Motivation

This document describes the methodology used for extracting and analyzing data from the Who’s Who of American returned students [Youmei tongxue lu 遊美同學錄] published by Tsing Hua College in 1917 (Tsing Hua College 1917). The purpose is two fold (1) conduct a prosopography of the first generations of US educated Chinese (2) use this study as a test case to design a workflow for the automated extraction and multidimensional analysis of complex historical information from similar sources.

Primary Source

The Who’s Who of American returned students contains the biographies of 401 Chinese individuals who studied in the United States between 1850 and 1917. It was compiled through the initiative of the Tsinghua College Returned Students’ Information Bureau (Liumei xuesheng tongxun chu 留美學生通訊處) established in 1915. However, it is not limited to Tsinghua students, since most of the students biographed had returned by the time Tsinghua College was established in 1909. The directory was constructed by sending questionnaires directly to the students, with the assistance of students’ clubs (Wu Mi 吴宓 1995), 153–55).

Although the rationale for selecting the biographies remains opaque, this book nonetheless represents the most complete information available on the first generations of Chinese students in America. Each biography provides information about the students’ social and geographical background, educational curricula, subsequent professional careers, as well as their family members and sources of funding — information which is generally omitted from most biographical sources. The biographies are presented in both Chinese and English to cater to two distinct groups of readers—Chinese and American—with a dual objective in mind: first, to provide a valuable reference work for the public seeking the services of Western-educated Chinese, and second, to foster mutual understanding among the returned students themselves.This directory represents a milestone in the history of returned students in China since it represents the first attempt to construct the American-returned students (liumei xuesheng 留美學生, or liumei 留美) as a distinct, highly self-conscious social group, united by their shared educational experience in the US.

Several digital avatars of this directory are accessible online, including on Wikisource and Internet Archive. This research relies on the version provided by the Institute of Modern History (IMH) at the Academia Sinica in Taipei, which is available for data mining with HistText (Blouin et al. 2023).

Research Purposes

The study has 3 main directions:

  1. Analyze the social characteristics of the population to build a collective portrait of late Qing-early Republican American returned students
  2. Uncover hidden connections among biographies based on shared affiliations or family ties
  3. Reconstruct career paths to examine social mobility and multigenerationnal patterns of study abroad

Part of this comprehensive research is published in Twentieth-Century China under the title “Reshaping the Chinese Ladder of Success in the Era of Globalization: Family Strategies and Social Mobility of Early American-educated Chinese (1850-1917)” as part of the special issue titled “Rethinking the Study Abroad Movement in Modern China (1850-1950s)” (Armand 2024).

Outline

Given the scope of this research, this documentation comprises several parts based on the type of analysis and method used:

  1. Data extraction and curation (2 scripts, one for each language)
  2. Collective portrait using multivariate and other statistical analyses
  3. Family ties and background using network analysis (igraph) and correspondence analysis (CA) (FactominR)
  4. Affiliation networks using formal networks analysis (igraph)
  5. Career patterns using sequence analysis (TraminR)

Data Extraction

Three main families of tools were used to extract the data, depending on their nature, as outlined below :

  1. Supervised methods such as regular expressions (Regex) or concordance/Keyword in Context (KWIC) were employed for date of arrival and return, source of funding, relatives’ names and occupation, Chinese degrees, special scholarships.
  2. Unsupervised methods, specifically Named Entity Recognition (NER) were employed to extract affiliation data (name of organizations)
  3. Mixed Methods including Question & Answering (Q&A) were employed to extract date and place of birth, complete educational curricula (including relations between degree, discipline, university, and date of graduation) and career data (position name, employer name, date of position taking/ending). The list of questions and the resulting raw outputs are attached for reference in the GitHub repository.


   
FAMILY   OF TOOLS    		   
INFORMATION   RETRIEVED   
   
Question & Answering (Q&A)   
Persons’ names, date and place of birth

Educational curricula, professional career
   
Rule-based    		   
Concordance/KWIC   
Gender, marital status, descendance, relatives’ names & occupations

Date of Arrival and Return in America

Source of Funding, Preparation in China

Academic Degrees & Disciplines

Address in 1917

Pattern Matching
   
Regex   

Named Entity Recognition (NER) 		   
Persons   
Educational Institutions (Schools, Universities)

Employing Institutions (Government, Universities, Companies…)

Clubs and Associations
   
Organizations   
   
Locations   
   
Dates   


For further information on data extraction, please refer to the dedicated documentation.

Datasets

Given its richness and the complexity of information it contains, the data drawn from this source is subdivided into several datasets encompassing its different aspects:

  • main (attribute data, one row for each individual)
  • kinship (relational data, one individual may have multiple rows)
  • education (retrieved with Q&A)
  • career (positions) data (retrieved with Q&A)
  • Supplementary data: affiliations (retrieved with NER), degrees/disciplines, scholarship, early jobs/internships, metadata (e.g., length of biographies).

References

ARMAND, Cécile, 2024. Reshaping the Chinese Ladder of Success in the Era of Globalization: Family Strategies and Social Mobility of Early American-educated Chinese (1850-1917). In : Twentieth-Century China. 2024.
BLOUIN, Baptiste, HENRIOT, Christian et ARMAND, Cécile, 2023. HistText: An Application for leveraging large-scale historical textbases. In : Journal of Data Mining and Digital Humanities [en ligne]. 2023. Vol. 2023. DOI 10.46298/jdmdh.11756. Disponible à l'adresse : https://shs.hal.science/halshs-04178820.
TSING HUA COLLEGE, Peking, 1917. Who’s Who of American Returned Students [Youmei tongxuelu 遊美同學錄]. Peking : Tsing Hua College.
WU MI 吴宓, 1995. Wu Mi zibian nianpu 吴宓自编年谱: 1894-1925. Di 1 ban. Beijing : Sanlian shudian 三联书店. ISBN 978-7-108-00764-3.