What’s in the brain that ink may character …. :  A quantitative narrative analysis of Shakespeare’s 154 sonnets for use in (Neuro-)cognitive poetics

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Abstract

In this theoretical paper, we would like to pave the ground for future empirical studies in Neurocognitive Poetics by describing relevant properties of Shakespeare’s 154 sonnets extracted via Quantitative Narrative Analysis. In the first two parts, we quantify aspects of the sonnets’ cognitive and affective-aesthetic features, as well as indices of their thematic richness, symbolic imagery, and semantic association potential. In the final part, we first demonstrate how the results of these quantitative narrative analyses can be used for generating testable predictions for empirical studies of literature. Second, we feed the quantitative narrative analysis data into a machine learning algorithm which successfully classifies the 154 sonnets into two main categories, i.e. the young man and dark lady poems. This shows how quantitative narrative analysis data can be combined with computational modeling for identifying those of the many quantifiable sonnet features that may play a key role in their reception.

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The role of transportation in the persuasiveness of public narratives.

Tim H. Clutton-Brock, T C Brock (2001)

Transportation was proposed as a mechanism whereby narratives can affect beliefs. Defined as absorption into a story, transportation entails imagery, affect, and attentional focus. A transportation scale was developed and validated. Experiment 1 (N = 97) demonstrated that extent of transportation augmented story-consistent beliefs and favorable evaluations of protagonists. Experiment 2 (N = 69) showed that highly transported readers found fewer false notes in a story than less-transported readers. Experiments 3 (N = 274) and 4 (N = 258) again replicated the effects of transportation on beliefs and evaluations; in the latter study, transportation was directly manipulated by using processing instructions. Reduced transportation led to reduced story-consistent beliefs and evaluations. The studies also showed that transportation and corresponding beliefs were generally unaffected by labeling a story as fact or as fiction.

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Moving beyond Kucera and Francis: a critical evaluation of current word frequency norms and the introduction of a new and improved word frequency measure for American English.

Marc Brysbaert, Boris New (2009)

Word frequency is the most important variable in research on word processing and memory. Yet, the main criterion for selecting word frequency norms has been the availability of the measure, rather than its quality. As a result, much research is still based on the old Kucera and Francis frequency norms. By using the lexical decision times of recently published megastudies, we show how bad this measure is and what must be done to improve it. In particular, we investigated the size of the corpus, the language register on which the corpus is based, and the definition of the frequency measure. We observed that corpus size is of practical importance for small sizes (depending on the frequency of the word), but not for sizes above 16-30 million words. As for the language register, we found that frequencies based on television and film subtitles are better than frequencies based on written sources, certainly for the monosyllabic and bisyllabic words used in psycholinguistic research. Finally, we found that lemma frequencies are not superior to word form frequencies in English and that a measure of contextual diversity is better than a measure based on raw frequency of occurrence. Part of the superiority of the latter is due to the words that are frequently used as names. Assembling a new frequency norm on the basis of these considerations turned out to predict word processing times much better than did the existing norms (including Kucera & Francis and Celex). The new SUBTL frequency norms from the SUBTLEX(US) corpus are freely available for research purposes from http://brm.psychonomic-journals.org/content/supplemental, as well as from the University of Ghent and Lexique Web sites.