For this lab, I studied the first chapter of Jacob’s Room by Virginia Woolf. Each of the nodes represents a character in the chapter while the attribute represents their gender (1 is a male and 2 is a female), because gender is a large part of the novel as a whole. The edges show which characters conversed within the chapter and the graph is a visual representation of the table drawn above.
Jacob’s Room is a novel that balances many different themes in a stream of consciousness narrative, and while Jacob is technically the main character, it wasn’t until I graphed the nodes that I realized how important his mother is in the beginning of the novel. Betty Flanders plays a role in shaping him as a person and is also the only woman who Jacob forms a substantial relationship with that is relatively free of dysfunction and psychological issues. Chapter one is the earliest we see Jacob in his lifetime, so tracking his conversations as a young boy could lead to further discovery about his life as a young adult before his untimely death in the war.
Social network analysis in literary studies can be very advantageous for scholars and students alike when used correctly. In the perfect setting, a work is chosen that can be easily visualized while also offering insight into the dynamics of the piece. However, one interesting piece of this tool is when you map only dialogue like I did with Jacob’s Room. While the dialogue is important, if I had instead mapped how many times a character was mentioned in someone’s thoughts, the Jacob bubble would be huge and the other characters would be not only nonessential but hardly even present. In any piece by a stream of consciousness author like Virginia Woolf, the thoughts that are present are far more important than any dialogue that happens between the characters. So, while the mapping of the dialogue between the characters in the first chapter that I mapped is interesting to note, what is more interesting is whatever could not be represented visually–internal mentions in someones thoughts–that offer a potential flaw of social network analysis.
Ultimately, network analysis can help researchers in literary studies evaluate relationships between characters. This method of textual analysis offers a great deal of room to explore a novel and its inner workings. Instead of aiming to derive meaning like a close reading would do, we can now look further outside the box and make greater claims based on true evidence rather than simply observation or interpretation. For a discipline like humanities that hinges upon personal interpretation, inviting a research process like this takes a page out of the science handbook and forces literary scholars to look at true evidence. For example, who is talking the most and to whom are they talking to can be a valuable question to ask and can be found through this method. The character interactions don’t define a piece of literature, but they can help point a reader or a researcher in the direction that they hadn’t previously considered. Textual analysis can help us move beyond traditional research methods and improve our understandings of authors and their work.