Диссертация (1137487), страница 24
Текст из файла (страница 24)
7–11.60. Blessing A. и др. An End-to-end Environment for Research Question-Driven EntityExtraction and Network Analysis // Proceedings of the Joint SIGHUM Workshop onComputational Linguistics for Cultural Heritage, Social Sciences, Humanities andLiterature. Vancouver, Canada: Association for Computational Linguistics, 2017. P.
57–67.61. Blondel V.D. и др. Fast unfolding of communities in large networks // Journal ofStatistical Mechanics: Theory and Experiment. 2008. Vol. 10. P. 1008.62. Bodrova A., Bocharov V. Relationship Extraction from Literary Fiction [Электронныйресурс].2014.URL:http://www.dialog-21.ru/digests/dialog2014/materials/pdf/BodrovaAABocharovVV.pdf (дата обращения:30.08.2018).63. Bogdanov A.
Skorinkin D., Dzhumaev S., Starostin A. Anaphora analysis based onABBYY Compreno linguistic technologies // Компьютерная лингвистика иинтеллектуальные технологии: По материалам ежегодной Международнойконференции «Диалог» (Бекасово, 4 — 8 июня 2014 г.). Москва: Изд. РГГУ, 2014.С. 89–102.64. Bonch-Osmolovskaya А., Skorinkin D., Sidorova E. Verbal Identity of a FictionalCharacter: a Quantitative Study with a Machine Learning Experiment // DigitalHumanities 2016.
Conference Abstracts. Kraków: Jagiellonian University, 2016. P. 747–749.65. Bonch-Osmolovskaya A., Skorinkin D. Text mining War and Peace: Automaticextraction of character traits from literary pieces // Digital Scholarship in the Humanities.2017. Vol. 32. suppl_1. P. i17–i24.66. Brooke J., Hammond A., Hirst G. Using models of lexical style to quantify free indirectdiscourse in modernist fiction // Digital Scholarship in the Humanities.
2017. Vol. 32. №2. P. 234–250.67. Burrows J. ‘Delta’: a Measure of Stylistic Difference and a Guide to Likely Authorship //Literary and Linguistic Computing. 2002. Vol. 17. № 3. P. 267–287.68. Burrows J.F. Computation into criticism: a study of Jane Austen’s novels and anexperiment in method.
Oxford: Clarendon Press, 1987.69. Chatman S. Story and Discourse: Narrative Structure in Fiction and Film. Ithaca: CornellUniversity Press, 1978. 277 p.11570. Chaturvedi S., Srivastava S., Daume H., Dyer C. Modeling Dynamic RelationshipsBetween Characters in Literary Novels // CoRR. 2015.71. Clay G.R. Tolstoy’s Phoenix: From Method to Meaning in War and Peace. Evanston:Northwestern University Press, 1998. 142 p.72. Culpeper J. Keywords and Characterization: An Analysis of Six Characters in Romeo andJuliet // Digital Literary Studies: Corpus Approaches to Poetry, Prose, and Drama. NewYork, London: Taylor & Francis, 2014.
P. 9–34.73. Dalen-Oskam K. van, Zundert J. van. Delta for Middle Dutch—Author and CopyistDistinction in Walewein // Literary and Linguistic Computing. 2007. Vol. 22. № 3. P.345–362.74. Dittenberger W. Sprachliche Kriterien für die Chronologie der Platonischen Dialoge //Hermes. 1881. Vol. 16. № 3. P. 321–345.75. Eder J., Jannidis F., Schneider R. Characters in Fictional Worlds: UnderstandingImaginary Beings in Literature, Film, and Other Media. Berlin: De Gruyter, 2010.76. Eder M.
Does size matter? Authorship attribution, small samples, big problem // DigitalScholarship in the Humanities. 2015. Vol. 30. № 2. P. 167–182.77. Eder M. Style-Markers in Authorship Attribution A Cross-Language Study of theAuthorial Fingerprint // Studies in Polish Linguistics. 2011. № 6. P. 99–114.78.
Eder M. Visualization in stylometry: Cluster analysis using networks // DigitalScholarship in the Humanities. 2017. Vol. 32. № 1. P. 50–64.79. Eder M., Rybicki J. PCA, Delta, JGAAP and Polish Poetry of the 16th and the 17thCenturies: Who Wrote the Dirty Stuff?’ // Digital Humanities 2009: ConferenceAbstracts. : MD College Park, 2009. P.
242–244.80. Elson D.K., Dames N., McKeown K.R. Extracting Social Networks from Literary Fiction// Proceedings of the 48th Annual Meeting of the Association for ComputationalLinguistics ACL ’10. Stroudsburg, PA, USA: Association for Computational Linguistics,2010. P. 138–147.81. Fischer F., Göbel M., Kampkaspar D., Kittel C., Trilcke P. Network Dynamics, PlotAnalysis: Approaching the Progressive Structuration of Literary Texts // DigitalHumanities 2017. Book of Abstracts. Montréal: McGill University, 2017. (a)82.
Fischer F., Göbel M., Milling C., Orlova T., Palchikov G., Pavlova I., Pozdniakov I.,Skorinkin D., Trilcke P. Life(!) on Stage: Building an interface for the network analysisof TEI-encoded drama corpora // TEI Conference and Members’ Meeting 2017 Book ofAbstracts Vol. 16.
Victoria: University of Victoria, 2017. (b)83. Fischer F., Trilcke P., Kittel C., Milling C., Skorinkin D. To Catch a Protagonist:Quantitative Dominance Relations in German Language Drama (1730–1930) // Digital116Humanities 2018: Book of Abstracts / Libro de resúmenes. Mexico : Red de HumanidadesDigitales A. C., 2018. P. 193-201.84. Fisseni B., Kurji A., Löwe B. Annotating with Propp’s Morphology of the Folktale:reproducibility and trainability // Literary and Linguistic Computing.
2014. Vol. 29. № 4.P. 488–510.85. Forstall C., Galli Milic L., Damien N. Approaches to Thematic Classification for LatinEpic // Digital Humanities 2016: Conference Abstracts. Kraków: Jagiellonian University,2016. P. 508–510.86. Forster E.M. Aspects of the Novel. New York: Harcourt, Brace and company, 1927.87. Franzini, G., Kestemont, M., Rotari, G., Jander, M., Ochab, J.K., Franzini, E., Byszuk, J.,Rybicki, J. Attributing Authorship in the Noisy Digitized Correspondence of Jacob andWilhelm Grimm // Frontiers in Digital Humanities. 2018. Vol.
5. P. 4.88. Freytag G. Die Technik des Dramas. Leipzig: Verlag von S. Hirzel. 1905 (1863)[Электронный ресурс]. URL: https://www.gutenberg.org/files/50616/50616-h/50616h.htm (дата обращения: 30.09.2018).89. García A. M., Martín J. C. Function Words in Authorship Attribution Studies // Literaryand Linguistic Computing.
2007. Vol. 22. № 1. P. 49–66.90. Gleiser P. M. How to become a superhero // Journal of Statistical Mechanics: Theory andExperiment. 2007. Vol. 9. P. 09020.91. Grayson S. и др. The sense and sensibility of different sliding windows in constructingco-occurrence networks from literature // Computational History and Data-DrivenHumanities: Second IFIP WG 12.7 International Workshop, CHDDH 2016, Dublin,Ireland, May 25, 2016, Revised Selected Papers 2. : Springer International Publishing,2016. P.
65–77.92. Hołobut A., Rybicki J., Woźniak M. Old questions, new answers : computational stylisticsin audiovisual translation research // Audiovisual translation : research and use. Frankfurtam Mein: Peter Lang Edition, 2017. P. 203–216.93. Hoover D.L., Culpeper J., O’Halloran K. Digital Literary Studies: Corpus Approaches toPoetry, Prose, and Drama. New York, London: Taylor & Francis, 2014.94. Hoover D.L. The microanalysis of style variation // Digital Scholarship in the Humanities.2017. Vol.
32. № suppl_2. P. ii17–ii30.95. Hoover D.L. Testing Burrows’s Delta // Literary and Linguistic Computing. 2004. Vol.19. № 4. P. 453–475.96. Hume R.D. Money in Jane Austen // The Review of English Studies. 2013. Vol. 64. №264. P. 289–310.11797. Jacomy M. Venturini T., Heymann S., Bastian M. ForceAtlas2, a Continuous GraphLayout Algorithm for Handy Network Visualization Designed for the Gephi Software //PL o S One. 2014. Vol. 9. № 6.98. Jannidis F., Lauer G.
Burrows’s Delta and Its Use in German Literary History // DistantReadings. Topologies of German Culture in the Long Nineteenth Century Studies inGerman Literature Linguistics and Culture. / под ред. M. Erlin, L. Tatlock. Rochester:Camden House, 2014. P. 29–54.99. Jockers M.L., Witten D.M., Criddle C.S. Reassessing authorship of the Book of Mormonusing delta and nearest shrunken centroid classification // Literary and LinguisticComputing. 2008. Vol. 23. № 4. P.
465–491.100. Jockers M. Revealing Sentiment and Plot Arcs with the Syuzhet Package Matthew L.Jockers[Электронныйресурс].URL:http://www.matthewjockers.net/2015/02/02/syuzhet/ (дата обращения: 23.06.2018).101. Juola P., Baayen R.H. A Controlled-corpus Experiment in Authorship Identification byCross-entropy // Literary and Linguistic Computing. 2005. Vol. 20. № Suppl. P. 59–67.102. Knuth D.E. The Stanford GraphBase: A Platform for Combinatorial Computing. NewYork, NY, USA: ACM, 1993.103. Lee J., Wong T.
Conversational Network in the Chinese Buddhist Canon // OpenLinguistics. 2016. Vol. 2. № 1.104. Lee J., Yeung C.Y. Extracting Networks of People and Places from Literary Texts //Proceedings of 26th Pacific Asia Conference on Language, Information, and Computation(PACLIC). Bali: Faculty of Computer Science, Universitas Indonesia, 2012. P. 209–218.105. Liu M. et al.
Literary intelligence analysis of novel protagonists’ personality traits anddevelopment // Digital Scholarship in the Humanities. 2018.106. Lutoslawski W. The Origin and Growth of Plato’s Logic // Mind. 1898. Vol. 7. № 27. P.419–423.107. McCarty W. Knowing … : Modeling in Literary Studies// A Companion to DigitalLiterary Studies. Oxford: Blackwell, 2008.108.
![](https://s.studizba.com/z.php?f=/templates/si/i/noavatar.png&w=100&h=100&t=1"){kind=avatar}
