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Flag This Row	Text Mining Contemporary Popular Fiction: Natural Language Processing-Derived Themes Across over 1,000 New York Times Bestsellers and Genre Fiction Novels. Lundy, Morgan Master's Thesis, University of South Carolina, 2020. 77 p. (MAI 82(1)(E).) Subjects: CHARACTERIZATION; GENRES; MYSTERY GENRE; POPULAR LITERATURE; ROMANCE GENRE; SCIENCE FICTION; SETTING; TEXT MINING OR DATA MINING; THEMES; YOUNG ADULT LITERATURE Options: Download this record ; E-mail this record

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Text Mining Contemporary Popular Fiction: Natural Language Processing-Derived Themes Across over 1,000 New York Times Bestsellers and Genre Fiction Novels.

Lundy, Morgan

Master's Thesis, University of South Carolina, 2020. 77 p. (MAI 82(1)(E).)

Subjects: CHARACTERIZATION; GENRES; MYSTERY GENRE; POPULAR LITERATURE; ROMANCE GENRE; SCIENCE FICTION; SETTING; TEXT MINING OR DATA MINING; THEMES; YOUNG ADULT LITERATURE

Options: Download this record ; E-mail this record

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