Despite the fact that there are more books published annually than ever before; despite claims that the commercial publishing industry has sacrificed all pretenses of quality to churn out marketable content; despite the increased strength of indie publishers; despite inexplicable successes like Where the Crawdads Sing (unreadable), unlikely self-published blockbusters like Fifty Shades of Grey (unreadable, sometimes funny), and eyebrow-raising flubs like American Dirt (unreadable, racist); despite all of your friends with unfinished manuscripts stashed away in desk drawers; and despite the droves of applicants to your university's MFA program, one fact is certain: it's harder than ever to publish a novel.

A number of critics, myself included, have painted a bleak portrait of commercial publishing as an industry closed off to all but a select few who were privileged enough to attend the right boarding schools, universities, Hamptons cocktail parties hardly promising for the scores of armchair hopefuls working on the next "great American novel" across the country. And yet, thousands of aspiring writers persist, eager to find a way to break into the imposing and opaque industry. Many pursue traditional pathways to publication, whether MFA or NYC, or some combination of talent, sweat, and luck. But others have turned to more creative, more public, and seemingly more accessible means of landing a book deal: the Twitter Pitch Party.

The concept of the Pitch Party is simple, not unlike its televisual analogues American Idol, So You Think You Can Dance, The Great British Baking Show, and countless other reality shows. The next great writer is out there, but she may be an undisciplined raw talent, without access to insider knowledge. He may be unable to quit his day job, or simply suffering a string of bad luck. But with the right opportunity and the right coach, her ideas and his prose could shine. Would-be writers needn't camp out days in advance of an open casting call, awaiting their big break; they simply need a Twitter account. To participate, writers tweet a pitch of their "completed, polished, unpublished" manuscript in 280 characters, using designated hashtags. By clicking the heart icon ("favoriting" a tweet), prospective agents indicate their interest and invite a writer to submit a query and more material.1 What happens after the Pitch Party is up to author and agent. Agents may pass or offer representation; authors may publish quietly or break out.

Regardless of genre, audience age group, or topics of interest, there's bound to be a dedicated Pitch Party. There are general Pitch Parties, Parties for designated genres (such as #KissPitch for writers of romance), and Parties such as #DVPit, designed "exclusively for self-identifying, historically marginalized and underrepresented authors & illustrators."2 #DVPit underscores the key democratizing impulse of the Pitch Party: by opening the traditionally-closed process of querying, Pitch Parties attempt to circumvent the systems of patronage on which the publishing industry relies. Commercial publishing privileges personal networks and connections, replicating structural inequalities; the barriers are very steep for writers of color, queer writers, writers with disabilities, or writers from other historically marginalized groups. Twitter provides an open alternative to a closed industry: anyone stands a chance, or so the promotional materials claim.

But note that well-established agents do not turn to Pitch Parties to find clients. Agents who represent major award-winners, bestsellers, or notable public figures do not, as a rule, accept unsolicited queries. When they scout for clients, they take recommendations from existing clients, go to Iowa or Michigan, or read The New Yorker. But Pitch Parties can be an invaluable source for junior agents who are working to build their lists, or for agents who do not work at big-name agencies in New York or London. Typically, agency follows an apprenticeship model: a young agent begins as an assistant, learning the trade as a first-reader for an established senior agent. She may be given the opportunity to serve as co-agent, and eventually she may be allowed to take on her own clients, usually discovered in her boss's slush pile. If she hustles, finds and signs a promising client, and negotiates an impressive sale, she's on her way. The challenge for any unseasoned agent is convincing an author to sign with her instead of an agent with an established reputation; Pitch Parties provide one alternative, connecting agents who need clients with authors who need their big break. Additionally, there are countless freelance agents, agents who work remotely around the country, agents who are only loosely affiliated with an agency while working largely independently. For these agents, without an illustrious mentor's slush pile to comb, Pitch Parties are especially appealing.

For scholars of the contemporary literary field, Pitch Parties offer yet another, unique appeal: the opportunity to see the process of publication unfold. Just as the Pitch Party purports to make the industry accessible to writers, it also makes the process somewhat more transparent to scholars. Typically, we only learn about literary production after the fact. "The literary field," even when analyzed digitally en masse, is a small fraction of the books that churn through the publishing industry annually. Books that we talk about, let alone write about or assign, are in an even tinier minority, having come to our attention through a complex mechanism of promotion and prestige. If we want to learn about how those books were made, we can turn to archives; an author's papers may contain correspondence with their editor. If we're lucky, an author, editor, or agent might speak with us directly. Still, all of these forms of scholarship occur post-production. The Pitch Party sits at the other end of the timeline: not the Great Unread but the Great Unwritten. These small interactions tweet and favorite constitute the first contact between author and agent, typically a private form of communication negotiated by complex networks of friends-of-friends(-of-friends). These are early ideas, manuscripts still gestating, including some that may never be viable. These tweets index reception as much as potential production, indicating what scores of amateur writers think makes a good, or at least salable, book. The lucky pitches that win favorites reveal what agents think the market might reward; these are the ideas that might be worth taking a risk on, and the books that we might be reading in five yearsif the Pitch Party makes good on its promise.

To answer those two questions what are writers submitting? what are agents looking for? I began following two of the biggest Twitter Pitch Parties: #PitMad (short for Pitch Madness), one component of a larger mentorship contest called Pitch Wars, and #IWSG, a Pitch Party sponsored by the Insecure Writer's Support Group.3 Each of these Pitch Parties lasts for 12 hours, and participants are allowed one pitch per hour, up to three per project. In addition to the Party hashtag, they use pre-assigned hashtags to designate a genre or age group (as in #R for romance or #MG for middle-grade). Hearts are strictly reserved for agents, but there's a definite mutual-retweet ethos. I scraped 5,668 unique pitches from Twitter after the Parties concluded.

The Pitch is a formulaic genre. Participants are encouraged to write pitches that focus on the actions or issues motivating their main character. No world-building, no metacommentary, no big ideas. Pitch Party guides suggest that writers spend their 280 characters on the central question, conflict, or obstacle that their protagonist(s) must wrestle with, face, or overcome. The result is that pitches are formulaic, not unlike the template suggested in the Writer's Market Guide to Literary Agents, 2017: "When [Main Character] encounters [Obstacle], he/she must [Reaction] or else [Stakes]. #MG #PitMad."4 Agent Carly Watters demonstrates: "Girl abducted by rabbit from family picnic to fight war in magical dimension. When put on trial for her life, will she wake up? #PitMad #YA."5 (That's Alice in Wonderland, by the way.)

Participants are encouraged to allow their hashtag abbreviations to do the heavy-lifting of establishing genre hence, #YA. The formulaic nature of the genre allows us to use topic models to make a number of claims about the pitches as a whole. Topic models are a type of computational text analysis that enable us to understand the themes (topics) shared by a group of texts, based on the statistical co-occurrence of individual words. They are useful for working with a large amount of data, and for preliminary, exploratory analysis.6 I built a topic model to understand the general themes and trends of the Pitch Parties. Table 1 shows the top 25 topics that emerged from the entirety of the Pitch Party corpus, with one topic per row and ten words per topic.

Table 1: What Are Aspiring Writers Pitching?
(What Do They Think Makes a Good Book?)

Topic 1leaveturnshomelovestayhidingfriendsheaddecidefriend
Topic 2lifesecretfatherbacktownfamilybrothersecretsdeathmurder
Topic 3findhousespacedetectivemurdermancrewshipghostsclues
Topic 4storywomenamericanpunkfollowromancerockplanslovepart
Topic 5lifedayherohumansavecityhumanstakesgroupsuper
Topic 6earthwantedlifethingssexaliensplanetseekingturnthought
Topic 7dadmombookgreatfindgirlsdogfactfriendsgrandma
Topic 8worldfindslifelearnlovefriendspowermiddlesecretknew
Topic 9fairycursecursedprincessfindillfairytaletownbreakgodmother
Topic 10earthplanetmagicalientimemaxpowerslongdeadwrong
Topic 11findfighttimeyoungtravelvillageworldheartracedeadly
Topic 12treasurebrainfamilyfindgirlyearsmonsterfatherhuntquest
Topic 13yearfarmfindsdaymotherworldsavefamilydayswoods
Topic 14worldmissingprovedeathtowndealsistersetpersonwar
Topic 15deadfindlifefriendhappybackhomesisterbadthought
Topic 16schoolfriendsgirlmakehomerealmotherboymoonkids
Topic 17mantimespeculativekidgoodmeetsmakepocworldownvoices
Topic 18kingyearcheckgamessongqueenwakepowersgamespirit
Topic 19childrenwitchmonsterbloodfathermonsterssavevampiremermaidwar
Topic 20lovelifepastfindfamilyworldsavewomandeathfriends
Topic 21nightbabybearstorychristmasmeetswilddaylearnssanta
Topic 22changetimeworldrevengehardclimatesciencemakelivingstop
Topic 23lovelifefamilytimepastmeetsgirlboyfinddreams
Topic 24killerhusbanddemonslovetrappedescapesupernaturalendworldvictim
Topic 25magicsaveworldwardarkprinceevilpowerdragonkill

Table 1: These are the Top 10 words associated with the Top 25 topics from the entire Pitch Party corpus (5,668 tweets). The individual words per topic are arranged from left-to-right, in decreasing order of probability that each word appears in that topic.

The clearest finding is that writers are invested in genre fiction. Though genre-based hashtags have been cleaned from this data, the majority of these topics adhere to easily-identifiable generic conventions: Topic 6, including "earth," "aliens," and "planet" is a Science Fiction topic. Topic 3, with "detective," "find," "murder," and "clue" is a Mystery topic, though these mysteries may be set in space or on ships. Topic 9, featuring "fairy," "curse," "princess," and "godmother" is a Fairy Tale topic, and Topic 16 screams YA: "school," "friends," "girl". There are a number of fantastic creatures mentioned by name, including "monsters," "dragon," "demons," "mermaid," "ghosts," and yes, "vampire." Indeed, it is hard to separate any of these topics from the genres implied by such specific language.

Though the investment in genre fiction may appear to be a divergence from the tried-and-true pitch formula, the remainder of the pitches appear to follow the Protagonist-Does-Something formula evident in Watters's example. Mythical creatures aside, the topic model reveals investment in familial relationships. It includes forty-eight nouns related to people (excluding nouns relating to mythical creatures, such as "mermaid"). Several of the personal nouns included are general, like "detective," "prince," "person," or "woman," but the majority of the people included imply pitches with family relationships at the center, regardless of the genre. Words related to home or familial relationships appear in around 50% of topics. Most protagonists, then, seem to be facing a central conflict within or related to their families; alternately, writers may be particularly interested in exploring generational difference and belonging in their fiction OK, Boomer: The Novel.

Still, the topic model provides evidence of a focus more on actions than on people, suggesting that these stories are more event-driven than character-driven. These pitches do not waste time with description; there are only nine adjectives in Table 1, including "American," "super," and "deadly." There are very few words that would establish a setting "woods" here, or "town" there. Pitch Party participants seem to have taken the advice on overcoming conflicts to heart, as this model features more verbs (fifty-three) than nouns (forty-eight). Eight topics include the word "find," the most commonly used verb. Indeed, the verbs included in this model are largely epistemological, concerned with learning, understanding, and persuasion ("learn," "know," "prove," "decide"), suggesting that the central conflict or obstacle is the pursuit of knowledge. Though it's not a new phenomenon by any means, it's hardly surprising that, in a moment of national gaslighting, misinformation campaigns, and political propaganda, writers are investigating the basis of truth, knowledge, and facts in their fiction, whatever the genre or target age group. Though a number of these topics are fairly dark (Topics 2, 3, 14, 19, 22, 24, and 25), the verbs "save" and "find" appear with far greater frequency (fifteen times) than "murder" or "kill" (four times). While the books may be darkly suspenseful or paranormal, the pitches appear to be generally more positive, with protagonists overcoming or defeating whatever obstacle they encounter. It would seem that Pitch Party participants are far less interested in exploring the inner psyche of an antihero-as-protagonist, a la Gone Girl, than in retelling mythic encounters of good triumphing over evil.

Whereas Table 1 shows us the entirety of the Twitter slush pile, Table 2 (below) shows us the topics that emerge from only those tweets to which agents responded. This subset includes all tweets that received between 1-4 hearts. Of course, a request for more material is neither an offer of representation nor a book deal. Hearts are merely an expression of interest, a sense that there might be something there. Still, there is a marked difference in the topics proposed by authors and those that piqued the interest of agents.

Table 2: What Are Agents Interested In?
(What Do They Think the Market Might Reward?)

Topic 1backsecretshitdancebookmonstersharethingstownanxiety
Topic 2townhousesmallfamilylongliveslostkillerfriendamerican
Topic 3summerperfectbrokenwomantripdadclassfriendsdoorfamily
Topic 4lifeyearsloveworldagoplacefindlieshistoryborn
Topic 5lovehusbandfindlifefindslatekillwomanfeelingsman
Topic 6friendsfindlifefallrealescapelovedeepdreamsorder
Topic 7lifeescapegoodplandaytimesupposedbandsunanimals
Topic 8schoolyeartreasureislandbearsecretswildperfecttimegroup
Topic 9storyyoungbookdaylovethingsworldfunfriendshipfind
Topic 10findcatbeautyfriendstalesearchpetdaughtermouseforest
Topic 11magicsaveearthplanetfindwarpowershoperacedark
Topic 12fairyfindfightmurderedmanmagicsurviveghostsonface
Topic 13makinghunteradventureschoolfindstartmiddlecivillinesurvive
Topic 14familyhumanfindchangehomeworldbringwarvampirebrother
Topic 15lovecomingbigjobfriendsstaragegoodrealitymeets
Topic 16pastmemoriesenemyrevengefacemysteriousbattledeadnightvictim
Topic 17schoolfindlearnsputkidlearndeathfearsfigurehome
Topic 18savemagicworldprincepowergirldragonwarancientevil
Topic 19deaddeathmurderkillersisterbrotherdetectivetruthprovefamily
Topic 20lifesuperpartagentestrangedwomanfamilybeautifulhighfinds
Topic 21makerulesgivehumanchildchangesciencemoveimaginationfather
Topic 22lifelovefriendschoolsavechooseworldlovesfallsmeets
Topic 23timelifepastworldbackmansecretspaceblackready
Topic 24fathersecretdeathlearngoodkidsdangerjourneydiscoversave
Topic 25familyhomefindsmomdadgirlboyfindlovemakes

Table 2: These are the Top 10 words associated with the Top 25 topics from a subset of the Pitch Party corpusonly those tweets that received between 1-4 Hearts/Favorites (3,782 tweets in total). The individual words per topic are arranged from left-to-right, in decreasing order of probability that each word appears in that topic. Tweets and user accounts were manually spot-checked to ensure that Favorites were from agents; there is very likely some error here.

The major difference between the Writer and Agent models is the relative presence of generic markers. The language that clearly designates a work as a part of a genre in the Writer model fairy, detective, planet, questis largely absent from the Agent model. There are some designated genre fiction topics (14, 18, 19) but this language is not pervasive or even especially specific. Consider, for instance, the case of Science Fiction. In the Agent model, Topic 11 could be a Science Fiction topic, but only "earth" and "planet" distinguish it from a Fantasy topic ("magic," "powers," "dark"). Or Topic 23 could be a Science Fiction topic ("space," "world"), but it might equally be a Time Travel topic ("time," "past," "back"). By contrast, the Writer model includes five Science Fiction-related topics, featuring distinguishing words such as "space" and "aliens." While this certainly suggests that hard science fiction is not especially desirable to prospective agents, this trend holds: agents appear to be less interested than writers in pure genre fiction.7

In fact, the Agent model appears to privilege precisely what the Writer model ignores: description. This model includes twenty-three adjectives, including "small," "broken," "perfect," and "beautiful." The Agent model has forty-seven verbs, somewhat less than the Writer model; five topics contain no verbs at all. These differences suggest that agents place less emphasis on action or conflict than on descriptions of characters and settings, despite claims to the contrary. "Find" is the most common verb in both models, but the Agent model features a different set of epistemological terms: "memories," "secrets," and even "dreams" and "imagination" feature in the Agents model, suggesting a higher level of interiority. Characters are less committed to discovering external fact-finding missions than internal development. Perhaps the most telling turn toward descriptive setting are the number of history words in the Agent model. Topics 4, 16, 18, and 23 are all concerned with the past, including words such as "ago," "history," "ancient." These pitches are located in time, as well as in particular settings or spaces. As a whole, it would seem that the agents are interested in pitches that tend toward the literary.

Perhaps the discrepancy is due to the form of the pitch: high-concept genres are easier to describe in 280-characters, whereas literary fiction (supposedly) resists such neat packaging. Writers of literary fiction may find Pitch Parties ill-suited for their work and self-select out, taking more traditional routes. By contrast, writers of genre fiction, not unlike members of active fan communities, may find more robust support and encouragement online. Or perhaps the discrepancy is due to the conditions of agency as a profession within a larger publishing ecosystem: because the production of literary fiction is restricted, it has the potential to be more prestigious, and is therefore more desirable to represent. Agents may be more likely to respond to literary pitches as an act of position-taking and career strategy.

Here, the hashtags associated with pitches prove illuminating, suggesting both writerly push and agential pull. Literary fiction is not a popular hashtag in Pitch Parties. Very few pitches are explicitly tagged as literary fiction (using #LF or #litfic). In fact, literary fiction is one of the least commonly used generic hashtags a mere one hundred and twenty-one of the 5,000+ pitches I analyzed. These models privilege genre fiction because writers pitch more genre fiction. Though the Agent model does appear more literary, these few #LF pitches are not preferable to agents; they are not favorited at a higher rate than those pitches tagged with any of the major genre hashtags (41% for literary fiction vs. 46% for genre fiction). These figures suggest not that agents privilege literary fiction over genre fiction as one generic category over another, but that agents are drawn to more literary approaches to genre fiction. What scholars have referred to as the "genre turn" finds its industrial analogue here, in "upmarket fiction": that is, fiction that can attract both discriminating readers of literary fiction as well as those readers who identify as die-hard genre devotees, doubling the potential audience and market share. Upmarket fiction is a potential middle ground a compromise between culture and commerce allowing for the prestige associated with literary fiction and the financial returns seen in high-performing genre fiction.

It remains unclear how many of the faved tweets will receive offers of representation, and of those, how many will receive book deals certainly, not all 3,782. And an even vanishingly smaller fraction of these will result in a book on a shelf, let alone on a promotional list. The better-established Pitch Parties include success stories on their websites: very few of the successful authors have been signed by major agencies, and very few have sold books to reputable publishers (commercial or indie). A surprising number of "success stories" are books that were acquired directly by publishers, without an agent as an intermediary, a major red flag; a number of these publishers appear to be print-on-demand outlets, turning to Pitch Parties for content. This does not mean, however, that Pitch Parties don't provide a useful and unique look at the publication process; short of an invitation to comb through an agent's slush pile or a published author's willingness to share early queries, the Pitches shared in Parties provide us one of the only views into a book's earliest prehistory. Those very lucky few authors who receive offers of representation have a long way to go in their collaboration with their new agent, one of the most overlooked stages of the publication lifecycle. An agent's fave simply means that the pitch is promising; securing a book deal will demand much more of both author and agent. To maximize the likelihood that a manuscript will be well-received, that publishers will see the potential that they see, agents play an active, collaborative role in helping authors to develop their 280-character pitches and accompanying pages into a polished product. We can track these changes through key points in the pre-publication life cycle.

Consider the success story of Rena Olsen. Olsen participated in the September 2014 #PitMad Pitch Party. Her tweet:

Clara raised them as her own daughters. She didn't know her husband kidnapped them to be sold to the highest bidder. #PitMad8

During the course of the day, Olsen's tweet was faved by agent Sharon Pelletier of Dystel & Coderich Literary Management; she requested a query and full manuscript, and signed Olsen within a month. By February 2015, Olsen had a two-book deal with Putnam (Penguin Random House).9 In the five months between the Pitch Party and selling her book to Putnam, Olsen and her agent made some significant changes to the manuscript. The book deal was announced on February 19, 2015, in Publisher's Marketplace, and the synopsis differs significantly from Olsen's first pitch in many ways:

Rena Olsen's THE GIRL BEFORE, about a young woman who begins to see through the lies about the family that raised her and realizes she must question everything she knows about her past and decide whether to protect the man she loves or to face the secrets he's been keeping, to Liz Stein at Putnam, in a two-book deal, by Sharon Pelletier at Dystel & Goderich Literary Management (World).10

Some components of the pitch remain the same: woman with questionable choice in men, secrets kept. But the emphasis shifts from an external crisis to an internal one, concerned more with gaslighting than the mechanics of familial conflict. The daughters have disappeared from the description, and hints of a backstory have taken their place. And by the time the jacket copy was produced, the young woman, Clara, has become implicated in whatever crime is afoot:

In chapters that alternate between past and present, the novel slowly unpeels the layers of Clara's fractured life. We see her growing up, raised with her sisters by the stern Mama and Papa G, becoming a poised and educated young woman, falling desperately in love with the forbidden son of her adoptive parents. We see her now, sequestered in an institution, questioned by men and women who call her a different name - Diana - and who accuse her husband of unspeakable crimes. As recollections of her past collide with new revelations, Clara must question everything she thought she knew to come to terms with the truth of her history and to summon the strength to navigate her future.

The Girl Before has become even more inwardly-focused, with Clara reflecting on her past. She is given a backstory forbidden romance! and is now complicit in the crimes that she had been hoodwinked into merely observing in the Pitch Party version of the story. The novel has acquired a compelling setting, an institution, and a new antagonist; whereas the Pitch and the log-line framed Clara's secret-keeping husband as the source of the novel's conflict, the jacket copy places Clara in opposition to her adoptive parents, the men and women at the institution, and ultimately, her own memory. The 140-character concept has taken a narrative form: chapters that alternate along two timelines. The Pitch Party emphasis on conflict (woman learns her adopted daughters have been trafficked) with generic hints toward crime, suspense, and a domestic thriller gives way to a far more psychological novel a thriller mixed with a coming-of-age story with a description that suggests a more sympathetic take on abuse, survival, childhood trauma, and generational violence. The Kirkus review similarly reflects this generic-hybridization. Written up as "a moving story of recovery and responsibility," the finished product of The Girl Before seems to turn generic conventions upside down: "What at first feels like a tale of suspense turns into a thoughtful look at victims and perpetrators and the difficulties that arise for someone who is both at once."11 If the title, jacket copy, and cover art still place The Girl Before on the same shelf as Gone Girl and Girl on the Train (psychological thrillers, all), the shift from external conflict to internal exploration suggests a move toward literary description, in keeping with the tendencies we saw in the Agent model: aiming upmarket, appealing to the widest possible audience, in hopes of maximum sales.

We may not be privy to every conversation between author and agent, or between author and editor as mediated by agent; but by following the Pitch Party, we can see the extent of a book's development far before the acts of publication, circulation, and reception. Certainly, much of The Girl Before's narrative evolution is due to the dictates of different genres: a 140-character pitch, a one-sentence log-line announcing a book deal, and a short description for a book jacket. More than simply reflecting conventions, however, many of these changes reflect different strategies at different stages of the publication process, each appealing to different readers. And each reflects a different assumption about what sells. But through these key moments, we can also see the effects of preproduction at work. Rare though they might be, the success stories that emerge from such Pitch Parties reveal a vital process that is otherwise conducted in private, and has received scant scholarly attention as a result.

While Pitch Parties may provide useful insight into a book's prehistory, it remains unclear if they accomplish their main goal: making the publishing industry more accessible to more people. Pitch Parties will not replace querying, and Twitter will not replace the slush pile, though some agents and authors certainly do form productive, mutually beneficial working relationships as a result of their Twitter interactions. Still, publishing a novel any novel is not getting any easier; publishing a successful novel is nearly impossible. There has yet to be a Kelly Clarkson-style breakout from a Pitch Party; no matter how trendy the hashtag, Pitch Parties are unlikely to launch a stratospheric career, or even a middling one. And it would appear even less likely that a Jennifer Hudson might emerge; Rena Olsen, an exceptional case, is a white woman, whose odds would have been better than those of a woman of color even if she queried in the traditional way. It appears that many Pitch Party success stories still replicate the logic of the dominant industry.12

At best, Pitch Parties reduce complex, large-scale structural inequities to a problem of mere access whose solution could present itself in 280-characters and a Heart icon. At worst, they prey on hopeful authors pursuing publication at all costs, propping up an illusion of access while providing a steady stream of content to less-than-reputable publishers, or a 15% commission to predatory agents. More realistically and, I think, more naïvely Pitch Parties make an earnest attempt at providing opportunities for authors who lack the training or connections to get their work in front of agents who might not see it otherwise. They traffic in the same misguided fictions that underpin American Idol: that meritocracy is real, and that capitalism works.

Laura B. McGrath is Associate Director of the Stanford University Literary Lab. Beginning fall 2020, she will be Assistant Professor of English at Temple University.


  1. Brenda Drake, "After the Wars... Twitter Pitch Party Today!" Pitch Wars, September 7, 2017. []
  2. "What is DVPit?" DVPit. []
  3. Agents have called #PitMad and #DVPit the "gold standard" of Pitch Parties because of their clear rules, focus, and organization. Unfortunately, I was unable to scrape data from #DVPit due to the timing of the Pitch Party. See Claire Kirch, "Twitter Events Connect Agents and Writers," Publishers Weekly, December 19, 2017.[]
  4. Lisa Katzenberger, "Pitch Agents Through Twitter: Agents Love Online Pitch Parties." Writer's Market Guide to Literary Agents, 26th Edition, ed. Cris Freese (Blue Ash: Writer's Digest Books, 2017), 43.[]
  5. Carly Watters, "The Ultimate Writers' Guide to Twitter Pitch Contests" Writers in the Storm,  September 3, 2014. []
  6. I built these models using the MALLET package in R. McCallum, Andrew Kachites, et al. "MALLET: A Machine Learning for Language Toolkit," 2002. []
  7. With one exception: it appears that the Mystery/Crime/Thriller genre is over-represented in the Agent model compared to the Writer model. If there's a type of genre-fiction that's of interest to agents, it's precisely that type of genre that Writers seem to have moved away from.[]
  8. Katzenberger, 43.[]
  9. "PitMad Success Stories," Pitch Wars. []
  10. "February 19, 2015 THE GIRL BEFORE by Rena Olsen." Publisher's Marketplace, February 19, 2015. []
  11. "The Girl Before by Rena Olsen," Kirkus. May 17, 2016.[]
  12. Again, #DVPit is a notable exception, designed for writers from marginalized communities. Unfortunately, no #DVPit contest was scheduled during the writing of this article, and I was unable to include it in my data.[]