The purpose of this study is to examine trends in research on James Joyce¡¯s work while identifying the characteristics of keywords between two periods (2003-2012 and 2013-2022) and relations among the research keywords. In order to achieve the research goal, the current study conducted a keyword network analysis of the articles published in James Joyce Journal for 20 years. The data were collected using a Biblio data collector, and the English titles, keywords, and abstracts of a total of 283 papers were analyzed using the data-mining software, Netminer4. Then, the data were divided by time period, and the frequency of occurrence of keywords was analyzed and visualized as a word cloud. In addition, in order to identify the relationship between keywords, the analysis was conducted based on the degree centrality, closeness centrality, and betweenness centrality. The results showed that first, the most studied work in the last 20 years is Ulysses, followed by Dubliners and Finnegans Wake. Relatively little research has been done on A Portrait of the Artist as a Young Man. Next, unlike the 2003-2012 period, ¡®paralysis¡¯ and ¡®epiphany¡¯, the most critical terms used to describe Dubliners, appeared more often in the 2013-2022 period. Moreover, the results of the centrality analysis revealed that in the 2003-2012 period, the words ¡®Ulysses¡¯, ¡®Ireland¡¯, and ¡®Stephen¡¯ were found to play the most central role, and in the 2013-2022 period, the words ¡®character¡¯, ¡®Dubliners¡¯, and ¡®Ulysses¡¯ played the most central role. Interestingly, the word ¡®character¡¯, which appeared in a similarly high frequency in both periods, showed relatively weak centrality in the former period, but showed the highest centrality in the latter period. Finally, the word ¡®Ireland¡¯ was ranked the second highest in centrality between the 2003-2012 period; however, it showed remarkably low centrality in the 2013-2022 period. This study is meaningful in that, unlike the previous analysis method, it examined the research trends of James Joyce¡¯s texts through a keyword network analysis. |