The Well-Balanced: Popular posts that are both Type A and Type B.

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"Well-Balanced" posts that exhibit both Type A and Type B behavior. These are posts that have sharp spikes of viral activity, yet are able to maintain long-term steady traffic. See comments on how to choose the "Skew Factor". For starters (SkewFactor = 4.0) is a good starting point. Anything between 1.0 and 10.0 seems to produce relevant results.

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-- "The Well-Balanced" - Middle-ground Type A and Type B posts from:
-- http://data.stackexchange.com/stackoverflow/query/109257/popular-posts-type-a-vs-type-b

-- Lower  "Skew Factor" favors more viral activity and less steady-state.
-- Higher "Skew Factor" favors less viral activity and more steady-state.

-- Skew Factor = 0         is the same as Type A sorting. (http://data.stackexchange.com/stackoverflow/query/109334/)
-- Skew Factor = infinity  is the same as Type B sorting. (http://data.stackexchange.com/stackoverflow/query/109312/)

declare @minDataSize numeric = 30
declare @skewFactor  numeric = ##SkewFactor?4.0##

DECLARE @endDate date
SELECT  @endDate = max(CreationDate) from Posts;

WITH rawData(type,pid,uid,age,score,vMax,vSum,vNStd)
AS(
SELECT
    (CASE tmp.posttype
        WHEN 1 THEN 'Q'
        WHEN 2 THEN 'A'
     END),
    tmp.[Post Link],
    tmp.[User Link],
    tmp.[Age],
    tmp.score,
    MAX(tmp.dVotes),
    SUM(tmp.dVotes),
    CASE
    -- If more than 30 days of votes, use standard deviation.
    WHEN COUNT(tmp.dVotes) >= @minDataSize THEN STDEVP(tmp.dVotes) + 1
    -- If less than 30 days of data, use some sort of zero-padded standard deviation.
    ELSE
        SQRT(
            (
                VARP(tmp.dVotes) * COUNT(tmp.dVotes)
                - SQUARE(MAX(tmp.dVotes) - AVG(tmp.dVotes + 0.))
                + SQUARE(MAX(tmp.dVotes) - SUM(tmp.dVotes + 0.) / @minDataSize)
                + SQUARE(SUM(tmp.dVotes + 0.) / @minDataSize) * (@minDataSize - COUNT(tmp.dVotes))
            ) / @minDataSize
        ) + 1
    END
FROM

-- Subquery forked from:
-- http://data.stackexchange.com/stackoverflow/query/108188/upvotes-per-post-and-per-day
    (SELECT
      p.PostTypeId AS posttype,
      v.PostId AS [Post Link],
      p.OwnerUserId AS [User Link],
      v.CreationDate AS [Date],
      DATEDIFF(DAY,p.CreationDate,@endDate) AS [Age],
      Count(*) AS dVotes,
      p.score AS score
    FROM Votes v
    LEFT JOIN Posts p ON p.Id = v.PostId
    WHERE
        v.VoteTypeId = 2 and p.PostTypeId is not null
    GROUP BY
        v.PostId,
        v.CreationDate,
        p.CreationDate,
        p.OwnerUserId,
        p.PostTypeId,
        p.Score
    ) AS tmp
    
WHERE tmp.score > 0
GROUP BY
    tmp.[Post Link],
    tmp.posttype,
    tmp.[User Link],
    tmp.score,
    tmp.[Age]
)

SELECT TOP 1000
    type AS [ ],
    pid AS [Post Link],
    uid AS [User Link],
    age AS [Age],
    score AS [Score],
    vMax AS [Vote Spike],
--    CAST(vNStd / SQRT(vSum) * 100 AS DECIMAL(20,5)) AS [Variance Index],
    CAST(vNStd AS DECIMAL(20, 3)) AS [Type A],
    CAST(score / vNStd AS DECIMAL(20, 3)) AS [Type B],
    Cast(score / 
        (@skewFactor * vNStd + score / vNStd)
        AS DECIMAL(20, 3)) AS [Balance]
FROM rawData
ORDER BY [Balance] DESC

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