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Dr. Matthew Jockers is a prominent scholar in the field of digital humanities and computational literary analysis. He is known for his work applying data-driven methods to the study of literature. Jockers has authored books including The Bestseller Code (with Jodie Archer), which uses algorithms and data analysis to explore what makes a book a bestseller, and Text Analysis with R (with Rosamond Thalken), an instructional textbook now in its second edition.[1] He is also the author of Macroanalysis: Digital Methods and Literary History, which applies computational techniques to large-scale literary analysis. Jockers' work often involves the use of statistical and computational methods to uncover patterns and trends in large corpora of texts, contributing to the emerging field of literary data science.[2]
Macroanalysis influenced a quantitative turn in literary studies by introducing and popularizing the use of computational and statistical methods for analyzing literature on a large scale.[3] The book encouraged literary scholars to move beyond the close reading of individual texts to the analysis of large corpora of texts. This shift allowed for the identification of broad patterns, trends, and themes across vast collections of literature that would be impossible to discern through traditional methods. Jockers's work bridged the gap between data science and literary studies, demonstrating how computational techniques like text mining, topic modeling, and sentiment analysis could be applied to literary texts. This interdisciplinary approach helped inspire a new generation of digital humanities scholars applying quantitative methods to uncover new insights into the evolution of literary genres, themes, and styles over time. Jockers analysis of thousands of texts provided empirical evidence for literary trends and shifts that had previously been based on more subjective interpretations. Macroanalysis played a crucial role in legitimizing and expanding the field of digital humanities. It demonstrated the value and potential of digital methods in humanities research, leading to increased funding, resources, and academic programs dedicated to this area.
In addition to his notable books, Matthew Jockers is known for key contributions to stylometry and authorship attribution where he has conducted research using machine learning methods to attribute authorship of texts based on stylistic features. His work in this area included a controversial study of the Spalding–Rigdon theory of Book of Mormon authorship.
Beyond his scholarly work, Jockers co-founded the Stanford Literary Lab with Franco Moretti,[4] an initiative that focuses on computational approaches to literary history. The lab supports research that combines literary studies with quantitative methods. Jockers later founded a similar lab at the University of Nebraska[5] where he later moved into academic administration as Associate Dean of Research and Partnerships. Jockers then moved to Washington State University where he was appointed Dean of the College of Arts and Sciences in 2018.[6]
According to his web site, Jockers left academia in 2021 for a position as a distinguished scientist and Senior Research Manager at Apple.[7]
References
edit- ^ Text Analysis with R. Quantitative Methods in the Humanities and Social Sciences. 2020. doi:10.1007/978-3-030-39643-5. ISBN 978-3-030-39642-8.
- ^ Jockers, Matthew L. (2013). Macroanalysis: Digital Methods and Literary History. University of Illinois Press. ISBN 978-0-252-03752-8. JSTOR 10.5406/j.ctt2jcc3m.
- ^ "An Impossible Number of Books: Matthew L. Jockers's "Macroanalysis"". Los Angeles Review of Books. 2013-08-16. Retrieved 2024-07-30.
- ^ Perry, Mark (May 28, 2010). "The Humanities Go Google". Chronicle of Higher Education. Retrieved July 30, 2024.
{{cite news}}: CS1 maint: url-status (link) - ^ "'Lit Lab' project collects digital Cather insights | Nebraska Today". news.unl.edu. Retrieved 2024-07-30.
- ^ "Associate Dean Jockers accepts new position as dean at WSU | College of Arts and Sciences". cas.unl.edu. 2018-05-29. Retrieved 2024-07-30.
- ^ "Matthew L. Jockers". Retrieved 2024-07-30.
External links
edit- "bn:9781250088277 - Search Results". search.worldcat.org. Retrieved 2024-07-30.
- "ORCID". orcid.org. Retrieved 2024-07-30.
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