Citation-based Plagiarism Detection

1. Front Matter

   Pages I-XXVI

   PDF

2. Introduction

   • Bela Gipp

   Pages 1-7

3. Plagiarism Detection

   • Bela Gipp

   Pages 9-42

4. Citation-based Document Similarity

   • Bela Gipp

   Pages 43-55

5. Citation-based Plagiarism Detection

   • Bela Gipp

   Pages 57-88

6. Prototype: CitePlag

   • Bela Gipp

   Pages 89-99

7. Quantitative and Qualitative Evaluation

   • Bela Gipp

   Pages 101-201

8. Summary & Future Work

   • Bela Gipp

   Pages 203-221

9. Back Matter

   Pages 223-350

   PDF

Plagiarism is a problem with far-reaching consequences for the sciences. However, even today’s best software-based systems can only reliably identify copy & paste plagiarism. Disguised plagiarism forms, including paraphrased text, cross-language plagiarism, as well as structural and idea plagiarism often remain undetected. This weakness of current systems results in a large percentage of scientific plagiarism going undetected. Bela Gipp provides an overview of the state-of-the art in plagiarism detection and an analysis of why these approaches fail to detect disguised plagiarism forms. The author proposes Citation-based Plagiarism Detection to address this shortcoming. Unlike character-based approaches, this approach does not rely on text comparisons alone, but analyzes citation patterns within documents to form a language-independent "semantic fingerprint" for similarity assessment. The practicability of Citation-based Plagiarism Detection was proven by its capability to identify so-far non-machine detectable plagiarism in scientific publications.

• Citation analysis
• Citation-based Plagiarism Detection
• Detection approaches
• Plagiarism detection
• Plagiarism forms

• Department of Statistics, UC Berkeley, Berkeley, USA

  Bela Gipp

Bela Gipp is a postdoctoral researcher at the University of California, Berkeley.

Policies and ethics