It’s getting to that point in the academic year when assignments start piling up – so we’ve been busy too. We’ve added new PlagPointer features, improved the checker and made the site much easier to use, ready for the busy months ahead. Here’s what we’ve been up to in no particular order: If you haven’t … Read more
Almost everyone believes they can spot AI writing. The em dashes. The “it’s worth noting.” The suspiciously balanced conclusion that begins “In conclusion.” The research says otherwise. Across more than half a dozen controlled studies summarised in a 2025 Journal of Artificial Intelligence Research survey by Fraser, Dawkins and Kiritchenko of the National Research Council … Read more
Discusses how to use AI essay writers such as Uniwriter effectively as learning tools, backed by top university AI policies and education research.
There’s a persistent misunderstanding that circulates through classrooms, content marketing teams and online forums alike: the idea that if a work carries a Creative Commons licence, it can be used without attribution 0 and that doing so carries no consequences. It’s an appealing notion, but it’s wrong on both legal and ethical grounds. In fact, … Read more
Summary: Plagiarism detection is a critical component of academic integrity and intellectual property protection. Traditional plagiarism detection systems rely on text-matching algorithms. These tools find identical or highly similar passages between a submitted work and existing sources. However, these methods can fail to detect more subtle forms of plagiarism, such as paraphrasing, ghostwriting, or contract … Read more
Today’s guest post is courtesy of Emma, a lecturer who spends too much of her time marking, advising, and trying to keep pace with changing academic rules. Lately, she’s been struck by a curious contradiction: students may openly acknowledge using ChatGPT in their assignments, but the very same universities come down hard on anyone who … Read more
Summary: Plagiarism detection has evolved into a multifaceted research area at the intersection of text analysis, information retrieval, and natural language processing. The challenge stems from the diverse ways in which plagiarists disguise copied content – ranging from verbatim copy-paste to subtle paraphrasing, structural reordering of text, cross-language translation, or even idea plagiarism that copies … Read more
Summary: Plagiarism remains a serious concern in academia and beyond. It not only includes verbatim copy-paste theft of text, but also disguised plagiarism such as paraphrasing, translating content from another language, or stealing ideas without proper credit. Traditional plagiarism detection software relies mainly on text matching and often fails to catch these sophisticated forms (Maurer … Read more
Summary: Plagiarism detection is a critical concern in academia and publishing, and it traditionally relies on text-matching algorithms to find copied or paraphrased passages. However, conventional plagiarism checkers often struggle to detect more covert plagiarism strategies. For example, heavily paraphrased content or translated text can evade detection by simple string matching. As a result, researchers … Read more
Summary: The most promising technical methods of plagiarism detection over the last 10 years combine deep learning, semantic analysis, and hybrid approaches to address increasingly sophisticated forms of plagiarism. 1. Introduction Over the past decade, plagiarism detection has evolved rapidly, driven by advances in machine learning, deep learning, and natural language processing (NLP). Traditional string-matching … Read more