Abstract
AbstractVideo game users have shown strong interests in having subject metadata to find games. However, creating and maintaining subject metadata is costly and difficult. This study explores the utility of an automated approach for generating subject metadata for video games, focusing on plot and narrative. By comparing two methods to analyze the reviews—qualitative analysis conducted by a human researcher vs. automated text analysis using topic modeling—the researchers investigate if an automated method can generate subject terms that are comparable to the ones generated by qualitative analysis. Findings suggest that even with a smaller set of sample dataset, qualitative analysis could create a better set of terms than automated text analysis. However, terms generated from the automated text analysis indicate that its capability to retrieve themes of the video game may be useful in future libraries.
Published Version
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