인문 “스몰 데이터” 연구 방법론과 사례 연구: 19세기말 영국 정기간행물 비평 담론 – 주간지 『런던』을 중심으로

Abstract

This paper is a “small data” study of the British critical weekly London (1877 - 1879). Small data is publicly available machine-readable data that has been assigned meaning by subject matter experts. London was a critical journal published by W. E. Henley (1849-1903), a leading critic of British literature at the end of the 19th century, and his circle. The hypothesis of this paper is that the three distinct sub-sections in the London’s literary section entitled “Bohemia” were organized with different logics, which produced the hierarchy of the works covered in the section. To explore this, this paper utilizes digital tools to perform statistical analysis and text mining. First, a basic statistical analysis of “Bohemia” reveals that London paid special attention to novel criticism; second, a morphological analysis extracts and compares nouns and adjectives that occur with high frequency in each sub-section. The findings highlight the significance of the term “genuine,” which relates to masculine attributes of authorship. Third, I perform cluster analysis and topic modeling based on LDA on all articles in “Bohemia.” The results show that mechanical article type and topic classifications do not correspond to the results of London’s own classification practice. However, this discrepancy allows us an “alien reading” that digital analysis offers: a discursive experience not confined to the critical projects of the Henley Circle.