discourse/app/models/reviewable_score.rb

119 lines
3.5 KiB
Ruby

# frozen_string_literal: true
class ReviewableScore < ActiveRecord::Base
belongs_to :reviewable
belongs_to :user
belongs_to :reviewed_by, class_name: "User"
belongs_to :meta_topic, class_name: "Topic"
enum status: { pending: 0, agreed: 1, disagreed: 2, ignored: 3 }
# To keep things simple the types correspond to `PostActionType` for backwards
# compatibility, but we can add extra reasons for scores.
def self.types
@types ||= PostActionType.flag_types.merge(PostActionType.score_types)
end
# When extending post action flags, we need to call this method in order to
# get the latests flags.
def self.reload_types
@types = nil
types
end
def self.add_new_types(type_names)
next_id = types.values.max + 1
type_names.each_with_index { |name, idx| @types[name] = next_id + idx }
end
def self.score_transitions
{ approved: statuses[:agreed], rejected: statuses[:disagreed], ignored: statuses[:ignored] }
end
def score_type
Reviewable::Collection::Item.new(reviewable_score_type)
end
def took_action?
take_action_bonus > 0
end
def self.calculate_score(user, type_bonus, take_action_bonus)
score = user_flag_score(user) + type_bonus + take_action_bonus
score > 0 ? score : 0
end
# A user's flag score is:
# 1.0 + trust_level + user_accuracy_bonus
# (trust_level is 5 for staff)
def self.user_flag_score(user)
1.0 + (user.staff? ? 5.0 : user.trust_level.to_f) + user_accuracy_bonus(user)
end
# A user's accuracy bonus is:
# if 5 or less flags => 0.0
# if > 5 flags => (agreed flags / total flags) * 5.0
def self.user_accuracy_bonus(user)
user_stat = user&.user_stat
return 0.0 if user_stat.blank? || user.bot?
calc_user_accuracy_bonus(user_stat.flags_agreed, user_stat.flags_disagreed)
end
def self.calc_user_accuracy_bonus(agreed, disagreed)
agreed ||= 0
disagreed ||= 0
total = (agreed + disagreed).to_f
return 0.0 if total <= 5
accuracy_axis = 0.7
percent_correct = agreed / total
positive_accuracy = percent_correct >= accuracy_axis
bottom = positive_accuracy ? accuracy_axis : 0.0
top = positive_accuracy ? 1.0 : accuracy_axis
absolute_distance = positive_accuracy ? percent_correct - bottom : top - percent_correct
axis_distance_multiplier = 1.0 / (top - bottom)
positivity_multiplier = positive_accuracy ? 1.0 : -1.0
(
absolute_distance * axis_distance_multiplier * positivity_multiplier *
(Math.log(total, 4) * 5.0)
).round(2)
end
def reviewable_conversation
return if meta_topic.blank?
Reviewable::Conversation.new(meta_topic)
end
end
# == Schema Information
#
# Table name: reviewable_scores
#
# id :bigint not null, primary key
# reviewable_id :integer not null
# user_id :integer not null
# reviewable_score_type :integer not null
# status :integer not null
# score :float default(0.0), not null
# take_action_bonus :float default(0.0), not null
# reviewed_by_id :integer
# reviewed_at :datetime
# meta_topic_id :integer
# created_at :datetime not null
# updated_at :datetime not null
# reason :string
# user_accuracy_bonus :float default(0.0), not null
#
# Indexes
#
# index_reviewable_scores_on_reviewable_id (reviewable_id)
# index_reviewable_scores_on_user_id (user_id)
#