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Bibliographische Detailangaben
Titel:Quantitative intertextuality
analyzing the markers of information reuse
Von: Christopher W. Forstall, Walter J. Scheirer
Person: Forstall, Christopher W.
ca. 20./21. Jahrhundert
Verfasser
aut
Scheirer, Walter J.
Hauptverfassende: Forstall, Christopher W. ca. 20./21. Jahrhundert (VerfasserIn), Scheirer, Walter J. ca. 20./21. Jahrhundert (VerfasserIn)
Format: Buch
Sprache:Englisch
Veröffentlicht: Cham Springer [2019]
Schlagworte:
Information Retrieval
Intertextualität
Intermedialität
Online-Zugang:http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=031448045&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA
http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=031448045&sequence=000003&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA
Beschreibung:xvii, 189 Seiten Illustrationen, Diagramme
ISBN:9783030234133
Internformat

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Datensatz im Suchindex

DE-BY-UBR_call_number 14/ST 302 F733
DE-BY-UBR_katkey 6149714
DE-BY-UBR_location UB Allgemeiner Lesesaal
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adam_text Contents Parti The Theory 1 What is QuantitativeIntertextuality?........................................................ 1.1 Introduction.......................................................................................... 1.2 Quantitative approaches....................................................................... 1.3 Authorship attribution and stylometry ............................................... 1.4 Text reuse.............................................................................................. 1.5 Synthesis of theory and practice......................................................... References...................................................................................................... 3 3 6 9 13 18 19 2 Statistical Learning as a Modelfor Intertextuality................................. 2.1 Theory and practice: a continuing relationship.................................. 2.2 Origins of intertextual theory............................................................... 2.3 Large-scale effects................................................................................. 2.4 Local effects.......................................................................................... 2.5 Other divisions....................................................................................... 2.6 A bottom-up model............................................................................... 2.7 The act of recognition........................................................................... 2.8 Intertextual origins — oral theory....................................................... 2.9 Expertise and pattern recognition ....................................................... 2.10 A general model for intertextuality..................................................... 2.11 The subjective experience of intertext................................................. 2.12 Where does intertext happen?............................................................. 2.13 Intertextuality and interpretive communities...................................... 2.14 The presence of the unsaid................................................................... 2.15 Machine learning and intertext ........................................................... References...................................................................................................... 23 23 26 28 29 31 32 33 35 37 38 40 41 43 45 47 49 xiii xjv Contents Part II The Practice 3 Lexical Matching: Text Reuse as Intertextuality.................................... 3.1 Words: The Basic Unit of Intertext...................................................... 3.2 Search Procedures.................................................................................. 3.3 Case Study: “Game of Thrones” and its Audience.............................. 3.4 Words as Features for Allusion Detection ........................................... 3.5 Additional Word-based Features........................................................... 3.6 Discussion.............................................................................................. References...................................................................................................... 55 55 57 58 62 69 74 75 4 Semantic Matching: Tracing Reuse by Meaning..................................... 79 4.1 The Meaning of a Text as an Intertextual Marker............................... 79 4.2 Case Study: Fiction from the Internet Writing Community Wattpad. 83 4.3 The Latent Semantic Indexing Approach............................................. 87 4.4 Computing Semantic Similarity............................................................. 90 4.5 Applications of Semantic Matching..................................................... 94 4.6 Discussion.............................................................................................. 99 4.7 Exercises ................................................................................................ 100 References........................................................................................................ 102 5 Sound Matching: Capturing Reuse in the Primitive Elements of Language ....................................................................................................... 105 5.1 Repetitive Sound as a Style Marker.......................................................105 5.2 Case study: Cowper’s Influence on Wordsworth..................................109 5.3 The Functional ո-gram Feature.............................................................Ill 5.4 Computing Relative Distance in the Feature Space of Sound............ 116 5.5 Open Set Influence Detection.................................................................120 5.6 A One-Class Methodology for Learning............................................... 121 5.7 Discussion..............................................................................................125 5.8 Exercises ................................................................................................127 References........................................................................................................128 6 Image Matching: Detecting the Reuse of Visual Elements......................133 6.1 What is Style in a Visual Sense?...........................................................133 6.2 Case study: Three Popular Memes .......................................................136 6.3 Histogram of Oriented Gradients...........................................................140 6.4 Nearest Neighbor Classification to Detect Reuse..................................143 6.5 Detecting Reuse in Meme Images and Rejecting Irrelevant Samples 146 6.6 Discussion..............................................................................................149 6.7 Exercises ................................................................................................151 References....................................................................................................... 152 7 Mcta-Matching: Combining Evidence From Heterogeneous Sources . 155 7.1 Combining Information in a Sensible Way...........................................155 7.2 Case study: The Self-Plagiarism of JonahLehrer................................ 158 Contents xv 7.3 Feature-level Fusion.............................................................................161 7.4 A Better Tool: W-SVM......................................................................... 167 7.5 Combining Hvidcnce Related to the Case Study..................................172 7.6 Discussion.............................................................................................175 7.7 Hxercises .............................................................................................. 176 References...................................................................................................... 177 8 Parting Thoughts ................................................................................. 181 8.1 What Have We Learned? ..................................................................... 181 8.2 Logical Next Steps l or Quantitative Intertextuality............................. 182 8.3 Building a Relationship with Psychology............................................ 185 References...................................................................................................... 187 Ibis book introduces quantitative intertextuality, a new approach to the algorithmic study of information reuse in text, sound and images. Employing a variety of tools from machine learning, natural language processing, and computer vision, readers will learn to trace patterns of reuse across diverse sources for scholarly work and practical applications. lhe respective chapters share highly novel methodological insights in order to guide the reader through the basics of intertextuality. In Part 1, “Theory”, the theoretical aspects of intertextuality are introduced, leading to a discussion of how they can be embodied by quantitative methods. In Part 2, “Practice”, specific quantitative methods are described to establish a set of automated procedures for the practice of quantitative intertextuality. Each chapter in Part 2 begins with a general introduction to a major concept (e.g., lexical matching, sound matching, semantic matching), followed by a case study (e.g., detecting allusions to a popular television show in tweets, quantifying sound reuse in Romantic poetry, identifying influences in fan faction by thematic matching), and finally the development of an algorithm that can be used to reveal parallels in the relevant contexts. Because this book is intended as a “gentle” introduction, the emphasis is often on simple yet effective algorithms for a given matching task. A set of exercises is included at the end of each chapter, giving readers the chance to explore more cutting-edge solutions and novel aspects to the material at hand. Additionally, the book’s companion website includes software (R and C++ library code) and all of the source data for the examples in the book, as well as supplemental content (slides, high-resolution images, additional results) that may prove helpful for exploring the different facets of quantitative intertextuality that are presented in each chapter. Given its interdisciplinary nature, the book will appeal to a broad audience. From practitioners specializing in forensics to students of cultural studies, readers with diverse backgrounds (e.g., in the social sciences, natural language processing, or computer vision) will find valuable insights.
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spellingShingle Forstall, Christopher W. ca. 20./21. Jahrhundert
Scheirer, Walter J. ca. 20./21. Jahrhundert
Quantitative intertextuality analyzing the markers of information reuse
Information Retrieval (DE-588)4072803-1 gnd
Intertextualität (DE-588)4114051-5 gnd
Intermedialität (DE-588)4605581-2 gnd
subject_GND (DE-588)4072803-1
(DE-588)4114051-5
(DE-588)4605581-2
title Quantitative intertextuality analyzing the markers of information reuse
title_auth Quantitative intertextuality analyzing the markers of information reuse
title_exact_search Quantitative intertextuality analyzing the markers of information reuse
title_full Quantitative intertextuality analyzing the markers of information reuse Christopher W. Forstall, Walter J. Scheirer
title_fullStr Quantitative intertextuality analyzing the markers of information reuse Christopher W. Forstall, Walter J. Scheirer
title_full_unstemmed Quantitative intertextuality analyzing the markers of information reuse Christopher W. Forstall, Walter J. Scheirer
title_short Quantitative intertextuality
title_sort quantitative intertextuality analyzing the markers of information reuse
title_sub analyzing the markers of information reuse
topic Information Retrieval (DE-588)4072803-1 gnd
Intertextualität (DE-588)4114051-5 gnd
Intermedialität (DE-588)4605581-2 gnd
topic_facet Information Retrieval
Intertextualität
Intermedialität
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