BiasBuster - release 0.9.11 iframe

A set of tools which ultimate goal is to analyze biases in English. Currently only handles KJZZ's radio broadcast. Under active developement since 10/1/2023.

BiasBuster provides an cron 24/7 stream downloader, a SQLite database, and a Python script to output visual statistics and html schedules to present all that.

The transcription is done on GPU and produces text files and captions in various formats. They are then crunched by a python script that fills a database, and outputs html files and word clouds, etc. PNG files are compressed by pngquant to save space.

This project comes in 2 parts:

A bash script that runs every 30mn to download mp3 chunks of, well, 30mn each
A Windows part:
- A batch that calls whisper-faster to transcribe mp3 to text
- A python script that loads transcriptions into a SQLite database, and outputs html, statistics, word clouds etc

The Windows part could run on Linux as well, whisper also can use CPU (slower), and the processing batch should be rewritten in bash.

These schedules are hosted temporarily here: https://www.it-cooking.com/kjzz/48/index.html

Under the hood

Linux part: kjzz.sh

Currently, this application only downloads KJZZ's broadcast, available at https://kjzz.streamguys1.com/kjzz_mp3_128

You can certainly rewrite it for Windows if you like.

Usage

The script accepts 2 parameters:

start: starts the download according to KJZZ-schedule.json
stop: kills current download if you want to

kjzz.sh will download chunks of 30mn, minus the musical programs of the night (sleep). Simply schedule CRON with this one line, to get 30mn long mp3 files under ISO week number folders (week starts Monday): # 0,1,30,31 * * * * root /path/BiasBuster/kjzz.sh start

This script will create a pid lock file with its runing PID, ensuring not 2 runs at the same time. When you run the script, it will tell you if it's running or not. Example: ./kjzz.sh

                             16:23
filename=KJZZ_2023-10-20_Fri_1600-1630_All Things Considered.mp3
kjzzDownloader 1859415 is appending "KJZZ_2023-10-20_Fri_1600-1630_All Things Considered.mp3" for the next 6 mm = 374 s. stop it?

KJZZ schedule: KJZZ-schedule.json

This schedule comes from their official website at https://kjzz.org/kjzz-print-schedule

The structure is pretty simple, and simply lists by hour then by Day, the title of the program/segment/show:

{
  "00:00": {
    "Mon": "BBC World Service",
    "Tue": "Classic Jazz with Chazz Rayburn",
    "Wed": "Classic Jazz with Bryan Houston",
    "Thu": "Classic Jazz with Bryan Houston",
    "Fri": "Classic Jazz with Michele Robins",
    "Sat": "Classic Jazz with Michele Robins",
    "Sun": "BBC World Service"
  },
  ...

The schedule does not look like it's going to change until next year. No handling of multi-schedules or other radio broadcasts yet.

Windows part 1: BiasBuster-whisper.cmd

Transcribe the mp3 to text with Purfview/whisper-standalone-win and CUDA. The whole point of using Windows is to put this GTX 3090 to good use. Whisper-Faster is compiled and ready to use.

I tried my best to compile whisper, whisper-bin-x64, and whisper-cpp, but failed miserably. Compiling it apparently requires you to install 6GB of CUDA SDK on Windows. My C: drive is full, sorry.

Here is how to transcribe the mp3 downloaded:

Have a CUDA GPU
install Whisper-Faster from https://github.com/Purfview/whisper-standalone-win
add cuBLAS.and.cuDNN as required
update BiasBuster-whisper.cmd to point to Whisper-Faster folder
copy BiasBuster-whisper.cmd as a shortcut in the sendTo folder (access by typing shell:sendTo)
download mp3 from your Cloud server
right-click the folder and select BiasBuster-whisper
watch the magic of AI transcription - JK it's machine learning.

The script as it is, will produce all text and caption files whisper-faster cam produce. This this project only uses .text extensions to load into the database, and .vtt when playing the chunks.

vtt + text account for rougly 15MB per week.
OpenPlayerJS is integrated within the html pages (created by kjzz-db.py), and will load those vtt caption files.
In the future we could simply save only the vtt into the database, to save space. But a dynamic page would be necessary.

Windows part 2: KJZZ-db.py

This Python script does the following:

Load the text files into SQLite kjzz.db
Exploits the data to produce statistics and graphics
- import single mp3
- import all mp3 in a folder
- query statistics on what is stored
- query words based on schedule
- generate word cloud
- generate misInformation analysis heatmap only for programs
- generate html week pages for chunks
- generate html week pages for programs
- generate html week pages that have pictures
- generate html week pages that have links
- generate html week pages that can navigate
- generate html week pages and also missing wordCloud pictures
- generate gender bias analysis
- generate html week pages that are useful
- generate html week pages that are interactive
- see roadmap ...

KJZZ-db.py Usage

KJZZ-db.py needs at least --import / --query / --gettext / --listLevel. python KJZZ-db.py --help

usage: python KJZZ-db.py --help
Required at least: --import / --query / --gettext / --listLevel

  --import < --text "KJZZ_2023-10-13_Fri_1700-1730_All Things Considered.text" | --folder inputFolder >
    -m, --model *small medium large...
                   Model that you used with whisper, to transcribe the text to import.
    -p, --pretty
                   Convert \n to carriage returns and does json2text.
                   Ignored when outputing pictures.
    --output *kjzz
                   Folder where to output pictures..
    --show
                   Opens the picture upon generation.
    --rebuildThumbnails <week>
                   Will (re)generate PICtures thumbnails only for that week.
    --dryRun
                   Will not generate PICtures, will not import or update the database.
    --noPics
                   Will not generate PICtures.
    --force
                   Will regenerate existing PICtures.

  --db *kjzz.db    Path to the local SQlite db.
  -q, --query < title | first | last | last10 | byDay | byTitle | chunkLast10 >
                   Quick and dirty way to see what's in the db.

  --html [--byChunk --printOut --autoGenerate] <week>
                   PICture: generate week number's schedule as an html table.
                   Outputs html file: kjzz/week00[-byChunk].html
                   --byChunk  Outputs schedule by 30mn chucks, no rowspan, no picture.
                   --printOut Will output html on the prompt.
                   --autoGenerate Will loop generate all wordCloud PICtures to show in html for that week.

  -g, --gettext < selector=value : chunk= | date= | datetime= | week= | Day= | time= | title= >
                   Outputs all text from the selector:
                   chunk="KJZZ_YYYY-mm-DD_Ddd_HHMM-HHMM_Title" (run KJZZ-db.py -q chunkLast10 to get some values)
                   date=2023-10-08[+time=HH:MM]
                   datetime="2023-10-08 HH:MM"
                   week=42 (iso week with Mon first)
                   Day=Fri (Ddd)
                   title="title of the show", see https://kjzz.org/kjzz-print-schedule
          example: chunk="KJZZ_2023-10-13_Fri_1700-1730_All Things Considered"
                   Will get text from that chunk of programming only. Chunks are 30mn long.
          example: week=41+Day=Fri+title="All Things Considered"
                   Same as above but will get text from the entire episode.
   *--printOut
                   Will output selected text on the prompt (default if no other option passed).
    --noMerge
                   Do not merge 30mn chunks of the same title within the same timeframe.
    --misInformation
                   PICture: generate misInformation graph or heatmap for all 4 factors:
                   explanatory/retractors/sourcing/uncertainty
      --graphs *bar,*pie,line
                   What graph(s) you want. Ignored with --noMerge: a heatMap will be generated instead.
    --wordCloud
                   PICture: generate word cloud from gettext output. Will not output any text.
      --noPngquant
                   Disable pngquant compression
      --useJpeg
                   Produces jpeg instead of png
      --jpegQuality <*50>
                   0-100 jpeg quality
      --stopLevel  0 1 2 *3
                   add various levels of stopwords
        --listLevel <0[,1 ..]> to just show the words in that level(s).

      --max_words *1000 int (default=1000)
               The maximum number of words in the Cloud.
      --width *2000 int (default=2000)
               Width of the canvas.
      --height *1000 int (default=1000)
               Height of the canvas.
      --min_word_length *3 int, default=3
               Minimum number of letters a word must have to be included.
      --min_font_size *4 int (default=4)
               Smallest font size to use. Will stop when there is no more room in this size.
      --max_font_size *400  int or None (default=400)
               Maximum font size for the largest word. If None, height of the image is used.
      --scale *1.0 float (default=1.0)
               Scaling between computation and drawing. For large word-cloud images,
               using scale instead of larger canvas size is significantly faster, but
               might lead to a coarser fit for the words.
      --relative_scaling *auto float (default='auto')
               Importance of relative word frequencies for font-size.  With
               relative_scaling=0, only word-ranks are considered.  With
               relative_scaling=1, a word that is twice as frequent will have twice
               the size.  If you want to consider the word frequencies and not only
               their rank, relative_scaling around .5 often looks good.
               If 'auto' it will be set to 0.5 unless repeat is true, in which
               case it will be set to 0.
      --background_color *white color value (default='white')
               Background color for the word cloud image.
      --normalize_plurals *True bool, default=True
               Whether to remove trailing 's' from words. If True and a word
               appears with and without a trailing 's', the one with trailing 's'
               is removed and its counts are added to the version without
               trailing 's' -- unless the word ends with 'ss'. Ignored if using
               generate_from_frequencies.
      --inputStopWordsFiles *[] file, default=None
               Text file containing one stopWord per line.
               You can pass --inputStopWordsFiles multiple times.
      --font_path *fonts\Quicksand-Bold.ttf str, default='fonts\Quicksand-Bold.ttf'
               Font path to the font that will be used (OTF or TTF).
      --collocation_threshold *30 int, default=30
               Bigrams must have a Dunning likelihood collocation score greater than this
               parameter to be counted as bigrams. Default of 30 is arbitrary.
               See Manning, C.D., Manning, C.D. and Schütze, H., 1999. Foundations of
               Statistical Natural Language Processing. MIT press, p. 162
               https://nlp.stanford.edu/fsnlp/promo/colloc.pdf#page=22

  -v, --verbose
                   -vv -vvv increase verbosity.
  --silent
                   Not verbose.

Import new data

-i, --import --text file | --folder folder

File naming convention

For KJZZ

Mp3 files must be named like so, in order to be matched against KJZZ-schedule.json during loading of the database:

KJZZ_2023-10-13_Fri_1700-1730_All Things Considered.text
     ^          ^   ^         ^                     ^
     YYYY-MM-DD Day HHMM      Program name          text (for folder import)

Day is redundant since we have the date, but makes the chunk name and database, convenient to interact with.

Import text files in the Database

python KJZZ-db.py --import --folder kjzz\\42

Will import every text file in the folder "kjzz\42" (week 42). --import will always avoid chunks already present in the database unless you add --force.

  db_init: 314 chunks found in kjzz.db
    db_load: Chunk already exist: KJZZ_2023-10-16_Mon_0000-0030_BBC World Service.text
    db_load: Chunk already exist: KJZZ_2023-10-16_Mon_0030-0100_BBC World Service.text
    ...
    db_load: Chunk added: KJZZ_2023-10-18_Wed_1030-1100_Here and Now.text
    db_load: Chunk added: KJZZ_2023-10-18_Wed_1100-1130_Here and Now.text
    ...
Loading... ---------------------------------------- 100% 0:00:00
  db_load: done loading 53/146 files

Query database

-q, --query title first last last10 byDay byTitle chunkLast10

Quick and dirty way to see what's in the db.

Database titles overview

python KJZZ-db.py -q byTitle

Outputs how many 30mn chunks are stored, by title and by Day:

[
  ('All Things Considered', 'Fri', 6),
  ('All Things Considered', 'Mon', 6),
  ('All Things Considered', 'Sat', 2),
  ('All Things Considered', 'Sun', 2),
  ...

Database title flat listing

python KJZZ-db.py -q title --pretty

Outputs alphabetically sorted list of all programing in the database, useful for loops for instance:

"All Things Considered"
"BBC Newshour"
"BBC World Business Report"
"BBC World Service"
"Bullseye"
"Climate One"
...

List the last chunks loaded

python KJZZ-db.py --query chunkLast10 -pretty

Adding pretty will flatten the output as simple text:

"KJZZ_2023-10-19_Thu_1930-2000_Fresh Air"
"KJZZ_2023-10-19_Thu_1900-1930_Fresh Air"
"KJZZ_2023-10-19_Thu_1830-1900_BBC World Business Report"
"KJZZ_2023-10-19_Thu_1800-1830_Marketplace"
"KJZZ_2023-10-19_Thu_1730-1800_All Things Considered"
"KJZZ_2023-10-19_Thu_1700-1730_All Things Considered"
"KJZZ_2023-10-19_Thu_1630-1700_All Things Considered"
"KJZZ_2023-10-19_Thu_1600-1630_All Things Considered"
"KJZZ_2023-10-19_Thu_1530-1600_All Things Considered"
"KJZZ_2023-10-19_Thu_1500-1530_All Things Considered"

gettext

validKeys = they will be used as parameters for the SQL query:

chunk="KJZZ_YYYY-mm-DD_Ddd_HHMM-HHMM_Title"
date=2023-10-08[+time=HH:MM]
datetime="2023-10-08 HH:MM"
week=42 (iso week with Mon first)
Day=Fri (Ddd)
title="title of the show", see https://kjzz.org/kjzz-print-schedule

You can also combine the keys with +, examples:

ALL of BBC Newshour for week 41: --gettext week=41+title="BBC Newshour"
ALL programs for a specific day [and time]: --gettext date=2023-10-08[+time=HH:MM]
ALL programs for a specific week: --gettext week=42
Specific date and time (30mn chunk): --gettext datetime="2023-10-08 HH:MM"

--stopLevel 3 is used by default; Look in the script what words the various levels contain, or type this to find out: python KJZZ-db.py --listLevel 0,1

0: basic stopWords
  {'being', "i'm", "hadn't", "he'd", 'you', 'yours', "mustn't", 'about', "he'll", 'how', "what's", 'ours', 'my', 'what',
  'through', 'nor', "can't", 'cannot', 'have', 'other', 'over', 'otherwise', 'below', 'this', "let's", 'i', 'both',
  "where's", "it's", "i'd", 'we', 'against', 'where', 'to', 'for', 'itself', "shan't", 'can', 'does', 'just', 'out',
  "aren't", 'in', 'no', 'r', 'above', "they're", 'get', "she'll", 'shall', 'on', 'like', 'after', "shouldn't", 'having',
  'since', "we'd", "hasn't", 'because', 'been', 'ourselves', 'hers', 'until', "he's", 'should', "there's", "haven't",
  "we'll", 'all', 'an', 'however', 'again', "why's", 'a', 'once', 'than', "she'd", "we've", "couldn't", 'as', 'with',
  'myself', 'was', 'further', "isn't", 'the', 'and', 'your', 'why', 'his', 'so', 'only', 'him', 'between', 'by', 'few',
  'theirs', 'ought', 'most', 'they', 'under', 'which', 'its', 'of', 'some', 'whom', 'themselves', 'but', 'ever', 'down',
  'hence', 'own', "who's", 'am', 'off', 'who', 'such', 'same', 'doing', "won't", 'while', 'any', "here's", 'therefore',
  'could', 'k', 'had', 'when', 'yourself', 'be', "we're", 'herself', "they've", 'each', 'here', 'she', 'more', "i'll",
  "wasn't", "you'd", 'very', 'their', 'or', 'up', 'http', 'at', "i've", "weren't", 'yourselves', 'if', 'too', 'not',
  'himself', 'are', "didn't", 'did', 'do', 'from', "when's", "how's", 'during', 'then', "she's", 'them', 'has', 'it',
  "that's", "doesn't", 'those', 'me', 'her', 'into', "they'll", 'he', 'our', 'there', 'www', 'before', 'would', "they'd",
  "you'll", 'also', 'that', 'were', 'is', "wouldn't", 'com', 'these', 'else', "you're", "you've", "don't"}
1: more stopWords related to broadcasting speech
  {'mean', 'new', 'kind', 'case', 'called', 'report', 'things', 'need', 'morning', 'become', 'live', 'even', 'okay',
  'many', 'point', 'trying', 'lot', 'come', 'came', 'really', 'week', 'going', 'always', 'got', 'think', 're', 'good',
  'day', 'almost', 'first', 'two', 'comes', 'part', 'went', 'still', 'little', 'today', 'well', 'actually', 'take',
  'years', 'another', 'right', 'next', 'look', 'one', 'see', 'will', 'thing', 'know', 'back', 'said', 'says', 'last',
  'yeah', 'made', 'say', 'never', 'number', 'coming', 'want', 'something', 'show', 'talk', 'way', 'much', 'sort',
  'edition', 'time', 'year', 'around', 'now', 'let', 'work', 'hour', 'people'}
2: specific stopWords for KJZZ station
{'month', 'donation', 'thank', 'gift', 'NPR', 'org', 'you', 'help', 'please', 'doubled', 'news', 'KJZZ',
'sustaining', 'member', 'make', 'contribution', 'call', 'give', 'BBC', 'support', 'drive'}

Get the text for a particular chunk

python KJZZ-db.py --gettext chunk="KJZZ_2023-10-13_Fri_1700-1730_All Things Considered" -p

Get the text for a particular program, ALL dates (slow)

python KJZZ-db.py --gettext title="All Things Considered" -p

Generate a word Cloud for a program, on a specific week and Day

python KJZZ-db.py -g week=42+title="Freakonomics"+Day=Sun --wordCloud--show --max_words=1000

Same but If you know the actual date: python KJZZ-db.py -g week=42+title="Freakonomics"+Day=Sun --wordCloud--show --max_words=1000

Generate a word Cloud for a particular chunk of program

python KJZZ-db.py -g chunk="KJZZ_2023-10-19_Thu_1500-1530_All Things Considered" -v --wordCloud

Verbose outpout:

wordCloud:     True
localSqlDb kjzz.db passed
  db_init kjzz.db
    cursor: 1 records
  db_init: 367 chunks found in kjzz.db
  gettext: SELECT text from schedule where 1=1 and start = '2023-10-19 15:00:00.000'
    cursor: 1 records
  gettext: image 1
    genWordCloud: most 10 common words before: [('the', 208), ('to', 142), ('a', 114), ('of', 110), ('in', 91), ('and', 89), ('that', 73), ('is',
70), ('this', 58), ('on', 49)]
    genWordCloud: most 10 common words after:  [('s', 68), ('you', 41), ('I', 37), ('are', 34), ('from', 32), ('they', 32), ('have', 24), ('like',
24), ('was', 23), ('so', 23)]
    genWordCloud: 4952 words - 195 stopWords == 3694 total words (1258 words removed)
    genWordCloud: stopWords = {"we're", 'nor', 'start=2023-10-19', 'they', "doesn't", 'we', 'on', 'me', 'can', 'out', 'get', "she's", 'about',
'few', 'once', "we'd", "you'd", 'of', "here's", 'is', 'www', 'but', "he'd", 'to', 'both', 'k', 'below', 'was', 'themselves', 'could', 'up',
'while', 'where', 'other', "shouldn't", 'like', 'or', 'same', 'what', 'myself', "it's", 'our', 'how', 'doing', 'her', 'ours', 'such', 'further',
'my', "there's", "couldn't", "they've", 'only', "i'll", 'it', 'then', 'therefore', 'else', 'which', 'after', 'just', 'for', 'be', 'very', 'at',
'are', 'since', 'being', 'r', 'against', 'too', 'should', 'having', 'were', 'in', 'them', "you're", 'yours', 'KJZZ', 'into', 'however', 'if',
'through', "why's", 'all', 'himself', 'more', "you've", 'otherwise', 'did', "she'd", "what's", "she'll", 'who', 'own', "wasn't", 'during',
"you'll", 'their', 'here', "won't", 'those', 'you', "who's", "didn't", "where's", 'has', "shan't", 'no', 'not', "can't", "hadn't", 'http',
'again', "don't", 'i', "aren't", 'ever', "let's", 'hence', 'with', 'until', 'whom', 'why', 'had', 'been', 'there', 'under', "we'll", "i'm",
'yourselves', 'am', "i'd", 'above', 'as', 'over', 'this', 'some', 'each', 'itself', 'from', 'between', 'that', "when's", "they're", 'off', 'any',
'an', 'the', "isn't", '15:00', 'and', "i've", 'his', "hasn't", 'most', "he'll", 'a', 'when', 'these', 'hers', 'by', "weren't", 'com', 'also',
'its', 'your', 'cannot', "haven't", "wouldn't", 'before', "they'll", 'than', 'yourself', 'ourselves', "he's", 'him', "how's", "they'd", 'ought',
"that's", 'because', 'do', 'herself', 'down', 'shall', 'she', 'he', 'does', "we've", 'so', 'would', 'have', "mustn't", 'theirs'}
    genWordCloud: file = "KJZZ start=2023-10-19 1500 words=4952 max=4000 scale=0.png"

wordCloud generated: Notice how it makes no sense as onlt the stop words are highlighted

Generate a cloud a an episode of "Freakonomics" on week 42

python KJZZ-db.py -g week=42+title="Freakonomics" --wordCloud --show --max_words=1000 --inputStopWordsFiles data\stopWords.Wordlist-Adjectives-All.txt

Generate a cloud a an episode of "Freakonomics" on week 42 with smaller max font size

python KJZZ-db.py -g week=42+title="Freakonomics" --wordCloud --show --max_words=1000 --inputStopWordsFiles data\stopWords.Wordlist-Adjectives-All.txt

Notice how more smaller words are stacked and make the cloud illegible:

Generate a cloud a an episode of "Freakonomics" on week 42 without stopWords

No stopWords: adjectives are now prominents and the cloud has no meaning anymore:

python KJZZ-db.py -g week=42+title="Freakonomics" --wordCloud --stopLevel 0 --show --max_words=1000

Generate PIE+BAR graphs about how uncertain information is in a program

python KJZZ-db.py --gettext week=46+title="Morning Edition"+Day=Tue --misInformation --graphs bar,pie --show

Generate a heat map about how uncertain information is in multiple chunks of a program

Simply add --noMerge: --graph will be ignored when treating multiple chunks, and output a heat map instead.

python KJZZ-db.py --gettext week=46+title="Morning Edition"+Day=Tue --misInformation --noMerge --show

Batch to generate JUST wordCloud pictures for a week

The loop below will generate png files for each program of each day of week 42, manually:

for /f "tokens=*" %t in ('python KJZZ-db.py -q title -p') DO (for %d in (Mon Tue Wed Thu Fri Sat Sun) DO python KJZZ-db.py -g week=42+title=%t+Day=%d --wordCloud --max_words=1000 --inputStopWordsFiles data\stopWords.ranks.nl.uniq.txt --inputStopWordsFiles data\stopWords.Wordlist-Adjectives-All.txt --output kjzz)

Notice how the order of --gettext parameters influence the file names: this is useful when you want your files sorted a certain way.

The loop above will have them sorted by Title. If you want to have them sorted by Day, use week=42+Day=%d+title=%t.

Now, there is a much easier way to generate all those wordCloud pictures.

Generate html page for a week + wordCloud pictures

Automatically: this command will generate week's 42 schedule html page, linking available wordCloud pictures:

python KJZZ-db.py --html 42 --autoGenerate --inputStopWordsFiles data\stopWords.ranks.nl.uniq.txt --inputStopWordsFiles data\stopWords.Wordlist-Adjectives-All.txt

Manually: the loop below will generate only the wordCloud files:

REM (re)generate all thumbnails for week 42 manually:
for /f "tokens=*" %t in ('python KJZZ-db.py -q title -p') DO (for %d in (Mon Tue Wed Thu Fri Sat Sun) DO python KJZZ-db.py -g week=42+title=%t+Day=%d --wordCloud --max_words=1000 --inputStopWordsFiles data\stopWords.ranks.nl.uniq.txt --inputStopWordsFiles data\stopWords.Wordlist-Adjectives-All.txt --output kjzz)

Notice how the order of --gettext parameters influence the file names: this is useful when you want your files sorted a certain way.

The loop above will have them sorted by Title. If you want to have them sorted by Day, use week=42+Day=%d+title=%t.

Requirements

Linux

none

Windows

Python 3.x:
- getopt, sys, os, re, regex, io, glob, time, datetime, pathlib, json, urllib, random, sqlite3, collections
Python 3.x modules:
- rich
- pandas
- numpy
- matplotlib
- seaborn
- wordcloud
- pngquant
Windows software:
- busybox.exe
- whisper-faster from https://github.com/Purfview/whisper-standalone-win

Acknowledgements

busybox: https://busybox.net/
rich print: https://github.com/Textualize/rich
pngquant: https://github.com/kornelski/pngquant
wordCloud: https://github.com/amueller/word_cloud
gender bias: https://github.com/auroracramer/language-model-bias
misInformation: https://github.com/PDXBek/Misinformation
- heatMap.explanatory.csv
- heatMap.retractors.csv
- heatMap.sourcing.csv
- heatMap.uncertainty.csv
IA transcribe: https://github.com/Purfview/whisper-standalone-win
stopWords lists:
- ranks.nl compilation: https://www.ranks.nl/stopwords
  - stopWords.ranks.nl.txt
- Thesaurus and adjectives: https://github.com/taikuukaits/SimpleWordlists/tree/master
  - stopWords.Wordlist-Adjectives-All.txt
mp3 player: OpenPlayer.js https://github.com/openplayerjs/openplayerjs/

Support

👍🏻 If you're using this project & happy with it or you appreciate what I do and wish to support my work, you can consider by

⭐️ Starring & Sharing the project is also appreciated. Thanks! ❤️

Contribution

I will be open to any contribution. If you have any idea, please let me know. I am by no means an expert in English language or statistics. Any idea to help reveal the agenda of the programmings are welcome.

License

This project is under GPL-2.0 License.

Roadmap

Scope creep ahead...

Name		Name	Last commit message	Last commit date
Latest commit History 53 Commits
assets		assets
data		data
fonts		fonts
kjzz		kjzz
.gitattributes		.gitattributes
.gitignore		.gitignore
BiasBuster-whisper.cmd		BiasBuster-whisper.cmd
BiasBuster-whisper_custom.cmd		BiasBuster-whisper_custom.cmd
KJZZ-db.py		KJZZ-db.py
LICENSE		LICENSE
README.md		README.md
kjzz.db		kjzz.db
requirements.txt		requirements.txt

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audioscavenger/BiasBuster

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BiasBuster - release 0.9.11 iframe

Under the hood

Linux part: kjzz.sh

Usage

KJZZ schedule: KJZZ-schedule.json

Windows part 1: BiasBuster-whisper.cmd

Windows part 2: KJZZ-db.py

KJZZ-db.py Usage

Import new data

File naming convention

For KJZZ

Import text files in the Database

Query database

Database titles overview

Database title flat listing

List the last chunks loaded

gettext

Get the text for a particular chunk

Get the text for a particular program, ALL dates (slow)

Generate a word Cloud for a program, on a specific week and Day

Generate a word Cloud for a particular chunk of program

Generate a cloud a an episode of "Freakonomics" on week 42

Generate a cloud a an episode of "Freakonomics" on week 42 with smaller max font size

Generate a cloud a an episode of "Freakonomics" on week 42 without stopWords

Generate PIE+BAR graphs about how uncertain information is in a program

Generate a heat map about how uncertain information is in multiple chunks of a program

Batch to generate JUST wordCloud pictures for a week

Generate html page for a week + wordCloud pictures

Requirements

Linux

Windows

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