User:Bohye Woo/Degrees of colonially in Terms of Service

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DoCiToS

DoCiToS (Degrees of Coloniality in Terms of Service) is a modern-colonial publishing archive, a series of numerical analysis that reveal the colonial contexts in 'Terms of Service (ToS)'. ToS is a modern working contract in digital colonial society, where big companies are dominating the power structures via ToS to deceive users. The project develops the colonization of metrics by measuring how colonized particular terms are being used in ToS.

Importance of this project

1. Language is important:
- Language as a colonial tool: because treaties in colonial times and Terms of Service in modern time both are to control the power structure. it shows a way to indoctrinate/manipulate the colonize subject via ToS.
- Using their comfort language -> colonial language: comfort language for the company(that are using highly specified terms that are used to obfuscate and conceal our labour to deceive users) -> colonial language.
- Language as a colonial waterway(shiproute): Shiproute in colonial times that used to sail to exchange/extract/export the goods. Language itself as a medium by which to interface with the colonizer.

2. Polarity of calming language: how specific words can play as colonial words

Process

1. Colonial languages will be made in colonial glossary
2. Analysing colonially of the language in ToS: degrees of coloniality: every platform has different tones of coloniality, different words being used. To what extent do platform has coloniality in ToS?
3. How to measure the degrees of coloniality: I specifically focus on measuring words within the realm of ToS. I narrow down the context to that of ToS to prevent generalizing the measurement.

A list of ToS

These companies are officially not a colony, but pratical term: a colony. There is a relationship that is unfair regardless what their intention is.

PokemonGo
TikTok
Snapchat
FaceApp
Netflix
Amazon
FaceBook
Instagram
Sony - Aibo https://us.aibo.com/terms/aibo-privacy.html
FaceApp https://www.faceapp.com/privacy-en.html / https://www.faceapp.com/terms-en.html

How to categorise colonial words?

STEP 1
Using a Standford Log-linear Part-Of-Speech Tagger in NLTK. A Part-Of-Speech Tagger (POS Tagger) is a piece of software that reads text in some language and assigns parts of speech to each word (and other token), such as noun, verb, adjective, etc. (https://nlp.stanford.edu/software/tagger.shtml)

The list of part of speech

  1. MD = would, could...
  2. RB = adverb 'very', 'slightly'...
  3. VB = verb
  4. JJ = adjective 'big'...
  5. NN = noun
  6. CC = coordinating conjunction 'and', 'or'...
  7. PRP = personal pronoun 'I', 'he', 'she'...

... more and more

STEP 2
When it's first categorized, I will establish sub-categories into the degree of coloniality.

degree of coloniality (gradation of intensity words)
100.00 = absolute level of coloniality
90.00 = extreme level of coloniality
80.00 = heavy level of coloniality
70.00 = high level of coloniality
60.00 = significant level of coloniality
50.00 =
40.00 = relative level of coloniality
30.00 = moderate level of coloniality
20.00 = reasonable level of coloniality
10.00 = fair level of coloniality
0.00 = neutral level of coloniality


Example 

epistemic_VB = { #verbs from FaceApp ToS
    100.00: d("must", "agree","use"),
    90.00: d("use", "bound", "access", "allow", "acknowlegde", "reproduce"),
    80.00: d("choose","claim", "permit", "collect" ),
    70.00: d("change", ),
    60.00: d("create"),
    50.00: d(),
    40.00: d("maintain"),
    30.00: d("support"),
    20.00: d("identify"),
    10.00: d("may"),
    0.00: d(),
}

Tools to reveal the degree of coloniality in ToS

- NLTK http://www.nltk.org/
- NLTK Book: https://www.nltk.org/book/
https://www.strehle.de/tim/weblog/archives/2015/09/03/1569
- Pattern https://www.clips.uantwerpen.be/pages/pattern/
- Modality.py https://github.com/clips/pattern/blob/master/pattern/text/en/modality.py
- Termcolor https://pypi.org/project/termcolor/
- https://numpy.org/
- Sementic Wiki https://www.semantic-mediawiki.org/wiki/Semantic_MediaWiki

Reference

https://www.cnet.com/how-to/amazon-and-google-are-listening-to-your-voice-recordings-heres-what-we-know/
https://www.cnet.com/news/faceapp-says-its-not-uploading-all-your-photos/
https://twitter.com/rycrist/status/1151479283661115392
FaceBook https://www.wired.com/story/faceapp-privacy-backlash-facebook/
Aibo https://www.cnet.com/news/yes-the-robot-dog-ate-your-privacy/

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