A COMPARATIVE ANALYSIS OF WORD FREQUENCY IN “LOOKING FOR ALASKA” AND “PAPER TOWN” USING VOYANT TOOLS
Abstract
This study aims to compare the word frequency patterns in two novels by John Green, Looking for Alaska and Paper Towns, using Voyant Tools as a corpus analysis platform. The research focuses on identifying the most frequently used words, analyzing cross-document term distribution, exploring collocate patterns, and interpreting thematic implications based on the lexical data. Both novels were selected due to their thematic similarities and their popularity among young adult readers, making them suitable candidates for comparative corpus analysis. Data were collected through digital text processing via Voyant Tools, which produced visualizations in the form of Cirrus (word cloud), Trends graph, Document Terms table, and Collocates table. The analysis was conducted systematically by examining each visualization to identify recurring lexical patterns across both texts. Results show that the word "said" dominates both novels with relative frequencies of 8,856 and 7,960 respectively, indicating a strong reliance on dialogue as a narrative device. Character-specific terms such as "colonel," "alaska," "ben," "margo," and "radar" reflect distinct character configurations in each novel. These findings demonstrate how corpus-based tools like Voyant Tools can provide meaningful quantitative insights into literary texts, complementing qualitative literary analysis and opening new possibilities for computational approaches to literary studies.
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