I’M JUST A PERSON

Back in 2018 when I started writing, I felt like I didn’t know anything about or anyone in publishing. Well now it’s 2023 and my debut novel is will be published in June, but I still feel like… I’m just a person. Know what I mean? (If you don’t, keep reading :)

A literary social network

What is this?

One of the most oft repeated pieces of advice for aspiring writers looking for literary agents is to look at the acknowledgements section of novels to see which literary agents represent the writers they admire. From there, the advice goes, just query those agents and, with a bit of work and kismit, one day you’ll be the published author whose acknowledgements people are trawling.

Okay, then!

The graphic above is me taking that advice… too far?

Sure I could have read the acknowledgements, made my list of literary agents and gone about my business, but… why not make it a thing? So, back in 2020, when I was first seeking representation for my novel, I created this social network constructed of the people (and organizations) mentioned in the acknowledgements sections of ~75 novels longlisted for the Center for Fiction First Novel Prize. I wanted to know:

  • do all the writers really know each other (it sure seems like they do on social media)? and

  • do all the writers have fancy degrees and go to fancy residencies (it sure seems like they do on social media)?

Well now it’s 2023 and I worked hard and I wrote a lot and yada yada yada, my debut novel is going to be published in June! So I know quite a few more publishing people today than I used to. Thus, I’ve taken the liberty of situating myself within the literary social network that I created in 2020. I’m the little green bubble labeled “Me.” (If you don’t see me, I might be hiding behind the “William Morris Endeavor” bubble.)

How does it work?

Each node (bubble) in the graph is color coded based on whether the entity is a:

  • debut author

  • agency

  • other organization (e.g. workshop, residency, MFA program)

  • an individual / friend

The bigger the node and the closer the node to the center of the graph the more influential that bubble is within social network. “Influential” here just means that more novelists have mentioned that particular entity in their acknowledgements. So the biggest bubble (Janklow & Nesbit) represents the node in the network that is most influential (i.e. was mentioned by the most novelists.)

You can click on the nodes / bubbles to see what other entities they are connected to. You can also drag the nodes around to see what amount of force they exert on the network. (The more the network moves with the node, the bigger its influence.)

Notes:

  • This is just for fun.

  • The data source: from the text of an author’s acknowledgements, I used a named entity recognition model to extract all of the individuals and organizations that were mentioned. The graphic you see creates a network of all those entities, connecting various authors to other individuals and organizations who are also connected to other authors: a literal literary social network.

  • Click on any bubble to highlight that entity and its connections. As you drag the bubble around you will see both the entities that are directly connected to it, as well as indirect connections, which are the connections of connections. The more an entity moves with another entity the more closely connected those entities are.

  • Tip: you can trace connections by clicking from one highlighted bubble to another if you want to explore more.

  • To return the graphic to its original form, click anywhere in the background. This will deselect whichever bubble was highlighted.

  • The size of the bubble represents the amount influence a particular entity has on the network, with the exception of the authors (red bubbles) which are all the same size.

  • The colors of the bubbles represent the type of entity: an author (red), an individual who an author mentioned in their acknowledgements (pink), an author’s literary agency (dark blue), any other organization an author mentioned in their acknowledgments (light blue), me (green.)

  • There are no named individuals in this graphic, because I figured most people probably don’t want their names on a random chart on the internet. So while there are labels for organizations (light blue) and agencies (dark blue) (and for me!) there are no labels for authors (red) and other individuals (pink) in this graphic. The authors included are a selection of ~80 debut novelists longlisted for the Center for Fiction First Novel Prize. I chose this sample because I, personally, was most interested in a who’s who among debut novelists.

  • There are a number of organizations missing (e.g. artists residencies like Yaddo, MacDowell, etc.) because the Named Entity Recognition model I used doesn’t pick those up. ¯\_(ツ)_/¯