Discover and avoid these types of plagiarism in your next academic paper
Nov 27, 2023 |
10 Mins Read
Originality is crucial in academic research. The initial approval process to conduct research relies on the originality of the idea and the new contribution the paper would make to the area of study. Academic research papers should be varied but rather drive the development of an idea or concept. This acceleration of new knowledge is hindered when plagiarism takes place.
What is plagiarism?
Plagiarism is the practice of presenting another person’s work or idea as your own. In the world of academia, this is a serious offense that can negatively impact a researcher’s career as their papers are usually retracted and they lose their credibility. Educational institutions like universities and colleges can expel and bar students from being admitted to other institutions as this ethical offense is reflected on their record.
Common types of plagiarism
| Type | Definition | How to avoid |
| Direct Plagiarism | Word-for-word duplication of somebody else’s content | - Acknowledge and cite the source. - Paraphrase the content by changing sentence voice (active to passive or vice versa) - Include quotation marks in direct qoutes. |
| Paraphrasing Plagiarism | Original author’s work is restructured very similarly without citing them and their research. | - Use synonyms for non-generic words. - Paraphrase by changing sentence voice and change clauses to phrases. |
| Mosaic Plagiarism | Occurs when phrases are taken from the original author without quotation marks and citations. | - Appropriately cite sources using quotation marks and footnotes. |
| Self-plagiarism | Utilising your own sentence structures and ideas from previously submitted work without citing the source. | - Ensure there is sufficient material to justify the new paper. - Appropriately cite the original source. |
| Patchwork Plagiarism | Occurs when material is copied from several sources and rearranged to create their own flow on a new paper without crediting any new sources. | - Paraphrase material into your own words. - Enclose verbatim content in quotation marks and cite. |
| Accidental Plagiarism | Occurs when the author inaccurately cites sources, misquotes information or unintentionally paraphrases too similarly without the intent to present ideas as their own. | - Proofread research paper multiple times before submitting. - Cite everything that was not discovered by you, including widely-known information. |
How to avoid plagiarism
When working on a research paper, you can try and apply the following strategies to avoid committing plagiarism:
- Cite your sources
When stating an idea or presenting information that you have found through a different source, add the proper in-text citation to indicate that this material is “borrowed”.
- Include quotation marks
When quoting a source verbatim, using quotation marks helps avoid plagiarism and indicates that these words are relevant but not yours. The quote should also include it’s source.
- Paraphrase
Paraphrasing can be tricky as it is a thin line between itself and plagiarism, it involves restructuring ideas into your own words without changing their meaning and intent. This also needs to be appropriately cited.
- Present your ideas
Your research paper should constructively explain your perspective on the information that is cited. Touch on how this is relevant to your findings or argument.
- Use plagiarism tracker
Utilising plagiarism detection tools can help avoid accidental plagiarism. These tools highlight plagiarised content and provide an overall percentage to help users understand their paper’s problem areas.
Ethical writing practices
In academic writing, ethical guidelines demand authors to avoid weaknesses of bias and exclusive language, while encouraging authors to write on a range of perspectives that are relevant to the area of study and clearly indicate through citations where external material has been incorporated into the paper. The infographic below describes 3 strategies to make sure your academic writing skills are in line with ethical guidelines.
Plagiarism detection tools
These detection tools ensure that academic research papers are original. They compare the material to a vast database of existing information and highlight any duplicated material, this helps maintain the author’s credibility and authenticity while avoiding certain legal issues.
Here are a few detectors that Zendy recommends:
In conclusion, plagiarism is a serious academic offense that taints a researcher or student’s career by taking away their credibility and authenticity. Which is why the approval process of academic research is a rigorous one, to ensure the author and researchers have sufficient new contributions and perspectives within a specific area of study. Furthermore, establishing a practice of scanning lengthy research papers against recommended detection tools benefits researchers in citing all content appropriately and even avoids accidental plagiarism.
Speed Up Your Research With “Insights”
'Insights', a brand-new feature designed to make your research experience faster, simpler, and more accessible. Insights gives you short, clear summaries of research papers, pulling out the most important information so you can understand the main points in just a few lines. Instead of reading through pages of dense content, you’ll get a quick overview that helps you decide if the paper is worth exploring further. Here’s how Insights can help: Save time by getting to the heart of a paper faster. Understand complex topics without feeling stuck. Focus on what matters and decide quickly what’s relevant to you. Why We Created Insights? We’ve heard from many of you that keeping up with research can feel like a never-ending task. There’s so much to read, and it’s hard to know where to start. That’s where 'Insights' comes in, to help you make the most of your time exploring the right research paper you are looking for. How Does It Work? Insights uses our AI to scan through a paper and extract key points. It focuses on sections like the introduction, methodology, results, and conclusion, so you can get a clear sense of what the paper is about. You don’t have to worry about missing anything important; it’s all laid out in a simple, easy-to-digest format. Head over to Zendy, search for what you are looking for, and see how Insights can give you a clearer overview in seconds, Check out Insights now!
Responsible AI In Research And Why It Matters
Artificial Intelligence (AI) is changing how we live, work, and learn. However, as AI continues to evolve, it is important to ensure it is developed and used responsibly. In this blog, we’ll explore what responsible AI means, why it is essential, and how tools like ZAIA, Zendy's AI assistant for researchers, implement these principles in the academic sector. What Is Responsible AI? Responsible AI, also known as ethical AI refers to building and using AI tools guided by key principles: Fairness Reliability Safety Privacy and Security Inclusiveness Transparency Accountability AI vs Responsible AI: Why Does Responsible AI Matter? Keep in mind that AI is not a human being. This means it lacks the ability to comprehend ethical standards or a sense of responsibility in the same way humans do. Therefore, ensuring these concepts are embedded in the development team before creating the tool is more important than building the tool itself. In 2016, Microsoft launched a Twitter chatbot called "Tay", a chatbot designed to entertain 18- to 24-year-olds in the US to explore the conversational capabilities of AI. Within just 16 hours, the tool's responses turned toxic, racist, and offensive due to being fed harmful and inappropriate content by some Twitter users. This led to the immediate shutdown of the project, followed by an official apology from the development team. In such cases, "Tay" lacked ethical guidelines to help it differentiate harmful content from appropriate content. For this reason, it is crucial to train AI tools on clear principles and ethical frameworks that enable them to produce more responsible outputs.The development process should also include designing robust monitoring systems to continuously review and update the databases' training, ensuring they remain free of harmful content. Overall, the more responsible the custodian is, the better the child’s behaviour will be. The Challenges And The Benefits of Responsible AI Responsible AI is not a "nice-to-have" feature, it’s a foundational set of principles that every AI-based tool must implement. Here's why: Fairness: By addressing biases, responsible AI ensures every output is relevant and fair for all society’s values. Trust: Transparency in how AI works builds trust among users. Accountability: Developers and organisations adhere to high standards, continuously improving AI tools and holding themselves accountable for their outcomes. This ensures that competition centers on what benefits communities rather than simply what generates more revenue. Implementing responsible AI comes with its share of challenges: Biased Data: AI systems often learn from historical data, which may carry biases. This can lead to skewed outcomes, like underrepresenting certain research areas or groups. Awareness Gaps: Not all developers and users understand the ethical implications of AI, making education and training critical. Time Constraints: AI tools are sometimes developed rapidly, bypassing essential ethical reviews, which increases the risk of errors. Responsible AI and ZAIA ZAIA, Zendy’s AI-powered assistant for researchers, is built with a responsible AI framework in mind. Our AI incorporates the six principles of responsible AI, fairness, reliability and safety, privacy and security, inclusiveness, transparency, and accountability, to meet the needs of students, researchers, and professionals in academia. Here’s how ZAIA addresses these challenges: Fairness: ZAIA ensures balanced and unbiased recommendations, analysing academic resources from diverse disciplines and publishers. Reliability and Safety: ZAIA’s trained model is rigorously tested to provide accurate and dependable insights, minimising errors in output. Transparency: ZAIA’s functionality is clear and user-friendly, helping researchers understand and trust its outcomes. Accountability: Regular updates improve ZAIA’s features, addressing user feedback and adapting to evolving academic needs. Conclusion Responsible AI is the foundation for building ethical and fair systems that benefit everyone. ZAIA is Zendy’s commitment to this principle, encouraging users to explore research responsibly and effectively. Whether you’re a student, researcher, or professional, ZAIA provides a reliable and ethical tool to enhance your academic journey. Discover ZAIA today. Together, let’s build a future where AI serves as a trusted partner in education and beyond.
AI is Transforming Academic Research and Publishing – A Conversation with Kamran Kardan, CEO of Zendy
This blog was originally written by Sabine Louët, founder of SciencePOD, and published on Zendy with permission AI's real potential lies not just in speeding up processes but also in helping users engage more deeply with academic content. Sabine Louët, CEO of SciencePOD sat down with Kamran Kardan, CEO of Zendy to discuss how technology, particularly AI, is reshaping the way researchers and independent scholars access critical information and how research is published. Removing Barriers in Academic Research When asked by Sabine Louët “what drove the creation of Zendy?” Kamran Kardan’s response was clear and purposeful: “Zendy was created to remove the barriers that restrict access to academic research”.He highlights the significant gap that exists for those outside privileged institutions, who often face prohibitive costs or limitations when trying to access essential research. Zendy, he says, aims to make academic content not only affordable but also widely accessible to researchers, students, and professionals globally.Accessing scientific literature remains a privilege reserved for those with institutional affiliations, leaving independent researchers or those from less-resourced regions at a disadvantage. As Kardan puts it, “Zendy is committed to levelling the playing field”, it offers a legitimate alternative to illicit means of accessing research. AI’s Role in Enhancing Research Accessibility AI has become a buzzword, but Kardan stresses the importance of AI in Zendy’s strategy, describing AI as an enabler rather than the focal point. Zendy, he explains, uses AI to enhance user experience by making vast amounts of data more navigable. One of the platform’s key AI-driven features is its summarisation tool, which allows users to quickly digest complex academic papers. With this tool, users can identify relevant content faster and focus their research efforts more effectively. A forthcoming feature called ‘findings’, will use AI to group related articles together, offering a comparative perspective on topics and highlighting differing viewpoints. This tool is designed to empower researchers to explore a topic from multiple angles without having to sift through unrelated material. Safeguarding Research Integrity in the Age of AI Another point of discussion between Sabine Louët and Kardan was the issue of integrity while also leveraging AI. Kardan acknowledges that this is critically important and explains that Zendy is built on principles of transparency and respect for intellectual property. Their AI tools do not merely extract data but give due credit to authors and publishers. In addition, the platform’s revenue-sharing model ensures that content creators benefit from the usage of their work, fostering a more sustainable and fair ecosystem for academic publishing. Kardan also addresses the issue of AI-generated inaccuracies, commonly referred to as “hallucinations”. He emphasises that Zendy's AI is structured to avoid these risks. If the AI does not have sufficient data to provide an answer, it refrains from making assumptions, thus maintaining a high standard of accuracy. AI: Not Just Speed, but Deeper Learning In Kardan’s view, AI's real potential lies not just in speeding up processes but also in helping users engage more deeply with academic content. The tools developed by Zendy are designed to simplify complex materials, making them more approachable for users across various disciplines, without compromising on the depth of information. Louët agrees and notes that these features, particularly AI-driven comparison and summarising tools, align with the needs of modern researchers who require both efficiency and reliability in handling academic content. Looking Ahead: The Future of AI in Research What does the future look like? Kardan foresees more AI advancements that will continue to transform research access, making it more affordable, transparent and equitable. The focus is not just on technology for technology’s sake but on providing meaningful solutions that directly address the challenges of the academic community. “AI’s role in academic publishing is still evolving”, says Kardan, “and Zendy is committed to using AI responsibly to enhance access to knowledge, not to replace human expertise”.