Network Text Analysis Framework for Mapping Research Trends: A Neural Architecture Search Case Study

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F25%3A00638738" target="_blank" >RIV/67985807:_____/25:00638738 - isvavai.cz</a>

Result on the web

<a href="https://ceur-ws.org/Vol-4092/paper4.pdf" target="_blank" >https://ceur-ws.org/Vol-4092/paper4.pdf</a>

DOI - Digital Object Identifier

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Result language

angličtina

Original language name

Network Text Analysis Framework for Mapping Research Trends: A Neural Architecture Search Case Study

Original language description

Understanding the evolution of research trends is critical for navigating rapidly developing scientific literature. Large Language Models (LLMs) offer powerful tools for analysing scientific texts, enabling the extraction of key concepts and the construction of semantic networks. These capabilities can support the study of emerging ideas and research trends through graph-based representations. In this paper, we present a network-based text analysis framework designed to map the evolution of scientific knowledge. Our goal is to extract conceptual structures from research papers and construct graphs that represent both the occurrence of terms and their interrelationships. The integration of temporal information allows us to track the emergence and transformation of research themes. We demonstrate this framework using a case study on Neural Architecture Search (NAS) field, a fast-growing subfield in machine learning focused on the automated design of neural networks. Using data from ArXiv combined with metadata and citation records from OpenAlex, we construct and analyse graphs of keywords and articles. This allows us to reveal the dynamics of the NAS research landscape and highlight methodological trends and conceptual shifts.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

<a href="/en/project/EH23_025%2F0008711" target="_blank" >EH23_025/0008711: Knowledge in the Age of Distrust</a><br>

Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2025

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

Proceedings of the 25th Conference Information Technologies – Applications and Theory (ITAT 2025)

ISBN

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ISSN

1613-0073

e-ISSN

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Number of pages

8

Pages from-to

58-68

Publisher name

Technical University & CreateSpace Independent Publishing

Place of publication

Aachen

Event location

Telgárt

Event date

Sep 26, 2025

Type of event by nationality

EUR - Evropská akce

UT code for WoS article

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