Smells like Teen Spirit: An Exploration of Sensorial Style in Literary Genres (2022)

Abstract: It is well recognized that sensory perceptions and language have interconnections through numerous studies in psychology, neuroscience, and sensorial linguistics. Set in this rich context we ask whether the use of sensorial language in writings is part of linguistic style? This question is important from the view of stylometrics research where a rich set of language features have been explored, but with insufficient attention given to features related to sensorial language. Taking this as the goal we explore several angles about sensorial language and style in collections of lyrics, novels, and poetry. We find, for example, that individual use of sensorial language is not a random phenomenon; choice is likely involved. Also, sensorial style is generally stable over time - the shifts are extremely small. Moreover, style can be extracted from just a few hundred sentences that have sensorial terms. We also identify representative and distinctive features within each genre. For example, we observe that 4 of the top 6 representative features in novels collection involved individuals using olfactory language where we expected them to use non-olfactory language.

## introduction sensory perceptions shape how we use language and communicate @xcite . when we use sensorial words (i.e. words with meanings connected to our senses) like fuzzy or stinky, besides communicating sensorial experiences these also stimulate perceptual systems in the recipient's mind @xcite . the space of senses -sometimes called the "aristotelian" senses @xcite , include the five modalities: visual, auditory, haptic, gustatory, and olfactory. relatively recently, linguistics and psychologists have added a sixth sense -interoception @xcite . this refers to the perception of sensations from inside the body, both physical such as hunger and pain, and emotional, such as joy. this sensory space has been the basis of much prior research. sensorial linguistics is about studying how language relates to the senses. a key focus has been to study how different sensorial experiences and perceptions are packaged into linguistic units @xcite . researchers have looked at how some senses dominate in language @xcite , how sensorial language varies across lexical categories @xcite and how sensory experiences influence sensorial language @xcite . however, the domain of sensorial linguistics is still nascent with many unexplored questions. stylometrics: as individuals grow, besides consciously learning a vocabulary they also develop a linguistic style. some stylistic elements may be acquired subconsciously and others by choice. stylistic choices can reflect the individual's social reality or affective state @xcite . several categories of stylistic features have been identified, such as the use of function words and language complexity @xcite . stylometrics is important for goals such as author attribution and affect classification. style in sensorial language use: a key limitation in stylometrics is that linguistic style around sensorial language has not been studied systematically. a person who wants to express being depressed has several word choices. she could use "sad" or the less frequent "downcast". her propensity to choose one or the other may be considered as part of her linguistic style. consider a cloudy scene. a person may use visual language focusing on color, and say "the clouds are white". another may use haptic language focusing on texture, "the clouds are fluffy". while sensorial language is clearly important for communication, we do not yet know if there are distinguishable patterns in sensory language use at the level of individuals, texts, etc. this gap in stylometrics motivates us to ask the following about sensorial language style: in the 2010 animated film 'despicable me', the character of agnes hugs a unicorn and says "it is so fluffy". one reason why this quote acquired somewhat of a meme status is because it subverted audience expectations of a more visual word like "pretty" or "white" to describe the unicorn. instead she opts for the more unexpected haptic word "fluffy". this substitution of visual language for haptic, a synaesthesia, might indicate that agnes' perceives the world in a more tactile manner rather than in a visual way. in order to assess if this is a stylistic tendency, we can examine all of agnes' language use and ask the general question: to what extent does she use haptic language in contexts where we generally expect visual language? we can ask similar questions related to each combination of expected versus observed sensory modalities. observations for all combinations, including the homogeneous non-synaesthesia ones, are accumulated to form agnes' (or any other individual's, group's or genre's) sensory style representation. terminology and notation: more formally, we consider a sentence to be a "sensorial sentence" if it has at least one word or phrase that appears in a sensorial lexicon. further, we define a "sensefocused sentence" to be a sensorial sentence with a single sensorial term selected as focus term. thus, if a sensorial sentence has n sensorial terms then we derive from it n sense-focused sentences. assume s @xmath0, s i2 , ..., s in } is the set of n sense-focused sentences identified from the writings of individual @xmath1. let @xmath2, v, i, o, g, a} represent the modalities: haptic, visual, interoceptive, olfactory, gustatory, auditory respectively. using n to represent concepts that are "not-sensorial" we define c as: @xmath3. we also define two functions. f (ŝ ij ) is a sensory lexicon lookup function that returns the sensorial category @xmath4. e.g., given the sensorial sentence "the unicorn is white and fluffy", we have two sense-focused sentences s ij and s ik corresponding to the two sensorial terms, ŝij and ŝik . for s ij with the focus term "white" f (ŝ ij ) will return v . for s ik with focus term "fluffy" it will return h. the second function we define is m (s ij ) which returns the "expected" modality @xmath5.1. calculating observed to expected ratios: we represent an individual's sense-focused sentences as a list of length |s i |. each entry is a pair of expected and observed modalities of the form [(m (s ij ), (f (ŝ ij )]. for observed modality @xmath6, the observed to expected ratio α xy i for individual i is: note that these ratios are the informative units of sensorial style. for example, if the ratio is 1 when x and y are the same modality, a homogeneous combination, then the individual's use of that modality is highly aligned with general expectation. on the other hand, if it is close to 0 then she deviates considerably from the expected use of modality x, i.e. there is greater synaesthesia. style vectors: for each @xmath7, we then concatenate its 6 ratios into a vector of the form: we can now define the sensorial style vector u i of @xmath8, one for each expected modality. the size of u i is x × @xmath9. given a sense-focused sentence, function m returns the expected modality @xmath10. we leverage roberta-mlm foot_0 as a standin for general english language usage. roberta is a transformer based language model pre-trained on 160 gb of data @xcite . prior works like @xcite and @xcite have shown that language models learn the norms of the language on which they are trained. this makes them ideal for our task. we mask the focus sensorial words in our sentences and input them to the model. roberta returns the probabilities for all the words in its vocabulary at each masked location. probabilities represent likelihood of appearance of the words at that location. we use these probabilities to identify the expected sense modality at each masked location as follows. let @xmath11, p 1 ), (w 2 , p 2 ) . . . (w n , p n )} be the ranked set of words returned by roberta for a masked location (location of focus sensorial term) in s ij ; top ranked has highest probability. using f (w k ), we lookup the sense for each word in the top 100. we combine this information to get an aggregate probability score π(c, s ij ) for each modality c as follows: for greater confidence we only include s ij in our analysis if its majority modality has π(c, s ij ) > 0.5. we then define in essence, m (s ij ) returns the expected modality with the highest aggregate probability for the focused sense word in s ij as determined using roberta. we use the sensorimotor norms lexicon published recently @xcite which has 39,954 concepts from the english language. brysbaert et al. estimates that the average adult lexicon is composed of approximately 42, 000 words. therefore this lexicon approximates a significant majority of everyday english. ## datasets we analyze 3 literary genres -novels, poems, music lyrics. compared to poems and lyrics, novels can span tens of thousands of sentences. additionally, novels and poetry are generally associated with a single author. lyrics are sometimes collaborations, however, we assume an artist would not perform a song that is in a style they do not like. thus, we assume music lyrics to be a reflection of the artist's style. novels: we collected english language novels from the domestic fiction genre of project gutenberg foot_2 . there were 317 works written by 130 authors, with the earliest by henry fielding from the early 18 th century and the latest by rebecca west from the mid-20 th century. lyrics: we collected songs that were listed on the billboard hot 100 charts, 1963 to 2021 (inclusive). this weekly chart ranking of song popularity is considered the industry standard @xcite . we assume the first time a song is listed to be its year of production. we obtained song lyrics using the genius api foot_3 . there are 20, 785 song lyrics. poetry: following works like @xcite , we used the corpus of poems available on the poetry foundation's foot_4 website. to make this dataset more comparable to the lyrics dataset, we only included works published after 1963. ## case study: sensorial style in lyrics as a small illustration, we explore how sensorial style varies across different songs composed by the same artist. we consider all 962 artists who had at least 5 songs in the hot 100 and extract a sensorial vector for each song. we then measure the average pair-wise cosine similarity (self similarity) amongst the songs of each artist. almost 80% of the artists had an average self @xmath12.70. only two artists had a self @xmath13.50. the rapper nf was the most consistent artist with an average self similarity of 0.93. conversely, the least consistent artist was the rock musician tommy james with an average similarity of 0.42. for example, in the song "when i grow up", nf used auditory language non-synaesthetically in 85.7% of the cases and for the song "no name" this happened in 76.9% of the cases. the similarity between these two songs was over 95%. in contrast, "nothing to hide" and "ball and chain" by tommy james' had a similarity of 0.32. in "ball and chain", the artist uses visual language in all the instances where it was expected. however in "nothing to hide", he uses interoceptive language synaesthetically instead of visual in about 57% of the cases. this case study demonstrates a method for exploring sensorial style and their variations across writings at the individual level. ## related work there are no directly comparable studies examining sensorial style for large numbers of individuals that consider interoception. instead we briefly review closely allied topics. sensorial language: sensorial language is not uniformly distributed across the six sensory modalities as reflected in sensorial lexicons, such as the one we use @xcite . this is also observed in large text collections. in their analysis of 8 million words from around 7,000 english texts @xcite found over 28,000 visual descriptions and only 78 referring to the olfactory modality. similar findings for multiple corpora are observed in @xcite . our results are consistent with these prior works. sensorial language, the brain & emotion: the salience of sensorial words is known to be highly correlated with the volumes of cortical activation in the brain @xcite . @xcite show that there is directionality to how senses are substituted for each other. @xcite found that gustatory and olfactory words (e.g., 'stinky', 'delicious') are on average more emotionally valenced than visual and auditory words and these also appear in more emotionally valenced sentences. @xcite , show that alterations in mental states have a direct effect on perception; specifically, that depression directly impacts how the color blue was perceived. @xcite , found a decrease in the novelist iris murdoch's use of olfactory language following her diagnosis of depression and alzheimer's. we credit this study for providing us with the hint that sensorial language may lead to a sensorial style. we take their sensorial style analysis forward with larger collections of authors, several genres and a more informative representation of sensorial style. ## limitations and conclusions we have shown that individuals have sensorial language style and that this sensorial style is a non random phenomenon for novelists and musicians and therefore is likely developed intentionally. interestingly, we also found that it takes just a few hundred sentences to extract stable sensorial style representations. we also show that sensorial style in lyrics largely stable over time; the average similarity decreases at a rate of 3.37×10 -4 per year. additionally, we show that sensorial style vectors seem to perform well at genre identification. the performance was high (> 0.90), however, it was not close to perfect as with other style representations. the question about how sensorial style representations can be improved to increase performance requires further investigation. our study is limited in that our method relies heavily on the underlying @xcite lexicon, and as with similar studies, is only as good as the lexicon. additionally, we assume that each term is associated with a single sensorial modality. however, as research in psychology and neurology has shown, sensorial language is cross-modal. we leave this analysis to future work. in summary, we take a first step towards showing that sensorial style has a legitimate role in stylometrics research.