JSTOR TopicGraph

Folk Devils and Moral Panics: The Creation of the Mods and Rockers - JSTOR TopicGraph

Our group tried out JSTOR Labs’ “TopicGraph” Beta Version, which aims to help you “understand at a glance the topics covered in a book, then jump straight to pages about topics you’re researching.”

TopicGraph either provides a range of books from a multitude of academic disciplines for users to choose from, or allows users to upload a PDF of a document already in their possession. We uploaded a book by Stanley Cohen written in the 1960s, titled “Folk Devils and Moral Panics: The Creation of the Mods and Rockers.” For context, this book seeks to explain the vilifying stereotyping of certain groups of people. It highlights the phenomena of moral panics and how the media creates scapegoats out of these people, the folk devils, to shift the blame on them for crimes and social upheavals.

This is a helpful resource to understand the overarching topics within a book or paper at a glance, and allows users to actually dive into the pages of the book itself. The interface is easy to visually digest and navigate, and the extracted information accurately portrays the themes and vocabulary of the text we imported. That being said, this would be a great “first look” when deciding whether a source might be valuable in the scope of one’s research, getting a brief synopsis before reading the entire source, and even finding a quote that uses a specific and relevant term, but it in no way is a substitute for reading the actual material. It merely extracts information; it does not infer anything or make assumptions, but rather conveys the general “identity” of whatever source you uploaded. It would be interesting for JSTOR to take this tool further with machine learning/linguistics analysis by potentially attempting to interpret the tone of the writing, the arguments the author is making, and even the historical context behind the writing and publication of the source. These kinds of interpretations would elevate this tool from one that naively extracts information to a helpful tool that helps users understand the complexity and nature of the text they are attempting to learn about.