# User Summary - Most Liked By user attributions are incorrect

**URL:** <https://meta.discourse.org/t/user-summary-most-liked-by-user-attributions-are-incorrect/42668>\
**Category:** Bug\
**Created:** [2016 年 4 月 16 日午後 8:07 UTC](https://meta.discourse.org/t/user-summary-most-liked-by-user-attributions-are-incorrect/42668 "2016-04-16T20:07:30Z")\
**Posts on this page:** 1\
**Showing post:** 20

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**Author:** ![Mittineague](https://sea3.discourse-cdn.com/meta/user_avatar/meta.discourse.org/mittineague/32/114259_2.png) [@Mittineague](https://meta.discourse.org/u/Mittineague)\
**Post date:** [2016 年 4 月 18 日午後 9:47 UTC](https://meta.discourse.org/t/user-summary-most-liked-by-user-attributions-are-incorrect/42668/20 "2016-04-18T21:47:26Z")

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> [@Mittineague](#):
>
> The difference has to do with 2 “parent” categories that do not have any Create Read Reply permissions but are used only to hold sub-categories.
> 
> That pesky LikerGuy1 Liked the “About the” posts for those no-replies “topics”.

A correction is in order (as embarrassing as it s after Likes)  
It _should_ teach me to more thoroughly test _before_ posting results.

Anyway, I decided to repro and had LikerGal1 Like the same parent Cat OPs .  
No repro, ☹

Being a comparatively small localhost forum a lot of numbers have not diverged greatly and I looked for other “two occurrences events” that might be involved.

LikerGuy1 had also Liked 2 “hidden by Flags” posts.  
LikerGal1 did similar, - No repro, ☹

LikerGuy1 had also Liked 2 posts made by anonymous-mode members that were subsequently deleted by a Mod  
LikerGal1 did the same - repro !!

Was it because the posts had been made in anonymous-mode?  
A friendly member made a test post. Another Liked it, then it was Mod deleted. - repro !!

So unfortunately this isn’t as edge case as a topic-less category getting a Like.  
It seems that Liking any post that is subsequently deleted will decrement the post like count, but _will not decrement_ the associated topics like count.

Still a bit edge case I suppose, but maybe worth looking into if topic like count is used in value weighting algorithms.

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