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УДК 519.17
АНАЛИЗ ИСТОРИЧЕСКИХ СОЦИАЛЬНЫХ СЕТЕЙ ДЛЯ ИЗУЧЕНИЯ ИСТОРИИ
АРКТИКИ
Е.В . Храпунова, С. В. Ефремова, Е.В. Бурдина Научный руководитель - А.Е. Гончаров
Сибирский государственный университет науки и технологий имени академика М. Ф. Решетнева Российская Федерация, 660037, г. Красноярск, просп. им. газ. «Красноярский рабочий», 31
Анализ исторических социальных сетей является перспективным методом для проведения исторических исследований, в части определения комплекса взаимосвязей между отдельными событиями, личностями, а также историческими документами. В настоящей работе предложен метод использования этого инструмента для изучения истории освоения Арктики.
Ключевые слова: анализ исторических (социальных) сетей, статистические методы, история Арктики, архивные данные, сетевой граф, гиперграф
HISTORICAL NETWORK ANALYSIS FOR ARCTIC HISTORY
E.V. Khrapunova, S.V. Efremova, E.V. Вигёта Scientific supervisor - A.E. Goncharov
Reshetnev Siberian State University of Science and Technology 31 Krasnoiarskii Rabochii Prospekt, Krasnoyarsk, 660037, Russian Federation
Historical network analysis is a moderately recent tool for conducting various historical research enabling scholars to establish patters and relations between, seemingly, random historical events, individuals, and historical sources. In this paper, the authors propose implementing this method for studying the history of Arctic exploration.
Keywords: historical network analysis, statistical methods, Arctic history, network graph, hypergraph
Social network analysis (SNA) has been successfully applied for investigating various sociological issues since the late 1980s [1]. Advances in this method made it tempting to use in historical research, which effectively, has the same scope as sociology but in a historical context. The main problem in extrapolating SNA to historical events is the incompleteness of historical records [1], thereby making it difficult to construct patterns and connections between various historical events, actors, and documents. During the last decade, however, there have been a number of important projects that have spearheaded the application of SNA for historical research. Among these is a University of California Berkley project based on prosopography [2]. Prosopography investigates similar characteristics of individuals within a common social group, and, as such, allows reconstructing the lives of ordinary people based on the group in which they lived. The result of such research is a graph (Fig. 1) visualizing an array of historical data, such as names, family relations, the distribution of ideas, etc. The research team from Berkley focused their attention on the ancient history of Mesopotamia, when historical records mentioning individuals are extremely rare. This makes it extremely difficult to investigate the lives of ordinary people using traditional historical methods, thereby requiring novel interdisciplinary approaches including those based on applied mathematics and systems analysis.
Актуальные проблемы авиации и космонавтики - 2021. Том 2
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Fig. 1. Network graph illustrating a prosopographic social network (source: [2]).
Another project worth mentioning is the Mapping of the Republic of Letters launched by Stanford University. Visualizing the spread of philosophical, political, and scientific ideas during the Renaissance and Enlightenment, this project is based on personal correspondence between various European and American thinkers of those ages [3]. The incorporation of a massive data corpus of letters into a unified scheme is especially important as it provides further perspectives for similar studies into the correspondence between various historical characters and institutions.
Despite the advances of these and other projects into the application of SNA for historical research, it should be said that discipline continues to remain an obscure method rather than becoming an independent auxiliary science of history. The majority of projects in this field are staged by Western universities and have had so far little impact on, for instance, Russian historical studies [4]. Besides, even in such projects it has demonstrated little superiority over the
However, it should be argued that this method has great potential for analyzing and structuring large historical data from modern history (especially, 20th century history). One area for applying this method is for studying 20th century Arctic history. For instance, a one-day online survey of the records of the State Archive of the Krasnoiarskii krai (GAKK) (Krasnoyarsk, Russia) revealed over 3,000 files related to Arctic history produced between 1917 and 1960 (Fig. 2). At the same time, there were fewer than twenty relevant documents of the 19th century.
Archival documents (GAKK). 1917-1960
Cartographic data
Personal records
Official documents
Economic data
Fig. 2. Diagram illustrating the types of archival documents at the GAKK.
Obviously, hundreds of hours will be needed to process this immense amount of data. Furthermore, after it has been studied and systematized, it will require even more time to compile this data into a substantial historical paper, since the researcher will have to memorize and record countless factual evidence, such as dates, names, and events and be able to interpret them through series of patterns. The need for a functioning graphic visualizing of this evidence is thereby evident. With separate nuggets of information acting as nodes, it is possible to interconnect nodes and clusters into graphs of various complexities, including hypergraphs, such as the geographic map-based graphs proposing network analyses of historical correspondence (Fig. 3.).
Fig. 3. Network analysis of 38,000 historical letters by Lab1100 [5].
A proposed functional tool for building historical networks is nodegoat (https://nodegoat.net/). It is planned that in the nearest future, a similar network of archival sources on the history of the Arctic from the GAKK will be built by our team.
Библиографические ссылки
1. Wetherell C. Historical social network analysis // International Review of Social History. 1998. N 43(S6). P. 125-144. doi:10.1017/S0020859000115123
2. Social Networks from History. URL: https://matrix.berkeley.edu/research-article/social-networks-history/ (дата обращения: 03.03.2021)
3. Edelstein D., Findlen P., Ceserani G., Winterer C., Coleman N. Historical research in a digital age: reflections from the Mapping the Republic of Letters Project // The American Historical Review. 2017. N 122. P. 400-424. doi: 10.1093/ahr/122.2.400.
4. Быстрицкий Н.И. Исследования сетей в исторической науке // Исторический журнал: научные исследования. 2017. N 3. URL: https://cyberleninka.ru/article/n/issledovaniya-setey-v-istoricheskoy-nauke (дата обращения: 26.05.2021).
5. Network Analysis of 38.000 Historical Letters. URL: https://lab1100.com/update.p/99.m/31/network-analysis-of-38000-historical-letters (дата обращения: 03.03.2021).
© Храпунова Е.В., Ефремова С. В., Бурдина Е.В., 2021
