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Analyzing large text data for vocabulary profiling in corpus-based studies of academic discourse
Ismail Xodabande1, Mahmood Reza Atai1, Mohammad R Hashemi1
1Department of Foreign Languages, Kharazmi University, Tehran, Iran.
Researchers developed a new protocol for academic vocabulary profiling using a large 278-million-word corpus. This method efficiently analyzes academic texts, creating specialized word lists for fields like chemistry and biology.
Area of Science:
- Corpus Linguistics
- Academic Discourse Analysis
- Lexicography
Background:
- Academic discourse analysis requires efficient methods for handling large text corpora.
- Existing tools may struggle with the scale of data typical in academic fields.
- Vocabulary profiling is crucial for understanding and teaching academic language.
Purpose of the Study:
- To introduce a scalable protocol for vocabulary profiling of large academic corpora.
- To enhance corpus-based studies of academic discourse.
- To identify and categorize vocabulary suitable for academic use.
Main Methods:
- Developed a systematic protocol for compiling and analyzing a large academic corpus (278 million words).
- Adapted corpus linguistics tools for efficient handling of extensive text data.
- Employed advanced lexical analysis techniques for vocabulary identification.
Main Results:
- Successfully created a mid-frequency vocabulary list with high relevance to chemistry (6.4% coverage).
- Demonstrated specialized coverage in related fields like biology and life sciences (2.5-3%).
- Observed significantly lower coverage in general corpora, confirming the list's specialized nature.
Conclusions:
- The developed protocol offers a scalable solution for academic vocabulary profiling.
- The resulting vocabulary lists have pedagogical value for curriculum design and educational resources in specialized academic settings.
- This research advances vocabulary research in chemistry and related fields.
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