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Articles 1 - 3 of 3
Full-Text Articles in Computational Linguistics
Quantitative Criticism Of Literary Relationships, Joseph P. Dexter, Theodore Katz, Nilesh Tripuraneni, Tathagata Dasgupta, Ajay Kannan, James Brofos, Jorge A. Bonilla Lopez, Lea Schroeder
Quantitative Criticism Of Literary Relationships, Joseph P. Dexter, Theodore Katz, Nilesh Tripuraneni, Tathagata Dasgupta, Ajay Kannan, James Brofos, Jorge A. Bonilla Lopez, Lea Schroeder
Dartmouth Scholarship
Authors often convey meaning by referring to or imitating prior works of literature, a process that creates complex networks of literary relationships (“intertextuality”) and contributes to cultural evolution. In this paper, we use techniques from stylometry and machine learning to address subjective literary critical questions about Latin literature, a corpus marked by an extraordinary concentration of intertextuality. Our work, which we term “quantitative criticism,” focuses on case studies involving two influential Roman authors, the playwright Seneca and the historian Livy. We find that four plays related to but distinct from Seneca’s main writings are differentiated from the rest of the …
Nondescript: A Web Tool To Aid Subversion Of Authorship Attribution, Robin Davis
Nondescript: A Web Tool To Aid Subversion Of Authorship Attribution, Robin Davis
Dissertations, Theses, and Capstone Projects
A person’s writing style is uniquely quantifiable and can serve reliably as a biometric. A writer who wishes to remain anonymous can use a number of privacy technologies but can still be identified simply by the words they choose to use — how frequently they use common words like “of,” for instance. Nondescript is a web tool designed first to identify the user’s writing style in terms of word frequency from a given writing sample and document, then to suggest how the author can change their document to lessen its probability of being attributed to them. While Nondescript does not …
Personal Sense And Idiolect: Combining Authorship Attribution And Opinion Analysis, Polina Panicheva, John Cardiff, Paolo Rosso
Personal Sense And Idiolect: Combining Authorship Attribution And Opinion Analysis, Polina Panicheva, John Cardiff, Paolo Rosso
Conference Papers
Subjectivity analysis and authorship attribution are very popular areas of research. However, work in these two areas has been done separately. We believe that by combining information about subjectivity in texts and authorship, the performance of both tasks can be improved. In the paper a personalized approach to opinion mining is presented, in which the notions of personal sense and idiolect are introduced and used for polarity classification task. The results of applying the personalized approach to opinion mining are presented, confirming that the approach increases the performance of the opinion mining task. Automatic authorship attribution is further applied to …