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A sentiment analysis library for detecting absolutist language.

Project description

A sentiment analysis library for detecting absolutist language.

Quickstart

Installation:

$ pip install absolang
$ python -m spacy download en_core_web_sm

Determining absolutist index for text:

>>> from absolang import absolutist, absolutist_index
>>> absolutist_index("The bigger dog is running.")
0.0
>>> absolutist("The bigger dog is running.")
False
>>> absolutist_index("He was completely bowled over.")
0.2
>>> absolutist("He was completely bowled over.")
True

Algorithm

  • Parse text into tokens using Spacy’s en_core_web_sm language model.
  • Count the number of word tokens (a token is considered a word if it consists solely of characters from the alphabet).
  • Count the number of absolutist word tokens (a token is considered absolutist if its stem word is in the dictionary of absolutist words and it is not preceded by a negation, modifier or interjection).
  • The absolutist index is the number of absolutist words divided by the total number of words.
  • Text is considered absolutist if the index is greater than 1.1 percent.

Caveats

  • The frequency of absolutist words in control texts (ones written by people presumed not to suffer from anxiety or depression more than the average person) is about 1%, so one needs a few hundred words of texts before results start becoming meaningful.

Project details


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Files for absolang, version 0.0.2
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