentence, is relatively low, whereas the biological processes category remains the most frequent. These results are contrary to those of the social domain corpus, which reflects the characteristics of the corresponding corpus. The ratio of the conventional process to that of the perceptual process category was also the highest throughout all the corpora. Therefore, it can be confirmed that the characteristics of articles in the technology domain are presented in a manner that describes perceptions and cognitive processes, such as 'insight', 'causation', and 'certainty', about technology.