Skip to main content

Text Analysis Software

Project description

neolo

Text Analysis Software for Saulo Brandão. Developed by Joshua Crowgey in summer 2014.

usage: neolo [-h] [--dicts DICT [DICT ...]] [--mltd] [--msttr] [--hdd]
             [--verbose] [--wordlen] [--wordtypes] [--hapax] [--punc-ratio]
             [--no-hyphen] [--no-apostrophe] [--sents [ABBREV]]
             [--stemming LANGUAGE]
             TEXT

Extract lexical statistics from a text file.

positional arguments:
  TEXT                  the text you want to investigate

optional arguments:
  -h, --help            show this help message and exit
  --dicts DICT [DICT ...]
                        a list of reference texts to compute neologism count
  --mltd                measure of lexical textual diversity
  --msttr               mean segmental type-token ratio
  --hdd                 HD-D probabilistic TTR
  --verbose, -v         increase the verbosty (can be repeated: -vvv)
  --wordlen, -w         print the distribution of words by length
  --wordtypes, -t       print the distribution of wordtypes (unigrams) by
                        count
  --hapax, -x           print the list of hapax legomena
  --punc-ratio, -p      print the ratio of punctuation tokens out of total
                        tokens
  --no-hyphen, -y       remove the hyphen (-) from the list of punctuation
                        symbols used in tokenization
  --no-apostrophe, -a   remove the apostrophe (') from the list of punctuation
                        symbols used in tokenization
  --sents [ABBREV], -s [ABBREV]
                        print sentence length statistics, uses an (optional)
                        abbreviations file containing stings which don't end
                        sentences (eg: Mr.). One abbreviaion per line, include
                        relevant punctuation. Note that items in the
                        abbreviations file will also be protected during later
                        tokenization.
  --stemming LANGUAGE, -m LANGUAGE
                        stem words using NLTK prior to processing them

Neologism Count

The name of this program reflects this original functionality. Neologism count is computed by referencing known wordlists or dictionaries. Word types found in the text under consideration which are not found in the reference dictionaries/wordlists are considered neologisms.

To show a simple example, suppose you have a text file called mary.txt which contains the following traditional poem:

Mary had a little lamb,
Her fleece was white as snow.
Everywhere that mary went,
the lamb was sure to go.

Supposing you're using the debian distro of GNU/Linux, there is a list of English words stored in /usr/share/dict/words that you can use as a reference. You can ask neolo to check mary.txt for neologisms using the --dicts option. The --dicts option takes a list of one ore more filenames to use as references in calculating neologisms.

user@computer:~/src/neolo$ ./neolo texts/mary.txt --dicts /usr/share/dict/words
Opening texts/mary.txt with encoding:  utf-8 
Tokenizing, downcasing, stemming text: texts/mary.txt ... done.
Counting and sorting words in text: texts/mary.txt ...done.
Opening /usr/share/dict/words with encoding:  utf-8 
Tokenizing, downcasing, stemming dict files: ['/usr/share/dict/words'] ... done.
Counting and sorting words in dictonaries: ['/usr/share/dict/words'] ...done.
Neologism list:

Statistics:
-----------
Text size: 21 tokens in 18 types.
Number of hapax legomena: 15
TTR (type-token ratio): 0.8571428571428571
HTR (hapax-token ratio): 0.7142857142857143
HTyR (hapax-type ratio): 0.8333333333333334
Neologisms:  0 types not found in 1 dictionaries
Dictionaries contained 234937 tokens in 233615 types.

As you can see, there are no words in mary.txt which aren't in the reference wordlist file, so neolo says "Neolgisms: 0 types not found in 1 dictionaries".

However, if you edit mary.txt such that instead of fleece, the poem's second line says ``Her pleece was white as snow.'', now neolo prints a neologism list along with its regular output.

user@computer:~/src/neolo$ ./neolo texts/mary.txt --dicts /usr/share/dict/words
Opening texts/mary.txt with encoding:  utf-8 
Tokenizing, downcasing, stemming text: texts/mary.txt ... done.
Counting and sorting words in text: texts/mary.txt ...done.
Opening /usr/share/dict/words with encoding:  utf-8 
Tokenizing, downcasing, stemming dict files: ['/usr/share/dict/words'] ... done.
Counting and sorting words in dictonaries: ['/usr/share/dict/words'] ...done.
Neologism list:
pleece

Statistics:
-----------
Text size: 21 tokens in 18 types.
Number of hapax legomena: 15
TTR (type-token ratio): 0.8571428571428571
HTR (hapax-token ratio): 0.7142857142857143
HTyR (hapax-type ratio): 0.8333333333333334
Neologisms:  1 types not found in 1 dictionaries
Dictionaries contained 234937 tokens in 233615 types.

MLTD

MSTTR

HD-D

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Files for neolo, version 0.1.2
Filename, size File type Python version Upload date Hashes
Filename, size neolo-0.1.2-py3-none-any.whl (10.0 kB) File type Wheel Python version py3 Upload date Hashes View hashes
Filename, size neolo-0.1.2.tar.gz (9.1 kB) File type Source Python version None Upload date Hashes View hashes

Supported by

Elastic Elastic Search Pingdom Pingdom Monitoring Google Google BigQuery Sentry Sentry Error logging AWS AWS Cloud computing DataDog DataDog Monitoring Fastly Fastly CDN DigiCert DigiCert EV certificate StatusPage StatusPage Status page