Story visualization of novels with multi-theme keyword density analysis
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A new method for visualization of stories in literary works was explored. Our story visualization method consists of two parts: keyword-based statistical analysis for multiple themes and imagery expression of the results for visual understanding. In this study, we focused on novels as the targets, and discussed ways in which complex structures can be simultaneously visualized using multiple themes. The method was applied for the comparison of Charles Dickens’ novels with Shakespeare’s plays in order to identify any existing evidence concerning literal interest created by the overlapping of multiple scenarios in a single story. We also applied the method to non-literary documents such as newspaper articles, and showed that these documents contain simple statistic patterns regarding a given theme, which contrasts with the case involving novels that include the dynamic fluctuation of individual story elements.
KeywordsStory visualization William Shakespeare Charles Dickens Digital text analysis Literary work Keyword detection
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