Francesco Siddi
0e14bdd09f
These hotness and confidence calculation algorithms come from Reddit and have been tweaked based on our experience on the Dillo project.
88 lines
2.4 KiB
Python
88 lines
2.4 KiB
Python
# These functions come from Reddit
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# https://github.com/reddit/reddit/blob/master/r2/r2/lib/db/_sorts.pyx
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# Additional resources
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# http://www.redditblog.com/2009/10/reddits-new-comment-sorting-system.html
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# http://www.evanmiller.org/how-not-to-sort-by-average-rating.html
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# http://amix.dk/blog/post/19588
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from datetime import datetime, timezone
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from math import log
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from math import sqrt
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epoch = datetime(1970, 1, 1, 0, 0, 0, 0, timezone.utc)
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def epoch_seconds(date):
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"""Returns the number of seconds from the epoch to date."""
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td = date - epoch
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return td.days * 86400 + td.seconds + (float(td.microseconds) / 1000000)
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def score(ups, downs):
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return ups - downs
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def hot(ups, downs, date):
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"""The hot formula. Reddit's hot ranking uses the logarithm function to
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weight the first votes higher than the rest.
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The first 10 upvotes have the same weight as the next 100 upvotes which
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have the same weight as the next 1000, etc.
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Dillo authors: we modified the formula to give more weight to negative
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votes when an entry is controversial.
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TODO: make this function more dynamic so that different defaults can be
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specified depending on the item that is being rated.
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"""
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s = score(ups, downs)
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order = log(max(abs(s), 1), 10)
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sign = 1 if s > 0 else -1 if s < 0 else 0
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seconds = epoch_seconds(date) - 1134028003
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base_hot = round(sign * order + seconds / 45000, 7)
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if downs > 1:
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rating_delta = 100 * (downs - ups) / downs
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if rating_delta < 25:
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# The post is controversial
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return base_hot
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base_hot = base_hot - (downs * 6)
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return base_hot
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def _confidence(ups, downs):
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n = ups + downs
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if n == 0:
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return 0
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z = 1.0 #1.0 = 85%, 1.6 = 95%
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phat = float(ups) / n
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return sqrt(phat+z*z/(2*n)-z*((phat*(1-phat)+z*z/(4*n))/n))/(1+z*z/n)
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def confidence(ups, downs):
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if ups + downs == 0:
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return 0
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else:
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return _confidence(ups, downs)
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def update_hot(document):
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"""Update the hotness of a document given its current ratings.
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We expect the document to implement the ratings_embedded_schema in
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a 'ratings' property.
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"""
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dt = document['_created']
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dt = dt.replace(tzinfo=timezone.utc)
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document['properties']['ratings']['hot'] = hot(
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document['properties']['ratings']['positive'],
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document['properties']['ratings']['negative'],
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dt,
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)
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