The Event of Autofiction in English

While the term “autofiction” has been in use in French since the 1970s, it has only recently become common in English (Dix 2018). But why did English come to require this term, and what has it been used to describe? We approach these questions by gathering and exploring a corpus of autofiction in English. For text selection we rely on “genre ascriptions”: statements that a work is autofictional, whether found in academic discourse or literary discourse, on social media or the open web. Our corpus comprises works which are consistently and repeatedly described as autofiction across these domains. We suggest that corpus construction procedures like these, which have also been used to explore the “feminist novel” (Mandelman and Mukamal 2021) are generalizable and should be adopted more widely in literary studies, especially where genre boundaries are shifting or new categories are coming into view.

What is autofiction? A blend of fiction and autobiography. Yet the term has been contested; indeed some have offered satirical definitions which suggest that the concept is modish, vacuous, or both (e.g. Caplan 2021). We begin to reply by offering a basic quantitative description of autofiction, seeking regularities which distinguish autofiction in English from other forms of contemporary literature. I particular, we compare our new corpus with the CONLIT dataset (Piper 2022), which presents derived data from ~2500 works of contemporary literature. The CONLIT data is processed with a BERT-based annotation tool, BookNLP, which identifies text features ranging from character and entity identification to supersenses (Bamman 2021). As Mélanie-Becquet et al.(2025) have recently shown in introducing BookNLP-Fr, a French-language adaptation of the BookNLP pipeline, BookNLP entity tagging can address subgenre classification problems like ours, which are of standing interest in computational literary studies (Hettinger et al 2016; Underwood 2016). Early results indicate that even more than other kinds of contemporary literature, English-language autofictions emphasize the depiction of “perceptual encounter” which Piper (2018) has identified as a distinguishing aspect of 21c literary writing in English. This result tends to confirm that autofiction in English comprises an avant-garde, indicative of a directional evolution in English-language literary expression.

Because they emphasize internal reflection over external event, autofictions have often been described as “plotless” (e.g. Tanner 2022). Indeed some works frequently labelled “autofiction” are also described using the neologism “autotheory” (Cavitch 2022). We propose that autofictional “plotlessness” can be operationalized using the concept of narrative “circuitousness” introduced by Toubia et al (2021). This research on “nonlinearity” in narrative shows that distances in vector space can described disjunctions in a story’s time, setting, or perspective. The measure has been applied to several test types and has shown predictive value for various aspects of reception (Berger & Toubia 2024; Guest & Yan 2025). In querying the circuitousness of the texts in the CONLIT corpus, Piper and Toubia (2023) discovered that Jenny Offill’s Dept. of Speculation (2014) was among the least circuitous texts, because in their assessment Offill’s book “focuses on one thing after another with respect to a single character’s internal life.” Offill’s book is a prominent example of autofiction in English, one of the best-attested across various interpretative communities. We follow up by exploring circuitousness as a characteristic of our autofiction corpus. We interpret the results in dialogue with recent research that suggests that “sequentiality” (a measure of next-sentence prediction) predicts differences in autobiographical and imagined stories (Sap et al 2022). We hypothesize that, like sequentiality, circuitousness in autofictional narrative may be able to signal the distinctiveness of autofictional writing with respect to adjacent forms, including the memoir and the novel.

Works Cited

Bamman, D. (2021). BookNLP. https://github.com/booknlp/booknlp

Berger, J., & Toubia, O. (2024). The topography of thought. PNAS nexus, 3(5).

Caplan, W. (2021). 10 New Definitions of Autofiction. Lithub 21 October 2021. https://lithub.com/10-new-definitions-of-autofiction/

Cavitch, M. (2022). Everybody’s autotheory. Modern Language Quarterly, 83(1), 81-116.

Dix, H. (Ed.). (2018). Autofiction in English. Springer.

Guest, N., & Yan, J. (2025). Circuitousness in Disclosure Narratives. Available at SSRN 4098951.

Hettinger, L., Reger, I., Jannidis, F., & Hotho, A. (2016). Classification of literary subgenres. In Proceedings ofDHd. https://dhd2016.de/abstracts/vorträge-049.html.

Mélanie-Becquet, F. et al. (2024). “BookNLP-fr, the French Versant of BookNLP. A Tailored Pipeline for 19th and 20th Century French Literature”. Journal of Computational Literary Studies 3 (1). 10.48694/jcls.3924

Mendelman, L., & Mukamal, A. (2021). The generative dissensus of reading the feminist novel, 1995-2020: A computational analysis of interpretive communities. Journal of Cultural Analytics, 6(3).

Offill, J. (2014). Dept. of Speculation. Alfred A. Knopf.

Piper, A. (2018). Enumerations: data and literary study. University of Chicago Press.

Piper, A. (2022a). The CONLIT dataset of contemporary literature. Journal of Open Humanities Data, 8.

Sap, M. et al (2022). Quantifying the narrative flow of imagined versus autobiographical stories. Proceedings of the National Academy of Sciences, 119(45), e2211715119.

Tanner, J. (2022). The legacy of literary reflexivity; or, the benefits of doubt. Textual Practice, 36(10), 1712-1730.

Toubia, O., Berger, J., & Eliashberg, J. (2021). How quantifying the shape of stories predicts their success. Proceedings of the National Academy of Sciences, 118(26), e2011695118.

Underwood, W. E. (2016). The Life Cycles of Genres. Cultural Analytics (May 23 2016).