Consider an absolute # characters changed threshold for textual changes

[Mr0grog]

We should consider factoring in the absolute number of changed characters or words into the how textual changes contribute to priority. In extremely large pages, even a large change (which is worth looking at) can seem small percentage-wise. For example, only 1.1% of the text here changed, but that’s still 1,785 characters!

https://monitoring.envirodatagov.org/page/6767f063-29f7-4c50-93d0-b851d0292c98/4da08f36-ab67-463d-8517-cf191857dc02..0eae6081-9fac-4f00-b914-f19c0218e7fe

Currently, we only look at the percentage changed:

web-monitoring-task-sheets/analyst_sheets/analyze.py

Lines 324 to 325 in 54a6759

	if text_analysis['diff_count'] > 0:
	priority += 0.1 + 0.3 * priority_factor(text_analysis['percent_changed'])

[Mr0grog]

Maybe the easiest way to do this is to put a ceiling on how many characters of a page we’ll consider, e.g. pretend a page can never be longer than 5,000 (?) characters. That way, this example change above would have equated to 35.7% changed rather than 1.1% changed.