Plagiarism

 Plagiarism is using or presenting another author’s work or concepts without acknowledging them. Printed or unpublished content, whether documents, published or digitalized forms all fall under plagiarism definition. Plagiarism might be intended or unintended (Ferrero et al., 2017). Under the examination guidelines, intentional or untended plagiarism is a punishable offence. There are different types of plagiarism- verbatim, cut and paste, paraphrasing without giving the author credit. One of the most ignored forms of plagiarism is inaccurate citations. Hence citations should always be accurate.

How Effective Writing Mechanisms Assist In Preventing Plagiarism

Whenever a writer applies or uses the idea of another author, then it is only right for the writer to acknowledge the work or opinion of the original author. Apart from quoting or citing an idea, an author needs to paraphrase another author's concepts or ideas into his or her own words. However, paraphrasing can quickly become plagiarism if inappropriately carried out. Besides presenting another person's opinion, one can make use of his or her ideas so that plagiarism can be prevented altogether (Al-Bayed et al., 2018). Also, one needs to understand the context of the main ideas from the source. Comprehending the main ideas helps in isolating the main idea and using the correct words and phrases to explain the underlying issues uniquely. Subsequently, there are some ideas which do not need citing such as experimental outcomes one gathered from specific research or standard information, well known in the public domain. Lastly, using plagiarism checker can help an author isolate original ideas from plagiarized ones. A plagiarism checker detects and then highlights areas plagiarism by the author. In the end, the author can remove the plagiarized sections and remain only with the recommended sites.

References

Al-Bayed, M. H., & Abu-Naser, S. S. (2018). Intelligent Multi-Language Plagiarism Detection System.

Ferrero, J., Agnes, F., Besacier, L., & Schwab, D. (2017). Usingword embedding for cross-language plagiarism detection. arXiv preprint arXiv:1702.03082.