# Empirical Analysis of Parallel Corpora and In-Depth Analysis Using LIWC
## 3 Analyzing the AI Hub Corpus Using LIWC
### Korean-English Domain-Specialized Parallel Corpus  
**Corpus Description**. The Korean-English Domain-Specialized Parallel Corpus ([[https://aihub.or.kr/aidata/7974](https://aihub.or.kr/aidata/7974)]([https://aihub.or.kr/aidata/7974](https://aihub.or.kr/aidata/7974)), accessed on 25 May 2022) provides various parallel corpora specializing in several domains. This corpus was released in 2021, and three companies cooperated in its construction: Saltlux partners, Flitto, and Evertran.  
The corresponding corpus consists of 1.5M sentence pairs, including 250K instances of medical/health data, 200K instances of financial/stock market data, 100K instances of parent-notices data, 200K instances of international sport events data, and 100K instances of IT technology data, 200K instances of festival event content data, 150K judicial precedents, and 200K instances of data on traditional culture/food. The percentage of the domain data within the entire corpus is shown in Figure 2.  
**Corpus Analysis**. This corpus was released separately into training and validation datasets, and Table 2 shows the LIWC results of each dataset. The differences of the linguistic features between the training and validation datasets are generally less than 0.1%. Although there are exceptional differences in some summary-language variables, such as 'clout', which means confidence, and 'authentic', which means authenticity, there are rarely any differences in these features because the differences are at approximately 1%. Therefore we can conclude that the training and validation datasets are released in balance.  
In morphological analysis, there are generally similar results to those of Section 3.2. However, impersonal pronouns are used twice as much as personal pronouns. Although  
Figure 2: Data-domain statistics of the Korean–English Domain-Specialized Parallel Corpus.  
all the results show that the use of personal pronouns is low, \"i\" and \"you\" show the lowest results in other corpora.  
Focusing on the syntactic category, 'analytic', which represents analytic thinking in text, is highest in four summary language variables. The length of the sentences is the longest, and 'commas' is the most frequently used in all the Korean-English corpora we analyzed. This is because there are many long sentences with several phrases explaining the domain-specialized concepts in such corpora. Time orientation is still the highest in the present and the lowest in the future. However, the difference between the present and the past tense is smallest in all corpora because the data contain past cases, such as judicial precedents and financial/stock market data.  
Additionally, in semantics, the biological process category has the highest prevalence in the entire corpus. In this category, 'health/illness (health)' is especially high because this corpus contains several domains that include both medical and international sport data. The results of'money (money)' and 'leisure activities (leisure)' in the personal concerns category prove that there are international sports data and financial/stock market data in this corpus.  
In the results of the sentimental analysis, 'posemo' appears twice as much as 'negamo'. Additionally, the use of words representing sentiments is 7% lower than that presented in Section 3.2. Finally, male referents and female referents of this corpus allow for noticing gender bias because male referents are two times more than female referents unlike other corpora.