Predictive narrative features in successful young adult novels
Abstract
Despite the increasing popularity of young adult novels, very little research has considered narrative features as predictors of success in these novels. The aim of this research was to investigate if content characteristics and stylistic features could predict the success of young adult novels among the readers. Five types of content characteristics and four types of stylistic features, found in the NoveList database, of 150 bestsellers and 100 less successful novels were compared to the online review ratings of readers. Multiple regression analysis showed that both the content characteristics together, as well as the stylistic features together predicted success. Within the content characteristics the fantasy genre was an important predictor of success. Within the stylistic features a tone focusing on setting and a world building storyline predicted success. This study showcases that the success of young adult novels can be predicted in some degree by content and style.
Name: Rianne Geerlings Student number: 10963804 Master Thesis
University of Amsterdam
Graduate School of Communication
Master’s program: Entertainment Communication Supervisor: prof. dr. E.S.H. Tan
Introduction
In the past two decades the young adult novel has become more popular (Curwood & Fink, 2013). The New York Times was forced to introduce a children’s best-seller list in 2000, after
young adult novels like the Harry Potter series dominated the top spots of the regular
bestselling list for an extended period of time (Cart, 2010). In December 2012 the children’s list needed to be divided into two separate lists: the middle grade list (ages 8 to 12) and the young adult list (ages 12 to 18). This was necessary because the young adult novels now dominated the children’s bestseller list.
Strangely enough this publishing trend is not widely researched by scholars yet (Pearce, Muller & Hawkes, 2013). Previous research has shown that next to pure luck also good marketing can increase the chance of a book becoming a bestseller (Brown, 2011). The form in which a book is published has an influence as well (Schmidt-Stölting, Blömeke & Clement, 2011). Hardcover and paperback copies of the same book title can have different
and sometimes even conflicting influences on sales. But studies such as these do not suffice to
explain the popularity of bestselling young adult novels. Questions arise on what makes these
novels successful. The aim of this study is to narrow this research gap by investigating if narrative features can predict the success of young adult novels. These narrative features may consist of stylistic features and content features. Style is an important factor in higher forms of literature (Leech, 2014). However style is often not taken seriously as a success factor in popular literature.
This study will focus on and be limited to the narrative features of young adult novels provided by the NoveList database. NoveList is an organization of literal experts that provides catalogue enrichment for libraries in the form of information about the characteristics of novels. This study will investigate if the narrative features found in the NoveList database can
explain a part of the success of bestselling young adult novels. This leads to the following research question:
Can narrative features predict the success of young adult novels among the target group?
The narrative features can be divided in content characteristics and stylistic features. Among the content characteristics are: age of the protagonist, genre, gender of the protagonist, subject and presence of an evil antagonist. Stylistic features are: temporal setting, tone, storyline and writing style. Based on this distinction the following two sub questions are formulated:
1. Can content characteristics predict the success of young adult novels among the target group?
2. Can stylistic features predict the success of young adult novels among the target group?
Theoretical background of the narrative features
There are many different factors that could influence the success of a novel. For instance, reader characteristics are important. Readers could have a preference for a specific genre or a certain type of character (Saricks, 2005). Reader characteristics together with the narrative features of a novel could influence success. Although reader characteristics are important, this study will only focus on the narrative features of young adult novels. The NoveList database distinguishes nine narrative features, namely age of the protagonist, genre, gender of the protagonist, subject, presence of an evil antagonist, temporal setting, tone, storyline and
Hypotheses of Content
1) Age of the protagonist. The target group of young adult novels is usually between 12 and 18 years old (Flynn, 2008). Of course readers can be older or younger, but most readers will be in this age range. According to the moderate discrepancy theory (Valkenburg & Piotrowski, in press) teenagers prefer characters that are just a bit older than them self. This indicates that readers will prefer an older teen character, who is around 17 or 18 years old. Therefore the first hypothesis was formed:
H1: An older teen protagonist (approximately 17 or 18 years old) predicts higher levels of success in young adult novels.
2) Genre. The research of Hopper (2005) indicates that teenagers prefer to select a novel based on genre rather than on a single author. Hopper also found that fantasy was the most popular genre among British adolescents. Similar results were found with Australian adolescents in the study of Manuel & Carter (2015). Fantasy was overall the most popular genre in this study. However next to fantasy, the adventure genre was also very popular with Australian male adolescents. Adventure was also the most popular genre in the study of Davila and Patrick (2010). Yet the participants of this study were primary education students,
as well as secondary education students. Because no age distinction was made, it remains
unclear if adventure was the most popular genre among the teenagers in this study. Although
adventure probably is a popular genre, there is not enough evidence that this is the most
popular genre among adolescents. Therefore the following hypothesis was formed:
3) Gender of the protagonist. Beyard-Tyler and Sullivan (1980) found that twelve year-old
boys preferred a male protagonist, while twelve year-old girls preferred a female protagonist.
However as the respondents got older the boys’ preferences for a male protagonist became
stronger whereas the girl’s preferences for a female protagonist decreased. These results are in line with the results of Summers (2012) about the preferences of adult readers. According to
this study most male readers prefer a male protagonist, while most females do not have gender preferences. The female readers who did have a preference usually also preferred a male protagonist. Back in 1990 Schultheis found something similar in adolescent readers. In this study 64% of the novels chosen by female readers and 90% of the novels chosen by male readers contained a male protagonist. These results lead to the third hypothesis:
H3: A male protagonist predicts higher levels of success in young adult novels.
4) Subject. Koss and Teale (2009) did a content analysis of 59 bestselling and award-winning young adult novels. Their results indicate that the subject of successful young adult novels can vary widely. However subjects like coming of age, friendships, family and relationships and searching for answers/secrets are most common. A limitation to this study is that the successful novels were not compared with less successful novels. However the findings match with the knowledge about the developmental stage of teenagers. According to Arnett (2014) most teenagers are self-focused and peers become more important. Because of their
developmental stage teenagers might be more interested in stories with typical adolescent subjects that match with their own life. Therefore the fourth hypothesis was formed:
H4: Typical adolescent subjects like coming of age, teenage friends, first love and high schools predict higher levels of success in young adult novels.
5) Presence of an evil antagonist. Rentfrow, Goldberg and Zilca (2011) found in their study that dark and thrilling content are both popular entertainment genres among emerging adults. This could also be the case for adolescents as they usually have a large interest in
thrilling/exciting media content and horror movies (Valkenburg & Piotrowski, in press). The presence of an evil antagonist could have a thrilling and dark effect on the story. According to the Affective Disposition Theory higher levels of enjoyment can be reached by heightened emotional arousal (Zillman & Cantor, 1977). Invoking a strong moral and sympathetic disposition towards the characters will lead the reader to hope for a positive outcome for the protagonist and for a negative outcome for the evil antagonist. These strong dispositions towards characters will lead to higher levels of emotional arousal and therefore higher levels of enjoyment (Zillman & Cantor, 1977). The presence of an evil antagonist possibly leads to even stronger dispositions towards morally right sympathetic characters. Therefore stories with an evil antagonist could be more enjoyable than stories without an evil antagonist. The following hypothesis was formed:
H5: The presence of an evil antagonist predicts higher levels of success in young adult novels.
Hypotheses of Style
6) Temporal setting. This feature identifies if the story takes place in the past, present or future. The study of Hughes‐Hassell and Rodge (2007) showed that adolescents least
preferred to read stories about historical figures. This makes it less likely that adolescents
prefer stories that take place in the past. When a choice has to be made between a temporal
that take place in the present above stories that take place in the future. The following
hypothesis was formed:
H6: A temporal setting in the present time predicts higher levels of success in young adult novels
7) Tone. Tone may be formal, playful, ironic, serious or humorous or one of many other possible attitudes (Hutton, Hutton & Sampson, 2011). Adolescents are known for preferring humorous content (Valkenburg & Piotrowski, in press). Back in 1990 Schultheis found that humor in novels is an appealing factor for adolescents. This is in line with the results of Hussain and Munshi (2011). According to this study Pakistani adolescents prefer a sense of humor and wittiness in the books they read for pleasure. Based on the knowledge that adolescents prefer humorous media content (Valkenburg & Piotrowski, in press), it is likely that these results can be generalized to adolescents from other ethnical backgrounds. The following hypothesis was formed:
H7: A humorous or funny tone predicts higher levels of success in young adult novels.
8) Storyline. Novels can have many types of storylines. But often the storyline is more plot-driven or more character plot-driven (Perrine, 1987). A story is character-plot-driven when the focus lies on the internal change of the protagonist. When the focus lies more on the events and situations, the story is more plot-driven (Scholes, Phelan & Kellogg, 2006). Because
adolescents prefer thrilling media with high arousal (Valkenburg & Piotrowski, in press), it is
possible that they prefer stories that are plot-driven. Therefore the following hypothesis was
formed:
9) Writing style. Ashok, Feng and Choi (2013) researched if writing style could predict the success of novels. Their study is probably the only quantitative study ever conducted on this subject. They found that the frequencies of prepositions, nouns, pronouns, determiners and adjectives in novels are highly predictive for successful books. Less successful novels were characterized by a higher percentage of verbs, adverbs and foreign words. It seems clear that writing style can influence the success of novels. However, NoveList uses informal
classification to identify the writing style of young adult novels. It is unclear to what extent the results of Ashok et al. (2013) can be generalized to the NoveList database. Because of this no hypothesis will be formed. This study will only explore if the types of writing style
identified by NoveList can predict the success of young adult novels. The following research question was formed:
RQ: Which type of writing style from the NoveList database best predicts the success of young adult novels?
Method
This study contains a descriptive research design. In order the answer the research question a content analysis was conducted. The data, found in the NoveList database, from 150
bestselling young adult novels was compared to online review ratings of readers. In addition, the data from NoveList from 100 less successful young adult novels was also compared to online review ratings of readers.
Sampling procedure of the successful young adult novels
First, 243 successful young adult novels were identified from nine different bestseller lists that were published between August 2015 and March 2016. The following bestseller lists
Times YA bestseller list paperback, NY Times bestseller list YA E-book, NY Times bestseller list series, Amazon UK Young Adult bestseller list, Bol.com Young Adult bestseller list, Bruna Young Adult books bestseller list and the Amazon Germany Young Adult bestseller list. Novels that appeared on at least one of these lists were identified as a bestselling novel. The bestseller lists were only used to identify bestselling novels. No account was taken of how many times a novel appeared in the different bestselling lists. Novels that were identified as a bestseller but not appeared in the NoveList database were excluded from analysis. Out of the 243 bestselling novels a random selection of 150 titles was made with Microsoft Excel. These 150 titles were added to the sample and can be found in appendix A.
Sampling procedure of the less successful young adult novels
The less successful novels were selected based on the Amazon Sellers Rank, which can be found in the product details of each book that is sold on Amazon.com. Novels were
considered less successful if they had a seller rank beyond 50k, indicating that there are 50k novels with higher sales rates. Only novels published between 2006 and 2016 were be used. A sample of 150 novels with a rank beyond 50k was actively searched on the Amazon website. Less successful novels that were found in the Amazon store but not appeared in the NoveList database were excluded from analysis. Microsoft Excel was used to create a random sample of 100 titles out of the 150 novels. A list of the 100 less successful novels can be found in appendix B.
Sampling procedure of the online review ratings of readers
The online review ratings of readers were sampled from the review websites Goodreads.com, Commonsensemedia.com, Bol.com, Amazon.com, Amazon.co.uk and Amazon.de. These
websites give readers the opportunity to give novels a rate in the form of stars. The rates are varying from one star for a low quality novel till five stars for a high quality novel. The selected websites have an origin in four different countries. In addition, the website
Goodreads.com is an international platform. The ratings from these websites together give a global view on the level of success of the novels according to the readers. For every website the average amount of stars of each novel in the sample was recorded. The total amount of review ratings per novel varied strong between the different websites. Therefore the percentage ratios between the amount of reviews for each website were taken into account when calculating the overall average number of stars for each novel. The calculated overall average number of stars represented the success among readers in the analyses.
Measurement of the narrative features
The NoveList database provided information about the narrative features of each young adult novel in the sample. This information was collected via the catalogues of the New York Public Library and the London Public Library. Both libraries are affiliated with the NoveList database. For each novel the Internet web pages of both library catalogues were searched. These web pages gave clear information about which type of narrative features are
characteristic for each novel. A codebook with clear coding instructions was created to code all the different variables for the content analysis. This codebook, with a coding schedule and a coding manual, can be found in appendix C.
The stylistic features ‘tone’ and ‘writing style’ contained too many possible item options for proper statistical analyzes. Therefore the items of both variables were clustered in ten different clusters. The clusters and the original items can be found in the coding manual in appendix C2.
A coder coded all the variables based on the coding manual. The original SPSS dataset contained 250 novels. To check for inter-coder reliability a random selection of 50 novels was made. The second coder coded all the features again for these 50 novels. Cohen’s kappa was used to analyze the inter-coder reliability and the percentage agreement between the coders.
Results Inter-coder reliability
The inter-coder reliability of the dataset was checked using Cohen’s Kappa. The original SPSS dataset contained 250 novels. To check for inter-coder reliability a random selection of 50 novels was made. This selection contained 25 bestselling novels and 25 less successful novels. The 50 novels were coded by coder 1 and 2. The Cohen’s Kappa and the percentage agreement between the two coders were calculated with SPSS using crosstabs. The results can be found in Appendix D. The acceptance level of the Cohen’s Kappa is .80 (Lombard, 2016). Table D1 in Appendix D shows that the Cohen’s Kappa is above .80 for all variables. All variables were tested reliable for inter-coder reliability. This indicates that the whole dataset can be considered reliable.
Bestsellers vs. less successful novels
A t-test was conducted to research if there was a difference between the online review ratings of readers in bestselling and less successful novels. The bestselling novels (M = 4.02, SD = .276) got significantly higher online review ratings than the less successful novels (M = 3.68, SD = .292); t(248) = -9.211, p < .001, 95% CI.
Analysis of the content characteristics in association with success ratings by readers
Multiple regression analysis was conducted to research if all content characteristics i.e. genre, gender of the protagonist, subject, age of the protagonist and presence of an evil antagonist together could predict the success of young adult novels among the readers. The method was ‘enter’, meaning that all predictors were used simultaneously into the accusation.In order to do a multiple regression analysis it is important to check for assumptions like
multicollinearity and equality of variances between the residues. First the assumption for multicollinearity was checked. The results from the collinearity statistics in SPSS showed VIF-values of 10.0 or lower and tolerance-values higher than .10 for all variables in the analysis. This indicates that the assumption of multicollinearity was not violated (UCLA, 2016). Next the equality of variances between the residues was checked. The scatterplot of the residues did not show a clear pattern. This indicates that there is equality of variances between the residues, meaning the assumption was not violated.
The regression model with the online review ratings of readers as a dependent variable and the content characteristics genre, gender of the protagonist, subject, age of the protagonist and presence of an evil antagonist as independent variables was significant, F(17, 77) = 2.100, p = .015. The strength of this prediction was moderate (R2 = .32). Initially the variable present temporal setting was used as a control variable, but this variable failed to produce a
significant relationship with success. The variable gender of the protagonist was not used as a control variable because it was not clear if the readers were male or female.
The same multiple regression analysis was conducted a second time, but this time a distinction was made between the bestselling novels and less successful novels. There was a significant strong relationship between the content characteristics and the online review ratings of readers within the group of bestselling novels (F(17, 38) = 2.983, p = .003, R2
= .57). A similar relationship was found within the group of less successful novels (F(15, 23) = 2.843, p = .024, R2 = .62).
Tests of content
The first hypothesis was that an older teen protagonist would predict higher levels of success. This analysis checked if the success of novels increased when the age of the protagonists rises. No relationship was found between the age of the protagonist and the online review ratings of readers. This relationship was not found either when a distinction was made between
bestselling and less successful novels.
The second hypothesis was that the fantasy genre would predict higher levels of success. There was a significant relationship between fantasy and the online review ratings of readers (b* = .46, t = 3.59, p = .001, 95% CI [.17, .59]). This is a positive relationship, which indicates that novels with a fantasy genre got higher ratings by readers than non-fantasy novels. Next to fantasy, there also was a significant relationship between the humorous genre and the online review ratings of readers (b* = -.26, t = -2.33, p = .023, 95% CI [-.84, -.07]). This is a negative association, meaning that novels with a humorous genre got lower online review ratings than novels with a non-humorous genre. The relationship between the humorous genre and the online review ratings was also found within the group of bestseller novels (b* = -.45, t = -2.99, p = .005, 95% CI [-.94, -.18]). This is relationship is also negative, indicating that bestsellers with a humorous genre got lower ratings by readers than bestsellers with a non-humorous genre. The remaining genres failed to produce a significant relationship with success.
The third hypothesis was that a male protagonist predicts higher levels of success. No significant relationship was found between the gender of the protagonist and the online review ratings of readers. Within the group of less successful novels there was a significant
relationship between a female protagonist and the online review ratings (b* = -.41, t = -2.34, p = .028, 95% CI [-.55, -.03]). This was a negative relationship, meaning that less successful novels with a female protagonist got lower ratings by the readers than less successful novels without a female protagonist.
The fourth hypothesis was that typical adolescent subjects would predict higher levels of success. The predictors were coming of age, high schools, teenagers, first love and teenage friendships. No significant relationship was found between typical adolescent subjects and the online review ratings of readers. This relationship was also not found when a distinction was made between bestselling and less successful novels.
The fifth hypothesis was that the presence of an evil antagonist would predict higher levels of success. Again no relationship was found. Also no relationship was found when a distinction was made between the bestsellers and the less successful novels.
Analysis of the stylistic features in association with success ratings by readers
Next a second multiple regression analysis was conducted to research all the stylistic features i.e. temporal setting, tone, storyline and writing style could predict the success of young adult novels among the readers. The method was ‘enter’, meaning that all predictors were used simultaneously into the accusation.Again the assumptions of multicollinearity and equality of variances between the residues were checked. The results from the collinearity statistics in SPSS showed VIF-values of 10.0 or lower and tolerance-values higher than .10 for all variables in the analysis of the overall sample. This indicates that the assumption of
multicollinearity was not violated (UCLA, 2016). Next the equality of variances between the residues was checked. The scatterplot of the residues did not show a clear pattern. This
The regression model with the online review ratings of readers as a dependent variable and the stylistic features writing style, temporal setting, tone and storyline together as
independent variables was significant, F(28, 30) = 2.203, p = .018. The strength of this prediction was strong (R2 = .67). Initially the variable age of the protagonist was used as a control variable, but this variable failed to produce a significant relationship with success. Just like the first model, the variable gender of the protagonist was not used as a control variable because it was not clear if the readers were male or female.
When a distinction was made between the bestselling novels and the less successful novels multicollinearity appeared between many different variables in both of the regression models. Therefore the variables ‘temporal setting past’, ‘temporal setting present’ and ‘temporal setting future’ where combined into the new variable ‘temporal setting’. The variables ‘tone thrilling’, ‘ tone positive emotions’ and ‘tone negative emotions’ were
combined into the new variable ‘tone emotions’. At last the variables ‘storyline action-packed’ and ‘storyline plot-driven’ were combined into the variable ‘storyline action plot’.
Combining these variables resolved the problem with multicollinearity within the group of bestselling novels. The results from the collinearity statistics in SPSS showed VIF-values of 10.0 or lower and tolerance-values higher than .10 for all variables in the analysis. This indicates that the assumption of multicollinearity was not violated anymore for the group of bestselling novels (UCLA, 2016). Also the equality of variances between the residues was checked. There was no clear pattern found in the scatterplot of the residues, which indicates that there is equality of variances between the residues. This means the assumption was not violated.
After combining the variables, the regression model of the less successful novels was not significant. However, the regression model for the group of bestselling novels with the online review ratings of readers as a dependent variable and the stylistic features writing style,
temporal setting, tone and storyline together as independent variables was significant, F(20, 15) = 12.543, p < .001. The strength of this prediction was very strong (R2 = .87). This indicates that the stylistic features of novels can predict the online review ratings of readers within the group of bestselling novels.
Tests of style
Next the sixth hypothesis was analyzed. The hypothesis was that a temporal setting in the present time predicts higher levels of success. There was no significant relationship found between the temporal setting and the online review ratings of readers.
The seventh hypothesis was that a humorous tone would predict higher levels of success in young adult novels. No significant relationship was found between a humorous tone and the ratings by readers in the overall sample. This relationship was also not found in the group of bestselling novels. However there was a significant relationship between a ‘social problematic tone’ and the online review ratings by readers (b* = -.32, t = -2.34, p = .026, 95% CI [-.63, -.04]). This was a negative association, which indicates that novels with a social problematic tone got lower ratings by readers than novels without a social
problematic tone. The relationship between a social problematic tone and the online review ratings by readers was also significant within the group of bestsellers (b* = -.27, t = -3.42, p = .004, 95% CI [-.46, -.11]). This is a negative relationship, which indicates that bestseller novels with a social problematic tone got lower ratings by readers than bestseller novels without this type of tone. Next there was a significant relationship between a ‘romantic tone’ and the ratings by readers within the group of bestsellers (b* = -.23, t = -2.27, p = .038, 95% CI [-.29, -.01]). This is a negative relationship, meaning that bestseller novels with a romantic tone got lower ratings by readers than bestseller novels without a romantic tone. In addition,
review ratings by readers within the bestseller group (b* = .99, t = 7.69, p < .001, 95% CI [.34, .60]). This is a positive association, meaning that bestseller novels with a tone focusing on the setting got higher ratings by the readers than bestseller novels without this type of tone. In addition, there was a significant relationship between an ‘emotional tone’ and the ratings by readers within the bestseller group (b* = -.51, t = -4.01, p = .001, 95% CI [-.34, -.11]). This is a negative association meaning that bestselling novels with an emotional tone got lower ratings than bestselling novels with a non-emotional tone. At last there was also a significant relationship between a ‘serious tone’ and the online review ratings by readers within the group of bestsellers (b* = -1.03, t = -4.01, p = .001, 95% CI [-.34, -.11]). This is a negative relationship, meaning that bestselling novels with a serious tone got lower ratings by readers than bestselling novels with a non-serious tone. The remaining types of tone failed to produce a significant relationship with success.
The last hypothesis was that a plot-driven storyline would predict higher levels of success among the readers. No significant relationship was found within the overall sample as well as in the bestseller group. However there was a significant relationship between an intricately plotted storyline and the online review ratings of readers within the overall group (b* = -.44, t = -2.21, p = .035, 95% CI [-.77, -.03]). This is a negative association, indicating that novels with an intricately plotted storyline got lower ratings than novels without this type of storyline. This relationship was not found within the group of bestselling novels. At last there was a significant relationship between a world-building storyline and the ratings by readers within the group of bestseller novels (b* = .53, t = 5.22, p < .001, 95% CI [.16, .38]). This was a positive association, meaning that bestselling novels with a world-building storyline got higher online review ratings than novels without this type of storyline. The remaining storylines failed to produce a significant relationship with success.
The research question was about which type of writing style best predicts the success of young adult novels. The predictors were regional language, unusual structure, detailed, controversial, attractive, poetic, conversational, spare, thoughtful and witty. There was no significant relationship found between writing style and the online review ratings of readers within the overall sample. But within the group of bestsellers the writing styles ‘detailed’, ‘attractive’, ‘conversational’ and ‘spare’ significantly predicted the success among the readers. Because the variables ‘writing style conversational’ and ‘writing style spare’ were only
present in less than ten novels these variables were excluded from analysis. There was a negative association between a detailed writing style and the online review ratings of readers (b* = -.69, t = - 4.82, p < .001, 95% CI [-.48, -.19]). This means that novels with a detailed writing style got lower ratings by readers than novels without a detailed writing style. Next to a detailed writing style, there was a significant relationship between an attractive writing style and the online review ratings by readers (b* = -.30, t = -2.42, p = .029, 95% CI [-.34, -.02]). This was also a negative association, which indicates that novels with an attractive writing style got lower ratings by readers than novels without an attractive writing style. The remaining writing styles failed to produce a significant relationship with success.
Discussion
The first aim of this study was to explore if narrative features can predict the success of young adult novels. These narrative features were divided in content characteristics (i.e. age of the protagonist, genre, subject, gender of the protagonist and presence of an evil antagonist) and stylistic features (i.e. temporal setting, writing style, tone and storyline). The results suggest that the content characteristics and stylistic features are both important predictors of success.
Discussion of the Content Characteristics
Within the content characteristics only the fantasy genre predicted success. This suggests that the fantasy genre is more successful than other types of genres. The relationship between the humorous genre and success was also significant, but this was a negative association.
Against expectations, this study did not found a relationship between the other content characteristics and the success of young adult novels. This is remarkable as content
characteristics like age of the protagonist, gender of the protagonist and subject are important factors in identification with the main character (Cohen, 2001). Higher levels of identification lead to more intense media experiences, which induce higher levels of enjoyment (Cohen, 2001). This is a grounded theory. However in this research other factors that are involved in the identification process, like ethnicity and socio-economic status of the protagonist, were not investigated because they were not represented in the NoveList database.
Another explanation could be that although all hypotheses in this study were based on adolescent readers, not all readers were in fact teenagers. As mentioned before many content characteristics are important factors in identification with the main character (Cohen, 2001). Yet, the age of the readers remained unclear and it might be possible that in fact not all readers were teenagers. Older generations might have different preferences when it comes to content characteristics like the age of the protagonist, gender of the protagonist and type of subject. Identification with the protagonist in young adult novels might not work for older readers.
In addition it also remained unclear whether the readers were male or female. Gender of the readers might have an influence on the results. If the number of men and women in the sample is about equal and if men and women prefer opposite content characteristics, it might be possible that the results are neutralized. For instance, based on stereotypes it could be
possible that women prefer love stories and men prefer science fiction. These differences might be cancelled in the multiple regression analysis.
For the features genre and subject it might be possible that there were to many
categories in the analysis to get distinctive results. Combining more categories might have led to more powerful results.
The last result within the content characteristics was highly remarkable. No
relationship was found between the presence of an evil antagonist and the success of young adult novels. However according to the Affective Disposition Theory (Zillman & Cantor, 1977) higher levels of enjoyment can be reached by the presence of an evil antagonist. No explanation for this result could be found in the sample or the method.
Discussion of the stylistic features
Within the stylistic features a tone focusing on setting and a world-building storyline were both predictors of success. According to the readers, novels with a tone that focused on the setting were of higher quality than novels with a different type of tone. Thus, a tone that focuses on the setting of a story is more successful than other tones. In addition, novels with a world-building storyline received higher ratings by the readers than novels with a different type of storyline. This suggests that a world-building storyline, where readers are immersed in an imaginary world with invented histories and cultures, is more successful than other types of storylines. These two successful features can contribute to escapism. The results are in line with the research theory suggesting that escapism is an important need for adolescent readers that entertainment can gratify (Birdi, 2014).
No relationship was found between a present temporal setting and success. This is remarkable because most teenagers prefer plausible content (Valkenburg & Piotroski, in
press). In addition, no relationship was found between a historic or future temporal settings and success either. No explanation for this result could be found in the sample or the method.
There were many types of tones that showed a negative relationship with success. Besides, no evidence was found for the hypothesis that a humorous tone would predict
success. It is possible that teenagers do appreciate humorous aspects in a story, but that humor should not be the main tone.
None of the types of writing styles predicted success. However, a significant negative relationship was found between a detailed writing style and success. Writing style is a more linguistic feature, whereas tone and storyline are more based on imagination. In line with general notions about popular narratives it could be assumed that factors based on
imagination are more important than linguistic factors for the readers of young adult novels. Linguistic factors may be more important for literary stories that are less popular in the population.
Limitations and Future Directions
One of the limitations of the present study is the small sample size. The sample contained only 250 novels whereof 150 bestselling novels and 100 less successful novels. A larger sample size could answer some of the remaining questions that where stated above. Future research with a larger sample size is necessary to see if the results match with the results from the present study.
Another limitation of this study is that only bestselling and completely unsuccessful novels were used in the sample. These are the two extremes along the line. Using novels all along the line would give a more nuanced view. Future research should include novels with all different levels of success.
The next limitation is that it remains unclear how the NoveList database is established. Literary experts categorize all the novels in the database, however it is not clear how this is done. In an ideal world, future research would have a more transparent method on how the content characteristics and stylistic features are categorized.
A fourth and principal limitation is that there is no information about the readers in this study. Demographics like age, gender, ethnicity and socio-economic status were unknown. This is an insuperable limitation when using public Internet forums. A future study that
involves reader characteristics could give more insight in the reading preferences readers from different backgrounds.
This study found that fantasy, a tone that focuses on setting and a world-building storyline are important predictors of success. Future qualitative research should address why this is the case. This could contribute to the existing knowledge on the reading preferences of teenagers and the readers of young adult novels. Knowing why could also help to form new hypotheses and research questions.
Conclusion
This small study showcases that the success of young adult novels can be predicted in some degree by content en style. It is a general assumption that the success of popular literature is derived from content. Style is believed to be reserved for higher literature (Leech, 2014). However this research shows that style must at least be taken serious as a success factor in popular young adult novels. Especially stylistic features that invoke imagination are important, whereas linguistic style is less influential.
A fantasy genre, a tone focusing on setting and a world-building storyline were the most important predictors of success among the readers. These results suggest that escapism
References
Arnett, J. J. (2014). Adolescence and emerging adulthood. Pearson Education Limited.
Ashok, V. G., Feng, S., & Choi, Y. (2013). Success with style: Using writing style to predict
the success of novels. Poetry, 580(9), 70.
Beyard-Tyler, K. C., & Sullivan, H. J. (1980). Adolescent reading preferences for type of
theme and sex of character. Reading Research Quarterly, 104-120.
Birdi, B. (2014). Genre fiction readers: a quantitative exploration of provided construct
ratings. Journal of Documentation, 70(6), 1054-1075.
Brown, S. (2011). And then we come to the brand: academic insights from international
bestsellers. Arts Marketing: An International Journal, 1(1), 70-86.
Cart, M. (2010). Young adult literature: From romance to realism. American Library
Association.
Cohen, J. (2001). Defining identification: A theoretical look at the identification of audiences with media characters. Mass Communication & Society, 4(3), 245-264.
Curwood, J. S., & Fink, L. (2013). The Hunger Games: Literature, literacy, and online affinity
spaces. Language Arts, 90(6), 417.
Davila, D., & Patrick, L. (2010). Asking the experts: What children have to say about their
reading preferences. Language Arts, 87(3), 199.
Flynn, R. (2008). Boundary issues. Children’s Literature Association Quarterly, 33(2), 117-
118.
Hopper, R. (2005). What are teenagers reading? Adolescent fiction reading habits and reading
choices. Literacy, 39(3), 113-120.
Hughes‐Hassell, S., & Rodge, P. (2007). The leisure reading habits of urban adolescents.
Hussain, I., & Munshi, P. (2011). Identifying reading preferences of secondary school
students. Creative Education, 2(05), 429.
Hutton, R., Hutton, G., & Sampson, F. (2011). Passing the National Admissions Test for Law
(LNAT). SAGE.
Koss, M. D., & Teale, W. H. (2009). What’s Happening in YA literature? Trends in Books for Adolescents. Journal of Adolescent & Adult Literacy, 52(7), 563-572.
Leech, G. (2014). Language in literature: style and foregrounding. Routledge.
Lombard, M. (2016). Practical Resources for Assessing and Reporting Intercoder Reliability in Content Analysis Research Projects. Retrieved from
http://matthewlombard.com/reliability/#How%20should%20content%20analysis%20r
esearchers%20properly%20assess%20and%20report%20intercoder%20reliability Pearce, S., Muller, V., & Hawkes, L. (2013). Popular Appeal: Books and Films in
Contemporary Youth Culture. Cambridge Scholars Publishing.
Perrine, L. (1987). Story and structure. Canadian edition. Toronto, Ontario: Harcourt Brace Canada.
Rentfrow, P. J., Goldberg, L. R., & Zilca, R. (2011). Listening, watching, and reading: The
structure and correlates of entertainment preferences. Journal of personality, 79(2),
223-258.
Saricks, J. G. (2005). Readers’ advisory service in the public library. American Library
Association.
Schmidt-Stölting, C., Blömeke, E., & Clement, M. (2011). Success drivers of fiction books:
An empirical analysis of hardcover and paperback editions in Germany. Journal of
Media Economics, 24(1), 24-47.
Schultheis, C. (1990). A Study of the Relationship between Gender and Reading Preferences
in Adolescents.
Summers, K. (2013). Adult reading habits and preferences in relation to gender differences.
Reference & User Services Quarterly, 52(3), 243-249.
UCLA (2016). SPSS web books: Regression with SPSS. Retrieved from:
http://www.ats.ucla.edu/stat/spss/webbooks/reg/chapter2/spssreg2.htm
Valkenburg, P.M. & Piotrowski, J.T. (In press). Plugged In: Growing Up with Screens. New Haven, CT: Yale University Press.
Zillman, D., & Cantor, J. R. (1977). Affective responses to the emotions of a protagonist. Journal of Experimental Social Psychology, 13(2), 155-165.
Appendix A: List of the bestseller young adult novels
Novel Author
1 Girl online: on tour Zoe Sugg
2 The walls around us Nova Ren Suma
3 The siren Kierra Cass
4 Harry Potter and the chamber of secrets J.K. Rowling
5 Twilight Stephanie Meyer
6 the transfer Victoria Roth
7 If he had been with me Laura Nowlin
8 Truthwitch Susan Dennard
9 Black widow forever red Margaret Stohl
10 We were liars E. Lockhart
11 The mortality doctrine: the eye of minds James Dasher
12 An abundance of Katherines John Green
13 A thousand pieces of you Claudia Gray
14 The fault in our stars John Green
15 Mockingjay Suzanne Collins
16 Six of crows Leigh Bardugo
17 Salt to the sea Ruta Sepetys
18 Passenger Alexandra Bracken
19 Talon Julie Kagawa
20 I'll give you the sun Jandy Nelson
21 Fangirl Rainbow Rowell
22 The queen's poisoner Jeff Wheeler
23 I am number four Pittacus Lore
24 The mortal instruments: City of glass Cassandra Clare
25 The rest of us just live here Patrick Ness
26 Catching fire Suzanne Collins
27 99 Days Katie Cotugno
28 The 5th wave Rick Yancey
29 More happy than not Adam Silvera
30 The sleeper and the spindle Neil Gaiman
31 Harry Potter and the goblet of fire J.K. Rowling
32 The infernal devices: clockwork prince Cassandra Clare
33 Nightfall Jake Halpern and Peter Kujawinski
34 Harry Potter and the order of the phoenix J.K. Rowling
35 Illuminae Amie Kaufman and Jay Kristoff
36 The book thief Markus Zusak
37 The paper magician Charlie N. Holmberg
38 Sea of shadows Kelley Armstrong
39 Magonia Maria dahvana headley
40 Looking for Alaska John Green
41 Kill the boy band Goldy Moldavsky
42 My Life Next Door Huntley Fitzpatrick
43 The iron fey: call of the forgotten Julie Kagawa
44 Ice like fire Sara Raasch
49 Snow like ashes Sara Raasch
50 Breaking dawn Stephanie Meyer
51 Eclipse Stephanie Meyer
52 The infernal devices: clockwork princess Cassandra Clare
53 The raven king Maggie Stiefvater
54 Red queen Victoria Aveyard
55 The hobbit J.R.R. Tolkien
56 A court of thorns and roses Sarah J. Maas
57 Chronicles of the underworld city of ashes Cassandra Clare
58 The way I used to be Amber Smith
59 Percy Jackson: The lightning thief Rick Riordan
60 The perks of being a wallflower Stephen Chbosky
61 Divergent 0.1 Four Victoria Roth
62 The trials of apollo: the hidden oracle Rick Riordan
63 The dark elements Jennifer L. Armentrout
64 To all the boys I've loved before Jenny Han
65 P.S. I still love you Jenny Han
66 An ember in the ashes Sabaa Tahir
67 The sorcerer's daughter Terry Brooks
68 The matchmaker's playbook Rachel van Dyken
69 The lie tree Frances Hardinge
70 where she went Gayle Forman
71 The haunting of sunshine girl Paige McKenzie and Alyssa Sheinmel
72 Glass sword Victoria Aveyard
73 The hired girl Laura Amy Schlitz
74 Harry Potter and the philosopher's stone J.K. Rowling
75 The rose society Marie Lu
76 Those who leave and those who stay Elena Ferrante
77 This is where it ends Marieke Nijkamp
78 Paper Towns John Green
79 The master magician Charlie N. Holmberg
80 The banished of muirwood Jeff wheeler
81 The selection Kierra Cass
82 Traffick Ellen Hopkins
83 The infernal devices: clockwork angel Cassandra Clare
84 Walk on earth a stranger Rae Carson
85 Insurgent Victoria Roth
86 Lady midnight Cassandra Clare
87 Carry on Rainbow Rowell
88 Allegiant Victoria Roth
89 My brilliant friend Elena Ferrante
90 Me and Earl and the dying girl Jesse Andrews
91 Fire and flood Victoria Scott
92 If I stay Gayle Forman
93 The maze runner James Dasher
94 Thirteen reasons why Jay Asher
95 Unforgiven Lauren Kate
96 Dorothy must die Danielle Paige
97 Zeroes Scott Westerfeld
98 Divergent Victoria Roth
100 Illusionarium Heather Dixon
101 Eleanor and Park Rainbow Rowell
102 Harry Potter and the deathly hollows J.K. Rowling
103 I was here Gayle Forman
104 Tricks Ellen Hopkins
105 The white rose Amy Ewing
106 The maze runner: the death cure James Dasher
107 The hunger games Suzanne Collins
108 Miss Peregrine's home for peculiar children Ransom Riggs
109 The absolutely true diary of a part-time indian Sherman Alexie and Ellen Forney
110 The one Kierra Cass
111 Firstlife Gena Showalter
112 The wrath and the dawn Renee Ahdieh
113 Harry Potter and the half-blood prince J.K. Rowling
114 The jewel Amy Ewing
115 The darkest part of the forest Holly Black
116 We all looked up Tommy Wallach
117 The selection the prince and the guard Kierra Cass
118 The scorch trials James Dasher
119 Everything, everything Nicola Yoon
120 Harry Potter and the prisoner of Azkaban J.K. Rowling
121 Chronicles of the underworld city of bones Cassandra Clare
122 Jackaby William Ritter
123 Messenger of fear Michael Grant
124 Tamar Mal Peet
125 All the bright places Jennifer Niven
126 Steelheart Brandon Sanderson
127 The glittering court Richelle Mead
128 The wicked will rise Danielle Paige
129 Another day David Levithan
130 Saint anything Sarah Dessen
131 Lair of dreams Libba Bray
132 Suicide notes from beautiful girls Lynn Weingarten
133 Reawakened Colleen Houck
134 Hollow city Ransom Riggs
135 Midnight thief Livia Blackburne
136 Until Friday night Abbi Glines
137 Side effects may vary Julie Murphy
138 Off the page Jodi Picoult and Samantha van Leer
139 Asylum Madeleine Roux
140 Every last word Tamara Ireland Stone
141 The Elite Kierra Cass
142 The heir Kierra Cass
143 The Ciphers of Muirwood Jeff wheeler
144 The void of Muirwood Jeff wheeler
145 The fellowship of the ring J.R.R. Tolkien
146 The golden compass Philip Pullman
Appendix B: List of the less successful young adult novels
Title Author
1 Evercrossed Elizabeth Chandler
2 Darkness Becomes Her Kelly Keaton
3 Hush, hush Becca Fitzpatrick
4 Venom: the secrets of the eternal rose Fiona Paul
5 Shadow walkers Brent Hartinger
6 Ghost flower Michele Jaffe
7 Fairest Gail Carson
8 Lucky fools Coert Voorhees
9 When you open your eyes Celeste Conway
10 This is not forgiveness Celia Rees
11 Going over Beth Kephart
12 The spiritglass charade Colleen Gleason
13 Hunted: a house of night novel P.C. Cast & Kristen Cast
14 Ice Shock M.G. Harris
15 The outcasts of 19 schuyler place E.L. Konigsburg
16 Doing it Melvin Burgess
17 The way he lived Emily Wing Smith
18 Ready or not Meg Carbot
19 The downside of being Charlie Jenny Torres Sanchez
20 The celebutantes: In the club Antonio Pagiarulo
21 The extraordinary secrets of April, May & June Robin Benway
22 Kristen: a Clique novel Lisi Harrison
23 Someone else's life Katie Dale
24 Full service Will Weaver
25 David Mary Hoffman
26 Tantalize Cynthia Leitich Smith
27 Suck it up and die Brian Meehl
28 Au revoir, crazy European chick Joe Schreiber
29 Rosebush Michele Jaffe
30 You against me Jenny Downham
31 Inconvenient Margie Gelbwasser
32 Chloe Doe Suzanne Pjilips
33 The corner of bitter and sweet Robin Palmer
34 Raiders' ransom Emily Diamand
35 Darkwater Catherine Fisher
36 Six days Philip Webb
37 Stolen away Alyxandra Harvey
38 The dead of winter Chris Priestley
39 Endure Carrie Jones
40 ReVamped Lucienne Diver
41 Virals Kathy Reichs
42 Ascend Amanda Hocking
43 Flesh & bone Jonathan Maberry
46 The celestial globe Marie Rutkoski
47 Princess Academy Shannon Hale
48 Bloodrose Andrea Cremer
49 Destined P.C. Cast & Kristen Cast
50 White Crow Marcus Sedgwick
51 The innocents Lili Peloquin
52 Burried thunder Tim Bowler
53 Angels on sunset boulevard Melissa de la Cruz
54 I hunt killers Barry Lyga
55 As I wake Elizabeth Scott
56 Secret Society Tom Dolby
57 The shattering Karen Healey
58 Masquerade: a blue bloods novel Melissa de la Cruz
59 Flicker & burn: a cold fury novel T.M. Goeglein
60 Revelations Melissa de la Cruz
61 Prism Faye Kellerman and Aliza Kellerman
62 Jekel loves Hyde Beth Fantaskey
63 Diamond in the shadow Caroline B. Cooney
64 Stay with me Paul Griffin
65 17 & gone Nova Ren Suma
66 Mercy Rebecca Lim
67 Cold fury T.M. Goeglein
68 Death in the air Shane Peacock
69 Three black swans Caroline B. Cooney
70 If the witness lied Caroline B. Cooney
71 Melody burning Whitley Stieber
72 The madman of Venice Sophie Masson
73 Dark song Gail Giles
74 7 souls Barnabas Miller and Jordan Orlando
75 Hurricane song Paul Volponi
76 Code: a virals novel Kathy Reichs
77 Bonechiller Graham McNamee
78 Phoenix Island John Dixon
79 Secret letters Leah Scheier
80 In too deep Coert Voorhees
81 Hanging by a thread Sophie Littlefield
82 Streams of babel Carol Plum-ucci
83 Only the good spy young Ally Carter
84 Devil's kiss Sarwat Chadda
85 Shades of Earth Beth Revis
86 The different girl Gordon Dahlquist
87 Invisibility Andrea Cremer and David Levithan
88 Gifts Ursula K. Le Guin
89 Dark goddess Sarwat Chadda
94 The wrap-up list Steven Arntson 95 The eternal ones: what if love refused to die? Kirsten Miller
96 The magnolia league Katie Crouch
97 The dangerous days of Daniel X James Patterson and Michael Ledwidge
98 Divine one Lynne Ewing
99 Ghost town Rachel Caine
Appendix C: Codebook C1: Coding schedule T it le Su cc es s T y pe o f g enre G ender p ro ta g o nis t Su bje ct Ag e o f the P ro ta g o nis t P re sence ev il a nta g o nis t Writ ing -s ty le T empo ra l Set ting T o ne Sto ry lin e Ra ting C2: Coding manual Title
Record the title of the novel
Success
Fill in the number
1. Novel comes from the bestselling novels sample 2. Novel comes from the less successful novels sample
Type of genre
Young adult and juvenile genre can be ignored! Fill in the number
1. Fantasy 2. Love Story Including: Romance 3. War Story 4. History 5. Psychological Fiction
Including: Parody 8. Science Fiction Including: Dystopias 9. Thriller 10. Mystery 11. Horror
Including: Ghost story 12. Unknown
Gender of the protagonist Fill in the number
1. Male 2. Female 3. Unknown
Subject
1. Typical adolescent topics For instance: School life High schools Teenagers First love Coming of age 2. General novel topics
All other subject types
Age of the protagonist Record age (-1 if unknown)
Presence of an evil antagonist Fill in the number
1. Evil antagonist is present 2. No evil antagonist in the story
Writing style
Some types of writing style are clustered. Record the number of the cluster the type of writing style is in. 1. Regional language Dialect filled Jargon filled Slang heavy 2. Unusual structure Stylistically complex Experimental 3. Detailed Descriptive Richly detailed Lush 4. Controversial Candid Gritty 5. Attractive Engaging Compelling Attention-grabbing 6. Poetic Lyrical Wordplay filled 7. Conversational Conversational Dialogue-driven Banter-filled 8. Spare 9. Thoughtful 10. Witty
Temporal setting Fill in the number
1. Story takes place in the past 2. Story takes place in the present 3. Story takes place in the future 4. Temporal setting is unknown
Tone
Some types of tone are clustered. Record the number of the cluster the type of tone is in. 1. Humorous Amusing Darkly Humorous Funny 2. Social Problematic Angst filled Chaste High drama 3. Romance Romantic Steamy 4. Serious Serious Thought-provoking Reflective 5. Negative emotions Bittersweet Bleak Emotional intense Melancholy Suspenseful Heart wrenching
Atmospheric Homespun Nostalgic
Strong sense of place Whimsical 7. Thrilling Creepy Disturbing Gruesome Haunting Menacing 8. Positive emotions Feel good Inspiring Moving Upbeat 9. Offbeat 10. Mystical 11. Unknown Storyline
Fill in the number 1. Action-packed 2. Character-driven 3. Intricately plotted 4. Issue oriented 5. Nonlinear 6. Open ended 7. Plot-driven 8. Sweeping 9. World building
Rating
Appendix D: Results inter-coder reliability analysis Table D1
Results of inter-coder reliability testing
%Agreement Kalpha
Genre Fantasy 100 1.000
Genre Love Story 100 1.000
Genre Paranormal Genre Mystery 97.1 100 .892 1.000 Genre Adventure
Gender Protagonist Male Gender Protagonist Female Subject Typical Adolescent Age Protagonist
Presence of Evil Antagonist Writing Style Unusual Structure Writing Style Detailed
Writing Style Attractive Writing Style Poetic
Writing Style Conversational Writing Style Thoughtful Temporal Setting Past Temporal Setting Present Temporal Setting Future Tone Humorous Tone Social Problematic Tone Romance
Tone Serious
Tone Negative Emotions Tone Setting 100 96.0 98.0 98.0 100 97.8 100 100 100 100 100 100 97.7 100 100 100 100 100 100 100 100 1.000 .913 .953 .963 1.000 .955 1.000 1.000 1.000 1.000 1.000 1.000 .932 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000
Storyline Action-packed Storyline Character-driven Storyline Intricately-plotted Storyline Issue-oriented Storyline Plot-driven Storyline World-building 100 100 100 100 100 100 1.000 1.000 1.000 1.000 1.000 1.000
