@article{ref1,
title="Analysis of football research trends using text network analysis",
journal="PLoS one",
year="2024",
author="Kim, Jongwon",
volume="19",
number="4",
pages="e0299782-e0299782",
abstract="This study was aimed to identify football research trends in various periods. A total of 30,946 football papers were collected from a representative academic database and search engine, the 'Web of Science'. Keyword refinement included filtering nouns, establishing synonyms and thesaurus, and excluding conjunctions, and the Cyram's Netminer 4.0 software was used for network analysis. A centrality analysis was conducted by extracting the words corresponding to the top 2% of the main research topics to obtain the degree and eigenvector centralities. The most frequently mentioned research keywords were injury, performance, and club. Keyword performance showed the highest degree centrality (0.294) and keyword world and cup showed the highest eigenvector centrality (0.710). The keyword with the highest eigenvector degree changed from injury in the 1990s and world in the 2000s to cup since the 2010s. Although various studies on football injuries have been conducted, research on the sport itself has recently been conducted. This study provides fundamental information on football trends from research published over the past 30 years.  Keywords : Soccer; American football   SafetyLit note: The search system excluded articles with text-words American and Gaelic. This presumes that articles about &quot;American football&quot; will contain the word &quot;American&quot; when written by authors in the United States. A cursory examination of the SafetyLit database or thesaurus demonstrates that the vast majority of articles about American football that are written by authors in the USA do not contain the modifier &quot;American &quot;. <p /> <p>Language: en</p>",
language="en",
issn="1932-6203",
doi="10.1371/journal.pone.0299782",
url="http://dx.doi.org/10.1371/journal.pone.0299782"
}