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During the last few day in the "clogged" suggested-edits review queue, I encountered a suspicious user on an editing spree.

The last 3 days, the user made over 150 pointless tag-only edits (they didn't even add all the necessary tags). All of the user's edits consists of an addition of the tag and a summary of "Added the python tag for code color formatting."

My guess is that the user been using this simple search term for their edit candidates:

-[python*] python is:question

According to this proposed FAQ (How do I make a good edit?):

Don't go on editing sprees

Keep in mind that if you have less than 2,000 rep, all of your edits need to be approved in the suggested edit review queue. Don't waste reviewers' time by searching for and correcting simple errors en masse.

Also, editing a post bumps it to the front page, so don't edit too many posts in quick succession. If you feel the need to search out and correct a simple issue on several posts, please be sure to correct other issues while you're at it.

If you feel that there is an issue that affects a lot of posts, first discuss it here on Meta. Then the community can decide if mass editing is warranted.

When I'm editing or reviewing, I try to follow the three aforementioned points above everything. Of all the pointers made on the proposed FAQ (How do I make a good edit?), the user's edits did not even meet one.


Examples of the user's trivial edits:

This one's very recent, it's still pending for review not anymore, I rejected it.

https://stackoverflow.com/review/suggested-edits/19652911 the edit history in the link isn't correct because I reject+edited the post. For actual proposed edit, see below.

Original question and the edit the user made to it:

Title: How to parse each string in tensor

I have a file that saves the sentence parsing result by stanford parser, as follows:

(NP (NP (NP proud cat) (NP old school)) (NP trick frame))

(VP imke (NP (NP marion and) allison))

Now I load the file by tf.data.Dataset, so I can get a tensor which dtype is tf.string, now I need to parse each string in the tensor by the class Tree, as follows:

class Node(object):
    def __init__(self, word=None):
        self.word = word
        self.left = None
        self.right = None
        self.parent = None
        self.is_leaf = False
class Tree:
    def __init__(self, treeString):
        self.root = self.parse(treeString)
    def parse(self, treeString, parent=None):
        node = Node()
        node.parent = parent
        temp = treeString.split(None, 1)
        if len(temp) == 1:
            node.word = temp[0]
            node.is_leaf = True
            return node
        tag, phrase = treeString[1:-1].split(None, 1)
        temp = sexpr.sexpr_tokenize(phrase)
        if len(temp) == 1:
            temp = phrase.split(" ")
        node.left = self.parse(temp[0], parent=node)
        node.right = self.parse(temp[1], parent=node)
        return node

How can I achieve this function?

tags: [tensorflow], [python]

The bolded tag is the only thing that the user changed.

There's clearly a lot of things that should be edited here, which the editor did not make.

if I was editing this post, this would be the end result:

Title: How to parse each string in tensor with a user defined class?

I have a file that saves the parsed result by the standard parser.

The file is as follows:

(NP (NP (NP proud cat) (NP old school)) (NP trick frame))
(VP imke (NP (NP marion and) allison))

After I load the file with tf.data.Dataset, I get a tensor which it's dtype is tf.string. But I need to parse each string in the tensor with the Tree class.

class Node(object):
    def __init__(self, word=None):
        self.word = word
        self.left = None
        self.right = None
        self.parent = None
        self.is_leaf = False

class Tree:
    def __init__(self, treeString):
        self.root = self.parse(treeString)

    def parse(self, treeString, parent=None):
        node = Node()
        node.parent = parent
        temp = treeString.split(None, 1)
        if len(temp) == 1:
            node.word = temp[0]
            node.is_leaf = True
            return node
        tag, phrase = treeString[1:-1].split(None, 1)
        temp = sexpr.sexpr_tokenize(phrase)
        if len(temp) == 1:
            temp = phrase.split(" ")
        node.left = self.parse(temp[0], parent=node)
        node.right = self.parse(temp[1], parent=node)
        return node

How can I achieve this function?

tags: [python], [tensorflow], [tensor]

I ended up reject+editing the suggested edit.

On second thought, I wouldn't even edit this post, since IMO, it's a bit unclear and lacks a desired result. (And that I do not know enough about tensorflow to make a sophisticated edit...)


There are tons of this kind of edits made by this user in the past few days. The weird part is, most of them ended up being approved. Take the previous example for instance, there were already one user who approved it. Wasn't we, the reviewers, told to only approve edits that fixes all (at bare minimum, most) problems in a post and decline trivial edits?


Discussion questions:

  • I'm I justified to reject or reject+edit this kind of edit suggestions?
  • Is the user justified to make so many trivial edits and still get most of them approved?
    • since most edits got approved, the user wouldn't get the 7 day dan.
    • many of these trivial edits are made on old questions with poor quality, or that it's put on-hold. Editing them will bump poor quality questions onto the front page.
  • If the answers to the first two discussion questions are yes and no, how should these reviewers who approved these trivial edits be handled?

Finally, 1.5 hours of time spent writing this question... Let's us spark some meaningful discussions!

10
  • 7
    you should have mod flagged one of the edits and explained to them. Its not a good idea to call out the user here in meta.
    – Suraj Rao
    Commented May 7, 2018 at 6:42
  • 1
    No response means mod didnt get to your flag yet. Nothing to worry about
    – Suraj Rao
    Commented May 7, 2018 at 6:45
  • 5
    @SurajRao Well it is kind of worrying if some user is still on the spree and the flag is at the bottom of the mod queue. It is a good idea to post here then, to bring more attention to the issue.
    – Lundin
    Commented May 7, 2018 at 6:58
  • @Lundin fair enough.
    – Suraj Rao
    Commented May 7, 2018 at 7:26
  • 6
    I've messaged the user with information on how they should be using suggested edits. Assuming good faith though it's not hard for an editor to see things get approved and see affirmation they're doing something good and so they continue to do said thing. There's probably some reviewing to be done here to see how this user got quite so far along in their "spree" but reviewers generally shouldn't have been afraid to reject these edits and then this wouldn't have gotten as far as it has. Commented May 7, 2018 at 7:39
  • 1
    Clogging up the review queue is all by itself already a good enough reason to never do this. User notified about this meta question. Commented May 7, 2018 at 7:53
  • 3
    Maybe they got inspired by this?
    – rene
    Commented May 7, 2018 at 8:36
  • 1
    To put Hans comment in perspective: the suggested edits review queue never clogs. It requires only two users to approve or reject an edit.
    – Braiam
    Commented May 7, 2018 at 11:14
  • 1
    I've seen something similar with a guy who always changes pubic to public Commented May 7, 2018 at 14:12
  • 2
    @James_Parsons that's... a good edit.
    – Braiam
    Commented May 7, 2018 at 15:11

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