Skip to content

Scientometric Analysis of Research Structure and Trends in Neutrino and Dark Matter Detection: Scientific Mapping and Keyword Co-occurrence Analysis in Web of Science

Oct 2026 · DOAJ (DOAJ: Directory of Open Access Journals)
Dark Matter and Cosmic Phenomena

Abstract

Purpose: Neutrinos and dark matter are two fascinating and mysterious topics in modern physics, with numerous experiments conducted worldwide to study their properties, interactions, and their impact on our understanding of the universe. Neutrino detection is primarily achieved through two methods: charged current interactions and neutral current interactions. Although the scattering cross-section for neutral current interactions is generally smaller than that for charged current interactions, coherent scattering of neutrinos from atomic nuclei can increase the neutral current cross-section by a factor of two to four. This phenomenon has led to the development of many recent experiments utilizing coherent neutrino-nucleus scattering, employing techniques similar to those used in dark matter detection. This study analyzes the co-occurrence of the keywords "neutrino" and "dark matter" in scientific literature, focusing on detection methods to identify research trends and explore interdisciplinary connections between these fields.Methodology: A comprehensive dataset of published articles was extracted from the Web of Science database, and co-occurrence maps were visualized using VOSviewer software to analyze the connections between topics, authors, and countries. The results reveal significant clusters of studies linking neutrino physics and dark matter research, demonstrating increasing collaboration between these fields. These clusters not only reflect growing interest in the intersection of these areas but also point to promising directions for future research that could enhance our understanding of the fundamental components of the universe. In this article, we evaluate trends in scientific literature by examining the relationship between neutrino physics and dark matter research, with a particular focus on detection methods. Using data from the Web of Science database and co-occurrence maps generated in VOSviewer, we address the following research questions: First, what are the frequency and distribution of keyword co-occurrence in scientific articles indexed in the Web of Science database, and how do these patterns reflect the evolution of research topics over time? Second, what are the characteristics of scientific articles in terms of language, country, participating researchers, research areas, and keywords, and how do these factors influence the global research landscape in this field? Third, what clusters and topics emerge from co-occurrence analysis in the Web of Science database, and how do these clusters reflect the interdisciplinary nature of neutrino and dark matter research? Fourth, how have research topics evolved in Web of Science-indexed articles, and what key milestones mark the development of this field? Fifth, what patterns of international collaboration exist in this field based on Web of Science data, and how do these collaborations contribute to advancements in neutrino and dark matter research? To ensure a comprehensive and accurate analysis, a hierarchical tree diagram was created to map the relationships between different branches of research. This diagram, along with existing thesauri and expert input, helped select appropriate keywords. The search strategy employed Boolean operators (AND, OR) across titles, keywords, and abstracts to ensure broad coverage of the literature. This approach allowed us to examine all research activities in this field, from theoretical studies to experimental investigations.Findings: The analysis revealed that between 2010 and 2020, research activity in neutrino and dark matter studies increased significantly. Key topics included neutrino detectors, dark matter detectors, physics beyond the Standard Model, high-energy neutrinos, gravitational waves, and black holes. These subjects represent recent advancements in the field, with a strong emphasis on detection technologies, theoretical developments, and observational methods. The emergence of these topics reflects growing interest in the connection between neutrino physics and dark matter research, as well as advancements in the experimental and theoretical tools available to researchers. Additionally, the study identified seven collaboration clusters among countries, with the largest cluster comprising 19 countries. This cluster represents a strong network of international collaboration, highlighting the global nature of research in this field. In contrast, smaller clusters with fewer members indicate regions with more limited collaborative networks, suggesting opportunities for increased international engagement. These findings underscore the importance of global cooperation in advancing neutrino and dark matter research and the need for continued investment in international partnerships and infrastructure.Conclusion: This study offers a comprehensive overview of research developments in neutrino and dark matter studies. Through bibliometric analysis and co-occurrence mapping, key trends, emerging topics, and patterns of international collaboration have been identified. These findings not only clarify the current state of research but also suggest valuable directions for future investigations that could enhance our understanding of the universe's mysteries. The results highlight the importance of interdisciplinary approaches, international collaboration, and ongoing investment in research infrastructure to address fundamental questions in neutrino physics and dark matter research.

View source

Similar papers

#computer vision Review Sep 2017

Agile Software Development Methods: Review and Analysis

This publication proposes a definition and a classification of agile software development approaches and analyses ten software development methods that can be characterized as being "agile" against the defined criterion.

P. Abrahamsson, O. Salo, Jussi Ronkainen et al. · 727 citations · ⚡54
#small language model Dataset Open access Oct 2026

Socratic guiding questions in synthetic arithmetic data: matched LoRA runs (revision v2)

Supporting data, adapters, predictions and code for the article *Low-Cost LoRA Fine-Tuning of Small Language Models for Multi-Step Arithmetic Reasoning* by Jake O'Grady, Asena Isik Gürhan, Chee Fong Ting and Effirul Ramlan (University of Galway). We generated 20,000 GSM8K-derived arithmetic problems with step-by-step s...

O'Grady, Jake, Gürhan, Asena Isik, Chee, Fong Ting et al. · 465 citations
#computer vision Jun 2008

The impact of agile practices on communication in software development

The study shows that agile practices improve both informal and formal communication, but indicates that, in larger development situations involving multiple external stakeholders, a mismatch of adequate communication mechanisms can sometimes even hinder the communication.

M. Pikkarainen, Jukka Haikara, O. Salo et al. · 401 citations · ⚡48
#machine learning Review Open access Oct 2014

Software development in startup companies: A systematic mapping study

The results indicate that software engineering work practices are chosen opportunistically, adapted and configured to provide value under the constrains imposed by the startup context.

Nicolò Paternoster, Carmine Giardino, M. Unterkalmsteiner et al. · 394 citations · ⚡54

Related blog posts

GPT-Lab Sep 3, 2026

Adaptive AI Agents in Construction Workflows

Adaptive AI agents can help make BIM data more machine-readable by navigating IFC models, interpreting inconsistent information, and mapping it to defined standards. In this blog, Alok Rawat shares findings from a real-world pilot in construction workflows. The post Adaptive AI Agents in Construction Workflows appeared first on GPT-Lab.

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.