Social Reading in the Digital Age
UC Los Angeles
The rise of online platforms for buying and discussing books such as Amazon and Goodreads opens up new possibilities for reception studies in the twenty-first century. These platforms allow unprecedented freedom for readers to preview and discuss books, however they also exercise unprecedented control over which books readers buy and how they respond to them. Online reading platforms are built on algorithms with implicit assumptions that at times imitate, but often differ from the conventions of literary scholarship. This dissertation interrogates those algorithms, using computational methods including machine learning, sentiment analysis, and topic modeling to analyze online book reviews in order to find moments when literary and corporate perspectives on contemporary reading can inform each other. A focus on the algorithmic logic of book publications allows this project not only to critique the ways companies sell and recommend books in the twenty-first century, but to make room for improvements to these algorithms in order to improve both accuracy and theoretical sophistication. This dissertation forms the basis for re-imagining literary scholarship in the digital age by taking into account the online platforms through which so much of reading is now mediated.