Topic Modeling Russian History

Oiva, Mila

doi:10.1007/978-3-030-42855-6_24

Cited by 2 publications

(1 citation statement)

References 11 publications

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“…Использовать тематическое моделирование как инструмент генерации гипотез, а не для получения окончательных выводов. Как показали исследования [1,8],…”

Section: рекомендации по применению тематического моделирования в ист...unclassified

Artificial Intelligence in Historical Research: Potential and Limits of Effectiveness

Kuznetsov

2023

V International Scientific Conference «mip-v-2023: Modernization, Innovations, Progress»

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The article thoroughly analyzes the strengths and weaknesses of applying artificial intelligence technologies in historical research using the example of topic modeling methods. The use of popular machine learning algorithms such as Latent Dirichlet Allocation (LDA) for analyzing large arrays of textual data is examined in detail. The key advantages of topic modeling are discussed, including the abilities to process large volumes of text, identify hidden thematic structures, and track topic dynamics over time. At the same time, significant limitations of this approach are considered, such as the assumption of topic stability in most models, poor interpretability of results, their instability and strong dependence on parameter settings. This requires a critical attitude towards the results obtained and their careful verification based on the subject knowledge of the researcher. Specific limitations analyzed include the static nature of topics in many models, weak interpretability of results, their instability, and high dependence on parameter settings. Based on the analysis, it is concluded that it is essential to balance artificial intelligence methods with traditional qualitative approaches in the humanities. The article provides concrete recommendations on the application of topic modeling in historical research to maximize the benefits while minimizing the risks.

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Section: рекомендации по применению тематического моделирования в ист...unclassified

Artificial Intelligence in Historical Research: Potential and Limits of Effectiveness

Kuznetsov

2023

V International Scientific Conference «mip-v-2023: Modernization, Innovations, Progress»

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Beyond Topic Modeling: Analyzing Historical Text with Large Language Models

Kuznetsov

2024

Историческая Информатика

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The article explores the potential of large language models in thematic analysis of historical texts, exemplified by the 1849 diary of Vologda gymnasium student Kirill Antonovich Berezkin. This rich source illuminates the everyday life, worldview, and social interactions of a young individual in mid-19th century provincial Russia. The diary offers a multifaceted narrative, capturing cultural events, political contexts, and personal introspections. By meticulously analyzing this text, researchers can reconstruct not just an individual's experiences, but also gain profound insights into the social, cultural, and educational landscape of the era. Employing the Gemini 1.5 Pro model, renowned for processing extensive textual data, the study conducted a comprehensive analysis. The research methodology involved examining the diary both holistically and through monthly segmentation, enabling the identification of nuanced content aspects. The novelty of the approach lies in applying modern large language models to a Russian historical document. The results demonstrated the model's remarkable capability to identify key themes, successfully isolating eight major thematic areas that reflect the gymnasium student's life. Utilizing parallel prompting with a monthly text breakdown revealed specific themes and subtleties that a comprehensive review might have overlooked. The study ultimately validates the effectiveness of large language models in historical source analysis, presenting promising opportunities for automating topic modeling and uncovering hidden patterns in extensive textual datasets. However, the inherently stochastic nature of these models necessitates multiple analyses, careful result interpretation, and critical comparison with traditional historical research methodologies.

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Topic Modeling Russian History

Cited by 2 publications

References 11 publications

Artificial Intelligence in Historical Research: Potential and Limits of Effectiveness

Artificial Intelligence in Historical Research: Potential and Limits of Effectiveness

Beyond Topic Modeling: Analyzing Historical Text with Large Language Models

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