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You searched for subject:(Algorithmic criticism). Showing records 1 – 3 of 3 total matches.

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University of Adelaide

1. Cuthbertson, Galen Mereki. An Algorithmic Criticism of Audience Manipulation in Christopher Marlowe’s The Massacre at Paris.

Degree: 2017, University of Adelaide

In this thesis, I apply computational stylistics methods to investigate the structural underpinnings of audience manipulation in Christopher Marlowe’s The Massacre at Paris. By engaging an iterative process of re-reading underpinned by novel methods taken from computational stylistics and algorithmic criticism, I argue that formal features of The Massacre evince an intricate and intensely practical approach to the manipulation of audience response. This reading casts new light on the theatrical viability of the play itself, while simultaneously asserting the strength of digital methods in the analysis of neglected, ambiguous, and so-called corrupt or mangled playtexts. I engage this project of algorithmic criticism in three stages. In Chapter 1, I begin with a traditional reading of the multiple audiences of The Massacre. Building on Julia Briggs’ reading of “ritualised violence” (259), I identify a structure of ‘fractal’ self-similarity across the scenes of the play. With particular attention given to the spectatorial inset of scene xxi, and the critical effects of such metatheatrical modes of presentation across the entire play, I suggest that key features of the surviving text gesture towards a self-conscious realisation of genre and theatrical artifice. Moreover, I argue that this self- conscious realisation is fundamentally intertwined with, and energised by, the risk of theatrical failure. The apparent effect, I argue, is a mode of neutrality and double vision on the part of the text itself: the generation of an audience which, far from being overtly manipulated, is encouraged to freely interpret the play’s action. In Chapter 2, I deploy methods of computational stylistics to detect patterns of sentiment and syntactic fracturing in a time-series analysis of the playtext. Looking first at the presence and absence of basic syntactic coherence surrounding stage events, and later at the shifting status of positive and negative ‘sentiment’ language across the many character utterances, I suggest that the apparent audience freedom identified in the previous chapter may, in fact, be severely curtailed by subtler linguistic trends. Drawing on Evelyn Tribble’s notion of the “cognitive ecology” of the theatre (151), I argue that the clusters of linguistic fracturing evince a deeply pragmatic approach to the sociality of audience and stage. In Chapter 3, I engage with the play at its most abstract level. By setting aside the analysis of spoken utterances entirely and examining character interactions, I develop a model of the play’s changing social network. Here I find evidence that the structural features of the playtext’s character network(s) is itself vital to the strategic manipulation of audience response. Looking first at the shape of the network—its density, clustering, and the relative centrality of its key characters—and then at the dynamics responsible for the shifting dynamics of this network over time, I argue that the violent action of the play has a decisive impact on the generation, direction, and… Advisors/Committee Members: Potter, Lucy (advisor), School of Humanities : English and Creative Writing (school).

Subjects/Keywords: Algorithmic criticism; computational stylistics; digital humanities; early modern theatre; Marlowe; spectacle violence; social network analysis

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Cuthbertson, G. M. (2017). An Algorithmic Criticism of Audience Manipulation in Christopher Marlowe’s The Massacre at Paris. (Thesis). University of Adelaide. Retrieved from http://hdl.handle.net/2440/119677

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Cuthbertson, Galen Mereki. “An Algorithmic Criticism of Audience Manipulation in Christopher Marlowe’s The Massacre at Paris.” 2017. Thesis, University of Adelaide. Accessed December 15, 2019. http://hdl.handle.net/2440/119677.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Cuthbertson, Galen Mereki. “An Algorithmic Criticism of Audience Manipulation in Christopher Marlowe’s The Massacre at Paris.” 2017. Web. 15 Dec 2019.

Vancouver:

Cuthbertson GM. An Algorithmic Criticism of Audience Manipulation in Christopher Marlowe’s The Massacre at Paris. [Internet] [Thesis]. University of Adelaide; 2017. [cited 2019 Dec 15]. Available from: http://hdl.handle.net/2440/119677.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Cuthbertson GM. An Algorithmic Criticism of Audience Manipulation in Christopher Marlowe’s The Massacre at Paris. [Thesis]. University of Adelaide; 2017. Available from: http://hdl.handle.net/2440/119677

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Leiden University

2. Verhaar, F, P.A. Affordances and limitations of algorithmic criticism.

Degree: 2016, Leiden University

Humanities scholars currently have access to unprecedented quantities of machine-readable texts, and, at the same time, the tools and the methods with which we can analyse and visualise these texts are becoming more and more sophisticated. As has been shown in numerous studies, many of the new technical possibilities that emerge from fields such as text mining and natural language processing can have useful applications within literary research. Computational methods can help literary scholars to discover interesting trends and correlations within massive text collections, and they can enable a thoroughly systematic examination of the stylistic properties of literary works. While such computer-assisted forms of reading have proven invaluable for research in the field of literary history, relatively few studies have applied these technologies to expand or to transform the ways in which we can interpret literary texts. Based on a comparative analysis of digital scholarship and traditional scholarship, this thesis critically examines the possibilities and the limitations of a computer-based literary criticism. It argues that quantitative analyses of data about literary techniques can often reveal surprising qualities of works of literature, which can, in turn, lead to new interpretative readings. Advisors/Committee Members: Supervisors: A.H. van der Weel, K.H. van Dalen-Oskam.

Subjects/Keywords: Digital humanities; Algorithmic criticism; Text mining; Literary criticism; Digital humanities; Algorithmic criticism; Text mining; Literary criticism

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Verhaar, F, P. A. (2016). Affordances and limitations of algorithmic criticism. (Doctoral Dissertation). Leiden University. Retrieved from http://hdl.handle.net/1887/43241

Chicago Manual of Style (16th Edition):

Verhaar, F, P A. “Affordances and limitations of algorithmic criticism.” 2016. Doctoral Dissertation, Leiden University. Accessed December 15, 2019. http://hdl.handle.net/1887/43241.

MLA Handbook (7th Edition):

Verhaar, F, P A. “Affordances and limitations of algorithmic criticism.” 2016. Web. 15 Dec 2019.

Vancouver:

Verhaar, F PA. Affordances and limitations of algorithmic criticism. [Internet] [Doctoral dissertation]. Leiden University; 2016. [cited 2019 Dec 15]. Available from: http://hdl.handle.net/1887/43241.

Council of Science Editors:

Verhaar, F PA. Affordances and limitations of algorithmic criticism. [Doctoral Dissertation]. Leiden University; 2016. Available from: http://hdl.handle.net/1887/43241


Linköping University

3. Barakat, Arian. What makes an (audio)book popular?.

Degree: The Division of Statistics and Machine Learning, 2018, Linköping University

Audiobook reading has traditionally been used for educational purposes but has in recent times grown into a popular alternative to the more traditional means of consuming literature. In order to differentiate themselves from other players in the market, but also provide their users enjoyable literature, several audiobook companies have lately directed their efforts on producing own content. Creating highly rated content is, however, no easy task and one reoccurring challenge is how to make a bestselling story. In an attempt to identify latent features shared by successful audiobooks and evaluate proposed methods for literary quantification, this thesis employs an array of frameworks from the field of Statistics, Machine Learning and Natural Language Processing on data and literature provided by Storytel - Sweden’s largest audiobook company. We analyze and identify important features from a collection of 3077 Swedish books concerning their promotional and literary success. By considering features from the aspects Metadata, Theme, Plot, Style and Readability, we found that popular books are typically published as a book series, cover 1-3 central topics, write about, e.g., daughter-mother relationships and human closeness but that they also hold, on average, a higher proportion of verbs and a lower degree of short words. Despite successfully identifying these, but also other factors, we recognized that none of our models predicted “bestseller” adequately and that future work may desire to study additional factors, employ other models or even use different metrics to define and measure popularity. From our evaluation of the literary quantification methods, namely topic modeling and narrative approximation, we found that these methods are, in general, suitable for Swedish texts but that they require further improvement and experimentation to be successfully deployed for Swedish literature. For topic modeling, we recognized that the sole use of nouns provided more interpretable topics and that the inclusion of character names tended to pollute the topics. We also identified and discussed the possible problem of word inflections when modeling topics for more morphologically complex languages, and that additional preprocessing treatments such as word lemmatization or post-training text normalization may improve the quality and interpretability of topics. For the narrative approximation, we discovered that the method currently suffers from three shortcomings: (1) unreliable sentence segmentation, (2) unsatisfactory dictionary-based sentiment analysis and (3) the possible loss of sentiment information induced by translations. Despite only examining a handful of literary work, we further found that books written initially in Swedish had narratives that were more cross-language consistent compared to books written in English and then translated to Swedish.

Subjects/Keywords: Audiobooks; Bestsellers; Algorithmic Criticism; Large-scale Literary Analysis; Natural Language Processing; Gaussian Processes; Topic Modeling; Other Computer and Information Science; Annan data- och informationsvetenskap; Probability Theory and Statistics; Sannolikhetsteori och statistik

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Barakat, A. (2018). What makes an (audio)book popular?. (Thesis). Linköping University. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-152871

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Barakat, Arian. “What makes an (audio)book popular?.” 2018. Thesis, Linköping University. Accessed December 15, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-152871.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Barakat, Arian. “What makes an (audio)book popular?.” 2018. Web. 15 Dec 2019.

Vancouver:

Barakat A. What makes an (audio)book popular?. [Internet] [Thesis]. Linköping University; 2018. [cited 2019 Dec 15]. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-152871.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Barakat A. What makes an (audio)book popular?. [Thesis]. Linköping University; 2018. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-152871

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

.