Want to make sure your work is truly yours? The similarity checker in Word highlights what's unique in your document and makes it easier to add citations. You can focus on your writing, knowing that your original ideas stand out and your sources are properly credited.

When the check is complete, Editor shows you how much of your content matches text that it found online (indicated as a percent), and the number of distinct passages in the document for you to review.

Word Similarity Checker

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If Editor finds similarities, click or tap Similarities reviewed. In each section, you'll have the option to insert a citation. A link to the original content can help you decide if you should add a citation. If you feel a citation isn't necessary, select Ignore.

The similarity checker scans every single piece of the given document and finds the matched content within seconds.

It does not highlight the unique content and shows the percentage of matched content in both first and second content files.

I've finished writing my thesis and have done an online plagiarism check. I used -plagiarism.com/ to check and got a lot of plagiarism. I don't understand why. You can find an example below. For instance, I don't see where the plagiarism is in the first sentence which is marked red. When looking into the suggested URL, I don't even find the key words from this sentence there. What should I do?

The reason is that plagiarism is a subtle concept; determining whether some piece of writing P is plagiarized or not requires, in many cases, a proper understanding of the contents of P as well as of the context of P. Understanding those things is far beyond what software can currently (2022) do.

What software tools like the one you showed in your question really do is some kind of automated (probably statistical) analysis of texts, and highlighting of some parts of the text. The output of the software does not determine whether something is plagiarism. The fact that such a tool shows some absurd text message as a result (such as "33% plagiarized content" in your screenshot) tells us something about the software, not about the text it analyzed.

Looking at this particular one, clearly its statistical analysis (or whatever it's doing) is failing pretty badly. In tests on my work it's often not able to identify my original sources (from which there may well be a few phrases I did take verbatim), it suggests I've plagiarised from sources I've never seen, it claims that trivially short phrases and even single words are plagiarised, and, perhaps most astonishingly, it claims that large portions of my text are unique when it's comparing against a copy of that same document.

To see how this particular plagiarism checker works I took a couple of items from my personal technical notes and ran them through it. I picked this item on the technical details of video standards (dropping the last part to get it under 2000 characters) and this item on the design of the CMake language because these notes happen to have taken a particularly large amount of work to properly write up. (The first one because it's a complex topic where I had to use a lot of different sources, and the second one because CMake documentation is just terrible at explaining the core principles of the language design.) I am quite sure that these notes bear little resemblance to the original sources because I wouldn't have had to put such much work into them otherwise. (I am not particularly concerned about plagiarism in the notes I take for personal use in any event, but it's unlikely there would be much anyway because if a source is already in the form I need, I would just link to it rather than re-typing it.)

In the first example it identified 22 "plagiarised" bits. Almost all of them are from pages that were not sources I used. I checked only the first few before it started to seem rather pointless because without exception in the ones I checked the text given in the plagiarism match was from my document and there was nothing resembling that text in the source to which they linked. (In the case of a link to a BBC page, the source had not only no technical information about video standards, but almost no text at all.) Several of the matches were for a single word and, in a particularly hilarious example, the word "this" from the Merriam Webster thesaurus:

In the second example it correctly identified "plagiarism" from my on-line copy of the document linked above. (Given that it's from the same repo on GitHub as the first one, I have no idea why it failed to find the copy of the first one.) But somehow it decided that, though it was comparing against exactly the same document (albeit formatted slightly differently) the copy I'd given it was still "78% Unique Content."

No, plagiarism detectors are not accurate. They produce lots of false positives. All they can do is identify candidates for closer inspection and the bar is usually pretty low on what it takes to become a candidate. From there, it takes a human to carefully review the evidence (the matches) that were found and apply experience and judgement to decide if it's compelling.

They work well for what they're designed to do, quickly comparing a set of submissions against a vast database of possible sources that may have been plagiarized and producing a ranked list of submissions worth reviewing.

We used the MOSS (measure of software similarity) system at Stanford to do cheat-checking for one of our large intro CS classes at Michigan, each time comparing 1000+ new submissions against each other and our archive of roughly 10K prior submissions. This would have been impossible by hand. It scored and ranked the results and did a good job of identifying matching sections. For example, it wasn't fooled by common obfuscation, like variable renaming, simple expression rewriting, statement reordering, rewriting a for as a while, changes to comments, and so on. It really is very good at this.

If it flagged 30 submissions, we might commonly write up six to perhaps a dozen after a careful discussion with my cheat-checking team. We often agreed the rest were a little suspicious, but there just wasn't enough evidence to support a case. By these numbers, you might argue we saw a false positive rate of 40% to 80%. But as a practical matter, what we also experienced was that the cases we reported were usually the ones MOSS ranked highest.

While plagiarism detectors work well at comparing a large set of submissions against another far-larger set of possible sources of plagiarism to find possible matches, they do not work well on an individual submission except to produce a list of the closest matches it found, which may not be good matches at all.

The ranking score for a single result is completely meaningless.Ranking scores are only helpful for sorting a list of suspects (or similarly, search engine results) because rank values only have to obey ordering, not linearity. (A score of .8 may be better than .4, but it's probably not twice as good.) You need the context of other submissions it scored higher or lower to know what a score means.

In your case, you've reviewed the output and decided there's no real match. Good for you. It was a false positive, which is no surprise because these tools generate lots of false positives. (And presumably, you already knew you didn't plagiarize anyway.)

Some similarity checkers are moderately good at finding text that is similar between two documents. If a reputable checker says two sentences are the same, it is almost certain that they actually are. Producing such tool, with a sufficiently comprehensive database of sources to check against, is also very expensive. This is why universities and colleges pay very large sums for access to software like Turnitin. Its unsurprising that a free tool on the internet cannot do such a good job.

There is a reason that often universities don't allow students access to these tools (although this is not universal) - doing so helps them to plagiarize. Reading a source and then rephrasing it sufficiently to pass a plagiarism check is still plagiarism, its just plagiarism that can't be detected as easily. Plagiarism is using other peoples thoughts without attribution, not using their words.

The similarity checker isn't working. I've tried testing it on my other accounts (With Microsoft 365) but it's not working. It keeps saying "Something went wrong" and even when I click "Try again" it doesn't do anything. Ive tried opening the doc and trying it a few times, but its not working.

Mine does not work either and has not for 4 years now. I decided to subscribe to Grammarly because of this issue. It is absolutely ridiculous a tool that simply has not been addressed by Microsoft. I can not believe a company that large just allows this to continue. With Apple, I do not have these issues. If I could get my school to switch to using Apple, I would in a heartbeat. Maybe it will work someday, or they will simply remove it as a feature. Good luck, my friend.

Gaining insight into duplicate content only works if you get your results quickly. There are so many free plagiarism software online that promise to do the job for you. However, a lot of them are clunky, slow, and inaccurate. How can you produce original work without similarity detection you can trust?

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