Is a certain piece written by Shakespeare or is it not? This question and others,regarding different authors and a plethora of anonymous works, has been askedmultiple times but still remains unacknowledged for many cases.This paper presents a comparison of traditional and computer assisted approaches of Authorship Attribution Studies.
The main part of this work consists of chapter four, where the chances of computer assisted authorship attribution will be confronted with it's general challenges, after the most recent techniques are explained. Chapter 4.4 draws a line to forensic linguistics, another specific field of application, where authorship attribution becomes increasingly important.
The last chapter summarizes the key points of the paper and outlines the most important findings, concerning (computer assisted) authorship attribution in general and it's impact on literary history in particular.
Table of Contents
1. Introduction
2. Defining 'Author', 'Authorship' and 'Authorship Marker'
3. Authorship Attribution
3.1 Traditional Approach
3.2 Computer Assisted Approach
4. Computer Assisted Authorship Attribution
4.1 Quantitative Techniques
4.2. Challenges of CAAA
4.3 Chances of CAAA
4.4 Further Scope of Application
5. Conclusion
Objectives and Topics
This paper examines the methodologies of authorship attribution, focusing on the historical transition from traditional close-reading techniques to modern computer-assisted approaches. It aims to evaluate the effectiveness of computational tools in identifying stylistic markers and to determine whether these technologies can provide a reliable, universally applicable method for determining authorship in literary and forensic contexts.
- Comparison between traditional and computer-assisted authorship attribution (CAAA).
- Challenges associated with quantitative linguistic analysis and text processing.
- Evaluation of recent techniques like Part-of-Speech tagging and stylometrics.
- Potential applications of CAAA in forensics and cybercrime investigation.
- The future role of human-machine collaboration in authorship studies.
Excerpt from the Book
1. Introduction
"Attribution studies, in order to succeed, need a linguistic theory and methodology responsive to the fundamental feature of natural languages, that they weave together words of all kinds in order to create meaning" (Vickers 2009,135)
Is a certain piece written by Shakespeare or is it not? This question and others, regarding different authors and a plethora of anonymous works, has been asked multiple times but still remains unacknowledged for many cases.
Scholars of authorship attribution studies have attempted to solve this issue as long as written language exists. To do so, the work under discussion is generally compared with the corpus of works which assuredly derive from a certain author, in any characteristic with is considered distinctive.
Nevertheless, the opinions are deeply divided regarding both, the features and peculiarities which have be considered significant for authorship attribution and the methods which should be applied to determine, find and compare the authorship markers.
Summary of Chapters
1. Introduction: Outlines the historical necessity of authorship attribution and introduces the conflict between traditional qualitative analysis and modern computational methods.
2. Defining 'Author', 'Authorship' and 'Authorship Marker': Establishes theoretical definitions of authorship, distinguishing between executive, revisionary, declarative, and precursory roles to frame the study.
3. Authorship Attribution: Provides a historical context for attribution studies, differentiating between human-centric traditional close reading and the emerging field of linguistic processing.
4. Computer Assisted Authorship Attribution: Analyzes the practical application of quantitative techniques, discusses inherent challenges like sample size and text-length dependence, and explores potential solutions like POS tagging.
5. Conclusion: Synthesizes the main findings, suggesting that the future of the field lies in fusing computational tools with deep linguistic insights rather than replacing human expertise.
Keywords
Authorship Attribution, Stylometrics, Computer Assisted Authorship Attribution (CAAA), Forensic Linguistics, Natural Language Processing, Quantitative Analysis, Linguistic Markers, Part-of-Speech Tagging, Text Processing, Authorship Studies, Lexical Choices, Computational Linguistics, Shakespearean Attribution.
Frequently Asked Questions
What is the core focus of this research paper?
The paper explores the current state, challenges, and prospects of Computer Assisted Authorship Attribution (CAAA) as a modern alternative to traditional manual authorship identification.
What are the primary thematic fields covered?
The research integrates literary studies, computational linguistics, and forensic science to assess how authorship markers are identified and compared using software.
What is the main research objective?
The primary goal is to determine how computational methods can effectively model human language to achieve faster, reliable, and standardized results in identifying authors.
Which scientific methodology is primarily employed?
The author uses a comparative analytical methodology, evaluating existing literature and studies on quantitative techniques, stylometric levels, and natural language processing (NLP) tools.
What topics are discussed in the main part of the work?
The main section investigates quantitative techniques, the limitations of current algorithms, the impact of sample sizes, and how tools like Python and the Natural Language Toolkit (NLTK) can improve attribution accuracy.
Which keywords best describe this study?
The most relevant keywords include Authorship Attribution, CAAA, Forensic Linguistics, Stylometrics, and Computational Linguistics.
How does the author view the role of the 'executive author'?
The paper treats the author as a label for the person who performs the act of writing, while acknowledging that writing is rarely an isolated process and is influenced by diverse factors.
What is the significance of the excursus on forensic linguistics?
The excursus illustrates that challenges found in literary authorship studies, such as the need for reliable text analysis, are equally pressing in criminal law, particularly regarding cybercrime.
Is it expected that computers will replace human researchers?
The author concludes that total replacement is unlikely; instead, the future lies in a convergence where computers handle high-speed processing while humans provide linguistic and contextual expertise.
- Quote paper
- Lea Manthey (Author), 2014, Chances and Challenges of Computer Assisted Authorship Attribution, Munich, GRIN Verlag, https://www.hausarbeiten.de/document/287861
