Another syntactic complexity analyzer of written English language samples.
NeoSCA is a rewrite of Xiaofei Lu’s L2 Syntactic Complexity Analyzer, supporting Windows, macOS, and Linux. The same as L2SCA, NeoSCA takes written English language samples in plain text format as input, and computes:
The frequency of 9 structures in the text:
- words (W)
- sentences (S)
- verb phrases (VP)
- clauses (C)
- T-units (T)
- dependent clauses (DC)
- complex T-units (CT)
- coordinate phrases (CP)
- complex nominals (CN), and
14 syntactic complexity indices of the text:
- mean length of sentence (MLS)
- mean length of T-unit (MLT)
- mean length of clause (MLC)
- clauses per sentence (C/S)
- verb phrases per T-unit (VP/T)
- clauses per T-unit (C/T)
- dependent clauses per clause (DC/C)
- Dependent clauses per T-unit (DC/T)
- T-units per sentence (T/S)
- complex T-unit ratio (CT/T)
- coordinate phrases per T-unit (CP/T)
- coordinate phrases per clause (CP/C)
- complex nominals per T-unit (CN/T)
- complex nominals per clause (CP/C)
Contents
NeoSCA vs. L2SCA Top ▲
| L2SCA | NeoSCA |
|---|---|
| runs on macOS and Linux | runs on WindowsmacOS, and Linux |
| single and multiple input are handled respectively by two commands | one command, nscafor both cases, making your life easier |
| runs only under its own home directory | runs under any directory |
| outputs only frequencies of the “9+14” syntactic structures | add options to reserve intermediate results, such as the results of parsing the text with Stanford Parser and matching patterns with Stanford Tregex |
- Install neosca
To install NeoSCA, you need to have Python 3.7 or later installed on your system. You can check if you have Python installed by running the following command in your terminal:
If Python is not installed, you can download and install it from Python website. Once you have Python installed, you can install NeoSCA using pip:
For users inside of China:
pip install neosca -i https://pypi.tuna.tsinghua.edu.cn/simpleInstall Java 8 or later
Download and unzip latest versions of Stanford Parser and Stanford Tregex
4. Set environment variables `STANFORD_PARSER_HOME` and `STANFORD_TREGEX_HOME`
In the Environment Variables window (press Windows+stype envand press Enter):
STANFORD_PARSER_HOME=\path\to\stanford-parser-full-2020-11-17
STANFORD_TREGEX_HOME=\path\to\stanford-tregex-2020-11-17export STANFORD_PARSER_HOME=/path/to/stanford-parser-full-2020-11-17
export STANFORD_TREGEX_HOME=/path/to/stanford-tregex-2020-11-17To use NeoSCA, run the nsca command in your terminal, followed by the options and arguments you want to use.
- Single input:
nsca ./samples/sample1.txt
# frequency output: ./result.csv
nsca ./samples/sample1.txt -o sample1.csv
# frequency output: ./sample1.csv- Multiple input:
nsca ./samples/sample1.txt ./samples/sample2.txt
nsca ./samples/sample*.txt
# wildcard characters are supported
nsca ./samples/sample[1-1000].txt- Use
--textto pass text through command line.
nsca --text 'The quick brown fox jumps over the lazy dog.'
# frequency output: ./result.csv- Use
-p/--reserve-parsed
to reserve parsed trees of Stanford Parser.-m/--reserve-matched
to reserve matched subtrees of Stanford Tregex.
nsca samples/sample1.txt -p -m
# frequency output: ./result.csv
# parsed trees: ./samples/sample1.parsed
# matched subtrees: ./result_matches/5. Use `–list` to print output fields.
W: words
S: sentences
VP: verb phrases
C: clauses
T: T-units
DC: dependent clauses
CT: complex T-units
CP: coordinate phrases
CN: complex nominals
MLS: mean length of sentence
MLT: mean length of T-unit
MLC: mean length of clause
C/S: clauses per sentence
VP/T: verb phrases per T-unit
C/T: clauses per T-unit
DC/C: dependent clauses per clause
DC/T: dependent clauses per T-unit
T/S: T-units per sentence
CT/T: complex T-unit ratio
CP/T: coordinate phrases per T-unit
CP/C: coordinate phrases per clause
CN/T: complex nominals per T-unit
CN/C: complex nominals per clause- Use
--no-queryto just save parsed trees and exit.
nsca samples/sample1.txt --no-query
# parsed trees: samples/sample1.parsed
nsca --text 'This is a test.' --no-query
# parsed trees: ./cmdline_text.parsed- Calling
nscawithout any arguments returns the help message.
If you use NeoSCA in your research, please cite it using the following BibTeX entry:
@misc{tan2022neosca,
author = {Tan, Long},
title = {NeoSCA (version 0.0.30)},
howpublished = {\url{https://github.com/tanloong/neosca}},
year = {2022}
}Also, you need to cite Lu’s article describing L2SCA:
@article{lu2010automatic,
title={Automatic analysis of syntactic complexity in second language writing},
author={Lu, Xiaofei},
journal={International journal of corpus linguistics},
volume={15},
number={4},
pages={474--496},
year={2010},
publisher={John Benjamins}
}NeoSCA is licensed under the GNU General Public License version 2 or later.
#NeoSCA #syntactic #complexity #analyzer #written #English #language #samples