On the surface, plagiarism detection seems simple enough: you copy and paste your text, link to a Google doc or upload your file, press a button, and the plagiarism detector goes to work, carefully analyzing your writing to root out any signs of plagiarism.
But the reality goes much deeper than that. It’s not just about analyzing your work, but also comparing it to other documents, files, reports and essays out there to determine if someone else’s work, phrasing or even their ideas match your own without proper credit or citation.
In addition, many plagiarism detection tools may differ slightly from each other. Some only check websites for plagiarism whereas others check numerous types of documents. In general, however, plagiarism detection works something like this:
The first step in the process is taking a “snapshot” of the text: a broad overview of what it covers and other details, and comparing it to existing sources. These sources differ between different plagiarism checkers but can include academic essays, books, websites, research papers and other people’s submitted documents.
At this stage a basic comparison is done between your document and others in these databases.
The second step involves the actual databases used to compare the submitted text. Many plagiarism checkers use databases that draw upon a variety of text sources. These can be pages collected from the web, academic journals and so on. These items are stored in a specifically structured format that makes them easier and more efficient to search, which is why plagiarism detectors are able to sift through millions of pieces of content so quickly.
Next comes a more thorough comparison. Before your text can be fully and thoroughly compared to other documents and texts in the aforementioned databases, the text has to go through preprocessing. This removes things like formatting (bold, italic, underline) punctuation and white space. This also helps the plagiarism detector to work more efficiently and helps reduce the risk of false positives.
Now that the text has been stripped of its formatting, white space and other extraneous stuff, the system can start to concentrate on finding similarities. With some plagiarism checkers, the text is broken down even further into individual sentences or phrases so that they can be compared individually to the text on different databases.
This is why sometimes, some basic plagiarism checkers will mark a false positive if your submitted content happens to use a common idiom or expression. More advanced algorithms like cosine similarity or Jaccard similarity are used to determine the percentage of “alikeness” that exists between the two text passages.
Depending on the plagiarism checker you use, there’s also the threshold adjustment. Some plagiarism checkers have this adjustment set extremely high, which can allow instances of actual plagiarism to seep through, whereas others have it set low, which can trigger the plagiarism detector over the smallest perceived similarity. Click here to checkout one of the best plagiarism detector tools for your content.
It can be a challenge to find a good “balance” for the threshold, but the best plagiarism detectors have found a “sweet spot” that gives the submitter a better idea of what words or phrases they need to re-evaluate to make their submission more unique. Some programs also let the user adjust this threshold manually.
Finally, a basic report is created showing any instances of direct plagiarism by highlighting the offending phrase or passage and comparing it to the passage found in the database. Some detectors also include a similarity percentage. This is useful for plagiarism like paraphrasing where the concept or core idea is copied but is expressed in different words.
It’s important to remember that no plagiarism detector, not even those using the latest technology of machine learning or artificial intelligence, is 100% foolproof all of the time. Plagiarism detectors also don’t judge whether or not plagiarism has actually occurred, they merely highlight points that could indicate potential plagiarism. It’s up to the writer, publisher, professor or other professional supervising the check to determine if plagiarism is actually involved.
To help fight back against plagiarism, there are also online tools built into several plagiarism detectors that help students or writers to properly cite their works according to various standards.
Originality.AI is trained on both human-written and AI-written texts from the latest versions of ChatGPT and other artificial intelligence writing systems. Despite the advances in AI and its ability to mimic human-sounding writing, there are still tell-tale signs that a piece has been written by a machine. Repetitive sentence structure, inaccuracies and other hallmarks. In addition, just as AI can create content, AI can also be trained to root out the content it creates.
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There are also certain deep learning signs that indicate an AI was used to write a particular piece. The first, perplexity, is how complex a text is. The second, burstiness, compares sentence variation. Since AI is all about looking at patterns and writing accordingly, the lower the writing scores in terms of its perplexity and burstiness, AI is predictable and so too is the content it produces.
Of course, AI tools like ChatGPT and Gemini ontinue to improve, which means that along with them, so too does Originality.AI. Try it now for as little as 1 cent per 100 word scan and scan for either plagiarism, AI-written content or both. By leveraging one of the most advanced plagiarism detectors, you can be confident that your work is bursting with…originality.
