drdigit-brezniczky 0.0.4

A digit doctoring detection package

DrDigit is a digit doctoring detection package at an early stage. Interested in contributing? Please feel free to contact me, e.g. by commenting on the issue “Contributors welcome!” at https://github.com/brezniczky/drdigit/issues/1.

Requirements

DrDigit requires Python 3.5 or later.

Concept

The tests are based on the statistics of digits which are assumed to have a uniform distribution. Near-uniform distributions can be obtained by looking at the last digits of sufficiently large values - such as vote counts (possibly above 100).

On a smaller scale, you can query for the probablity of a digit sequence using probability mass functions represented by Python functions.

There are larger scale tests for a sequence of digit groups. This is so to support situations where different groups are expected to be doctored by different people - testing for an overarching, consistent anomaly could be too strict in such cases.

Based on the current features (entropy, digit repetition, coincident digits in parallel sequences), it is possible to sort a data frame containing digit groups by probability, so then it is possible to inspect if there is any apparent sanity behind the doctoring.

A couple of advice

• Handle results with care, there is always some uncertainity

• Try to focus on interesting groups, this should yield much sharper results

Quick start

DrDigit can be installed using pip:

$ pip install drdigit-brezniczky

More to come …

Tests

Coming soon …