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Activity Number: 251
Type: Contributed
Date/Time: Monday, August 4, 2014 : 2:00 PM to 3:50 PM
Sponsor: Section on Statistical Learning and Data Mining
Abstract #311149
Title: Webcrawling, Data Mining, Quantitative Content Analysis, and Cluster Analysis, Oh My! Understanding Supernatural Horror Fandom
Author(s): Brenda Osuna*+ and Reagan Rose and Cynthia Vinney
Companies: University of Southern California and University of Southern California and Fielding Graduate University
Keywords: Data mining ; Quantitative Content Analysis ; Cluster Analysis ; Social Media Data ; Webcrawling ; Media Uses and Gratifications

The uses and gratifications approach theorizes that individuals actively choose the media with which they engage in order to fulfill personal psychological needs. The accessibility of unstructured data written by fans of popular culture who connect with one another via social media provides material for us to test this theory. We hypothesized that fans of supernatural horror fiction would have similarities in their psychological profiles. Using a webcrawler program written for this study, we mined data from fan sites related to the supernatural horror genre. Content analysis was then used to quantify words that indicate psychological elements present in the data. We conducted cluster analysis to create psychological profiles of groups of fans. Results imply that psychological data can be used for practical applications such as targeted media marketing campaigns. We suggest further research to determine if fan preferences can be used as an indicator of the psychological states and/or traits that drive the fandom of specific sub-genres.

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