Observations on the Intertextuality of Selected Abhidharma Texts Preserved in Chinese Translation
Bibliographic Data
| ID | 3280931 |
|---|---|
| Authors | Sebastian Nehrdich (University of California, Berkeley, corresponding author) |
| Year | 2023 |
| Volume | 14 |
| Issue | 7 |
| Pages | 911 |
| Publication date | 2023-07-14 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Religions (JOURNAL) |
| Journal identifiers | ISSN: 2077-1444 • E-ISSN: 2077-1444 |
| Publisher | MDPI AG (PUBLISHER • IT) |
| DOI | 10.3390/rel14070911 |
| OpenAlex | W4384338397 |
| Language | EN |
| Citations received | 1 |
| References cited | 7 |
Textual reuse is a fundamental characteristic of traditional Buddhist literature preserved in various languages. Given the sheer volume of preserved Buddhist literature and the often-unmarked instances of textual reuse, the thorough analysis and evaluation of this material without computational assistance are virtually impossible. This study investigates the application of computer-aided methods for detecting approximately similar passages within Xuanzang's translation corpus and a selection of Abhidharma treatises preserved in Chinese translation. It presents visualizations of the generated network graphs and conducts a detailed examination of patterns of textual reuse among selected works within the Abhidharma tradition. This study demonstrates that the general picture of textual reuse within Xuanzang's translation corpus and the selected Abhidharma texts, based on computational analysis, aligns well with established scholarship. Thus, it provides a robust foundation for conducting more detailed studies on individual text sets. The methods employed in this study to create and analyze citation network graphs can also be applied to other texts preserved in Chinese and, with some modifications, to texts in other languages
Archaeology · Art · Buddhism · Citation · Intertextuality · Linguistics · Literature · Natural language processing · Reuse · World Wide Web · Chemistry · Computer Science · History · Natural Language Processing Techniques · Philosophy · Topic Modeling · Artificial Intelligence
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A BLAST-based, Language-agnostic Text Reuse Algorithm with a Markus Implementation and Sequence Alignment Optimized for Large Chinese Corpora
Drawing Out the Essentials
| Citations per year | 0.33 |
|---|---|
| Citation span | 2023 - 2023 (1) |
| Highly cited | No |