Women’s Books versus Books by Women
1.
Introduction
Books written by and marketed towards women have been analyzed mostly in the context of popular culture ( Radway, 1987; Hollows, 2000; Modleski, 2008). In literary criticism however, fictional work by women is regularly held up to such ‘women’s novels’ to measure the quality (van Boven, 1992; Vogel, 2001; Groos, 2011). This connection made between female author gender and popular feminine novels is likely based on bias, but it is not yet well-researched in computational stylistics. In this paper we present a pilot study for examining this potential bias, through the combination of a reader survey and text analysis.
2.
Related work
Although computational stylistics is now quite common in analysis of fiction (i.e. Semino and Short, 2004), ‘women’s’ genres are not researched often in relation to literature. Jautze et al. (2013) focuses on differences between the syntactic make-up of sentences in literary novels and so-called ‘chick lit’ (cf. Ferriss and Young, 2013); Montoro (2012) performs computational-linguistic analysis on chick lit as opposed to a BNC sampler corpus – but not to literary fiction specifically.
3.
Women’s books
What is the relationship between books by women and ‘women’s books’ according to readers? We examine this through results of the National Reader Survey (2013). Respondents were supplied with a list of 401 recent Dutch-language novels (translated and originally Dutch, published between 2007-2012) that were most often loaned from libraries and bought from bookstores between 2009-2012 (Koolen et al., in preparation).
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Respondents supplied ratings of literary quality on books they had read (on a scale of 1-7) and were allowed to motivate one of their scores.
Overall, works by female authors are judged to have lower literary quality (M=3.92, SD=0.81) than those by male authors (M=4.73, SD=1.04); t(344)=-8.34, p < 0.01. This is partially caused by romantic novels, which are mainly written by women (M=3.02, SD=0.60).
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More surprisingly, within general fiction female authors’ works scores’ (M=4.55, SD=0.84) are significantly lower than for male’s (M=5.53, SD=0.73); t(120)=-7.60, p<0.01.
An analysis of the motivations shows that the concept of the ‘women’s book’ (‘vrouwenboek’) and similar gendered terms are used dozens of times to explain what literary quality is
not; a male equivalent is mentioned twice (‘men’s book’, ‘boy’s book’). Examples of novels referred to as ‘women’s’ book’ are translations of
Eat, Pray, Love by Gilbert (general fiction),
Remember Me? by Kinsella (romantic fiction) and
The Ice Princess by Låckberg (suspense). Thus, works by female authors are equated with ‘women’s books’ regardless of the novel’s own genre. Perceived connections that respondents provide are: bad story (about love), a simple style, no deeper layers, etc.. But how much do ‘women’s books’ differ from novels that are perceived as literary? And are they more strongly connected to other female-authored novels than to male-authored ones?
4.
Text analysis
We perform two experiments as a first exploration. We compare present-day romantic novels by female authors (R), predominantly chick lit, to general fiction by women (GF) and general fiction by men (GM). We select the lowest scoring novels in the romantic genre and the highest in the general fiction genre (i.e. the most ‘literary’ ones according to our respondents), to find the clearest contrast (cf. Table 1). We use only one novel per author, unless the author uses a different pen name (Kinsella/Wickham).
Genre / gender author (av. rating literariness) | Transl. from English | Originally Dutch |
Romantic / female (2.8) | 10 | 2 |
General fiction / female (5.2) | 10 | 2 |
General fiction / male (5.9) | 10 | 2 |
4.1.
Experiment 1: style
As we have shown, the style of ‘women’s books’ is seen as inferior. We use stylometric analysis to explore this notion, adding Gilbert’s
Eat, Pray, Love to this experiment (cf. Section 3); a hybrid of general fiction and romance. Stylometric analysis is most often used to perform authorship recognition, but has been successfully applied to identify gender (Rybicki, 2015) and fictional genres (Allison et al., 2011). We apply the method detailed in Eder (2017). First, with R-package Stylo (Eder et al., 2016), we construct a bootstrap consensus tree based on the 100 through 1,000 most frequent words with 100-word intervals, using Classic Delta to calculate stylistic similarity (cf. Eder, 2017). Second, we use network analysis and visualization tool Gephi to visualize the novels’ connectedness (Bastian et al., 2009). Color-codes are based on modularity, which visualizes groupings of greater inner coherence (Blondel et al., 2018). Finally, we apply the ForceAtlas2 algorithm to make groupings more visually distinct.
Fig. 1 shows six clusters. Part of the romantic novels (blue, soft pink) are indeed separated from the general fiction (other colors); Stockett’s
The Help is stylistically connected strongest to romantic novels. General fiction by female and male authors hardly form clusters of their own. Except for one ‘male’ cluster which contains a Barnes’ novel and an outlier: Gilbert’s novel – which is seen as a ‘women’s novel’ by our respondents. Weiner, known for opposing the ‘chick lit’ label to her work (Mead, 2014) has a stronger connection to general fiction. In other words, stylistically seen, part of the romantic novels appear to have a specific signature, but most novels by female authors are not obviously stylistically connected to them.
4.2.
Experiment 2: sentiment
We now use Linguistic Inquiry and Word Count (LIWC), a word list analysis tool, which has a dictionary for Dutch (Boot et al., 2017) and has been applied to literary fiction in genre analysis (Nichols et al., 2014). LIWC contains a number of content and sentiment-related categories that are of interest. Attention to physical appearance, a (heterosexual) love story, work and friendship and have been identified as themes of chick lit novels (Gill and Herdieckerhoff, 2006), which are the main component of the romantic genre in this corpus. We report significant differences on salient categories in an independent
t-test between averages of groups (p < 0.01).
LIWC category | Romantic-Gen. Female | Romantic-Gen. Male | Gen. Female-Gen. Male |
Articles | X | ||
Prepositions | X | ||
Affect | X | X | |
Posemo | X | X | |
Negemo | |||
Social | X | ||
Communication | X | X | |
Friends | X | X | |
Job | X | ||
Swearwords | X |
Table 2 shows that romantic novels differ from general fiction in some ways: more positive emotions, but no significant difference in negative emotions, more words pertaining to friendship. The romantic novels differ in other ways from either the female or the male-authored literary novels: there are more job-related words in the romantic novels than in female-authored general fiction; less articles and prepositions than male-authored general fiction. Female-authored literary novels and male-authored ones do not significantly differ on any category. This might indicate that when comparing literary fiction to romantic novels, readers choose to focus on commonalities with female authors and differences with male authors, whereas differences between female authors and commonalities with male authors are overlooked. However, we need to be careful with interpretations of
t-tests in LIWC (cf. Koolen and van Cranenburgh, 2017). Additional analysis will need to be performed to identify within-group differences. Finally, physicality and the body do not appear to be specific to romantic novels. This finding corroborates earlier research, see Montoro (2012) and Koolen (2018).
5.
Conclusion
Romantic novels appear to be more different from all general fiction than the general fiction differs among authors of female and male gender. They contain signature elements, albeit not all the expected ones (positive emotions and friends, not attention to appearance). Part of the romantic novels are clearly different from general fiction stylistically, but a number of them cluster with male-authored general fiction; most notably work by Gilbert and Weiner. Although further testing is needed, they show that computational stylistic analysis might be used to paint a more objective picture of the actual style of contemporary novels by female authors and the relationships between them. We offer a speculation: if we consider the romantic novels in this corpus to be ‘women’s novels’, there are a several indications that commonalties between female-authored general fiction and romantic novels are stressed heavily and this might be a reason female authors’ novels are judged to have less literary quality. Nevertheless, we do not aim to assert ‘low’ literary quality of the romantic novels, either. To examine gendered quality perceptions further, we will include other fictional genres in future research.
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Note that the Riddle corpus’ novels show the one-sidedness of the market: it consists of few genres, there are very few novels by people of color, it contains mostly European and North-American novels.
The factor of translation will be taken into account in further development of this pilot, for information on effects within the larger project, see van Dalen-Oskam, 2016.
To distinguish genres, we roughly base ourselves on Dutch publishers’ assignments of genre, which is done through a uniform classification system in the Netherlands.