1. Introduction

Plagiarism involves taking someone else’s work, ideas, words, images, or other intellectual property and presenting it as your own. This can include copying text without proper credit, buying or stealing someone else's work and claiming it, or using information from the internet without citation. As a form of intellectual theft, plagiarism is a major academic offense and, in some cases, is punishable by law ^{[1][2][3][4][5]}.

Artificial Intelligence (AI) refers to the capability of computers or machines to emulate human intelligence and behavior. It is employed in solving complex problems and executing tasks that typically require human intelligence, such as visual perception, language comprehension, decision-making, and problem-solving. AI systems can be trained with algorithms to recognize patterns, learn from experience, and make decisions with minimal human input ^[6][7].

AI can effectively detect plagiarism through Natural Language Processing (NLP) ^[8][9][10] technologies that analyze text for similarities across documents. NLP algorithms evaluate the frequency and arrangement of words and phrases to ascertain document similarity. By breaking down text into words, phrases, and sentences, AI tools can compare it against vast amounts of sources to identify parallels. Moreover, these tools can detect patterns like synonym usage and paraphrasing, which are tactics often used to disguise plagiarism.

AI tools are favored for plagiarism detection as they provide quicker and more accurate results than manual checks. They can analyze extensive datasets quickly, discerning patterns that might indicate plagiarism. Additionally, AI tools can verify references and citations, ensuring all sources are properly credited ^[11][12][13]. These tools can compare sentence structures, word choices, grammar, and more to gauge similarity between texts. They can also cross-reference documents against a large database of online content, including other student essays, to spot potential plagiarism.  Table 1 shows a list of some of the tools used in plagiarism detection.

Table 1. A list of some of the plagiarism detection tools and their description

The mean objective of this paper is to conduct a thorough review of existing literature to understand current trends and advancements in plagiarism detection tools. This involved reviewing academic papers, conference proceedings, industry reports, and online resources.

The search strategy for the paper references was to utilize online databases such as IEEE Xplore, Google Scholar, and JSTOR to identify relevant studies. Keywords used included "AI plagiarism detection," "plagiarism tools," and "academic integrity."

The criteria for inclusion that was followed in this paper is to identify a range of popular tools based on market presence, user reviews, and academic references. Tools were selected to represent a mix of price ranges, capabilities, and user bases.

The sample tools did include a variety of tools in the review, such as Turnitin, Grammarly, Copyscape, and others, to provide a balanced overview of options available in the market.

The metric selection that was used in this paper is to develop a comprehensive set of evaluation criteria based on accuracy, efficiency, cost, coverage, ease of use, reporting options, and support.

The scoring system that was used in this paper is to assign scores based on available data and user reviews to rank each tool on each criterion.

Interpret qualitative data from user reviews and academic literature to identify strengths and weaknesses of each tool.

We used tables to summarize and visually present the comparative rankings of tools based on evaluated criteria. We then summarized key insights from the review and proposed recommendations for the development of more sophisticated plagiarism detection technologies.

This paper is structured as follows: Section 2 delves into the state of art of plagiarism detection tools. Section 3 provides a detailed analysis of each tool, discussing their individual features, capabilities, and limitations. Comparative metrics such as accuracy, efficiency, cost, scope, user-friendliness, and support options are explored in Section 4. Section 5 discusses the implications of AI in plagiarism detection, highlighting potential challenges and future directions in the field. Finally, Section 6 concludes the paper with a summary of key findings and recommendations for users selecting a suitable plagiarism detection tool.

2. State of Art Plagiarism Detection Tools

The field of AI tools for detecting plagiarism is evolving rapidly, with numerous companies and research groups developing innovative methods to identify copied text. These advancements employ various approaches, including natural language processing (NLP), machine learning, and semantic analysis.

One prevalent method is NLP, which is used to identify textual similarities. NLP systems leverage algorithms to analyze texts, identifying key words and phrases that may suggest plagiarism. This technique is particularly effective for detecting plagiarism in longer documents, such as essays and research papers.

Machine learning also plays a crucial role in plagiarism detection. These algorithms are trained on extensive datasets containing both original and plagiarized texts. They can recognize similarities, helping to identify potential plagiarism.

Semantic analysis provides another methodology by examining the meanings of words and phrases in a text, rather than focusing solely on spelling and structure. This approach helps detect subtle changes that might indicate plagiarism.

Collectively, these methodologies are driving the development of more sophisticated AI tools for plagiarism detection. These tools are becoming increasingly accurate and are applicable in diverse contexts ^[14].

Types of Plagiarism

Plagiarism, the act of using someone else's work without proper acknowledgment, manifests in various forms, each with unique characteristics and implications. Understanding these different types is crucial for anyone engaged in academic, professional, or creative endeavors to uphold integrity and avoid unintentional misconduct ^[15][16]. The following is a comprehensive list detailing the different forms of plagiarism, ranging from direct copying to subtle practices such as mosaic or self-plagiarism:

1. Direct Plagiarism: This is where someone copies the exact words, ideas, and/or sentences from another person without giving credit.
2. Mosaic Plagiarism: This is where someone borrows phrases from another person without giving credit.
3. 3. Self-plagiarism: This is where someone recycles their own work without giving proper credit.
4. Accidental Plagiarism: This is where someone inadvertently uses another person’s work without giving credit.
5. Paraphrasing Plagiarism: This is where someone paraphrases the words, ideas, or sentences of another person without giving credit.
6. Patchwriting: This is where someone combines words, ideas, and/or sentences from another person without giving credit.
7. Incremental Plagiarism: This is where someone uses a small part of another person’s work without giving credit.
8. Fabrication Plagiarism: This is where someone creates a piece of work based on another person’s work without giving credit ^[17][18].

Table 2 shows the comparison of the different types of plagiarism based on distinct characteristics or aspects of how they occur. The table can help highlight the differences between each type and can clarify the nuances between types of plagiarism, especially regarding intent and source.

Table 2. Comparison of the Different Types of Plagiarism

3. Types of Plagiarism Detection Tools

This section presents an overview of some the popular tools developed for detecting plagiarism. The tools are as follows:

3.1. Plagiarism Checker X

Plagiarism Checker X is recognized for its ability to detect various types of plagiarism, including exact matches, near-exact matches, and paraphrasing. It offers features such as side-by-side text comparisons, color-coded highlights for easy identification, and a percentage-based similarity score to streamline the review process. Although exact efficiency metrics are not publicly disclosed, the tool is generally considered effective for its purpose ^[19]. Table 3 provides an overview of its key properties, strengths, weaknesses, and optimal use cases.

Table 3. An overview of the Plagiarism Checker X and its capabilities

3.2. Grammarly

Grammarly is designed to assist users in improving their written communication across academic, professional, and everyday contexts. Its primary users include students, professionals, non-native English speakers, and organizations focused on writing quality. Key features include personalized style and tone suggestions, along with robust grammar and spell-check capabilities. Grammarly also offers educational resources on grammar and style ^{[20][21][22][23]}. It is trusted by major companies and has been featured in respected publications like The Wall Street Journal and Forbes. Independent studies suggest Grammarly can enhance writing accuracy by up to 25% ^[22]. Table 4 presents an overview of Grammarly, summarizing its main properties, strengths, weaknesses, and optimal applications.

Table 4. An overview of Grammarly

3.3. Turnitin

Turnitin is an online plagiarism detection tool widely used by educational institutions and businesses to identify and deter plagiarism ^[24][25]. It compares submitted documents against a vast database that includes billions of sources such as websites, journals, and student papers, generating originality reports that highlight potential plagiarism and offer resources for education and prevention.

Turnitin is popular among universities, schools, and businesses due to its extensive database coverage, spanning over 50 billion web pages, articles, and books. Although its accuracy is generally over 90%, research indicates that detection accuracy ranges from 95% to 98%, with efficiency varying based on different factors. While effective in detecting plagiarism from published sources, Turnitin does not identify plagiarism from unpublished materials ^[22][26]. With its features, such as originality reports designed to improve writing skills, Turnitin remains a reliable and accurate tool for promoting academic integrity. Table 5 provides an overview of Turnitin, including its history, functionality, and capabilities in plagiarism detection.

Table 5. An overview of Turnitin

3.4. Copyscape

Copyscape searches the internet to find matches for user-provided content. When a match is detected, it provides links for users to compare the content with the source to determine if plagiarism has occurred. Beyond its free service for individual searches, Copyscape offers a paid service for bulk plagiarism checks across multiple documents and the internet.

Renowned for its accuracy and efficiency, Copyscape boasts an accuracy rate exceeding 95%, making it a reliable tool for detecting plagiarism in text, images, and audio formats. While the tool does not specify an exact efficiency rate, it is highly effective in identifying copied content ^[22]. Table 6 provides an overview of Copyscape, highlighting its history, functionality, and capabilities in plagiarism detection.

Table 6. An overview of CoyScape

3.5. PlagTracker

PlagTracker operates as an online tool that scans user documents, comparing them against a database of previously published content from various sources. The generated report highlights potential matches and indicates the percentage of similarity between documents. In addition to detecting plagiarism, PlagTracker offers users tips and advice for avoiding plagiarism in the future.

Known for its efficiency and accuracy, PlagTracker enables users to quickly identify areas of potential plagiarism while offering advanced features such as originality reports and citation analysis. Although it does not provide a specific efficiency rating, its accuracy depends largely on the quality and precision of user input ^[18][22]. Overall, PlagTracker is an effective tool for preventing plagiarism and ensuring the originality of written works.  Table 7 provides an overview of PlagTracker, detailing its history, functionality, and capabilities in plagiarism detection.

Table 7. An overview of PlagTracker

3.6. CopyLeaks

CopyLeaks functions by scanning text-based documents—such as essays, assignments, and research papers—and comparing them against millions of sources, including websites, books, journals, and other publications ^[27]. When similarities are detected, the tool flags potential plagiarism and provides a list of possible sources for users to identify and cite any copied material. It also allows for the comparison of multiple documents to identify patterns of plagiarism.

Widely used by universities, publishers, businesses, and other organizations, CopyLeaks helps protect intellectual property and ensure content originality. Its user-friendly interface and robust functionality make it an efficient and reliable plagiarism detection tool. Although the exact efficiency of CopyLeaks depends on the specific text being checked, it is generally recognized for its effectiveness ^[18][22]. Table 8 provides an overview of its history, functionality, and capabilities in plagiarism detection.

Table 8. An overview of CopyLeaks

3.7. Viper

Viper is a free online tool designed to detect plagiarism across various document types, including essays, assignments, articles, books, and web pages ^[28]. It compares user submissions against billions of sources such as web pages, books, and journals, highlighting sections with similarities and providing detailed reports for further analysis. This helps users identify potential plagiarism and take action to ensure originality and accuracy.

The tool utilizes a sophisticated algorithm to detect similarities and direct copies from online sources. Its features include keyword searches to identify document matches and detection of changes in text formatting, such as font size, style, and spacing. Viper is regularly updated to adapt to new plagiarism tactics.

Praised for its ease of use and detailed reporting, Viper is an ideal choice for students, educators, and anyone seeking to verify the originality of their work. Although the specific efficiency of Viper's detection capabilities is not publicly rated, the tool is estimated to detect up to 98% of plagiarism and has received high ratings in independent tests and reviews. Users consistently report its effectiveness in identifying plagiarism, supported by powerful algorithms that detect even subtle similarities ^[18][22]. Table 8 offers a clear and concise overview of Viper's key properties and capabilities.

Table 8. An overview of Viper.

3.8. ProWritingAid

ProWritingAid, in addition to its plagiarism detection capabilities, provides a suite of features aimed at enhancing writing quality ^[29]. These include grammar and style checkers, a readability scoring system, vocabulary suggestions, and sentence structure analysis. Acting as a virtual writing coach, the tool offers comprehensive feedback and resources to help users refine their writing skills.

The accuracy of ProWritingAid’s plagiarism checker is estimated to be around 95%, though results can vary depending on the quality of the source material checked. While the tool is efficient and widely praised for its performance, it does not guarantee absolute accuracy, and users are encouraged to verify results before making decisions based on its reports ^[22].

Overall, ProWritingAid is valued for its combination of plagiarism detection and writing enhancement features, making it a useful resource for writers aiming to produce high-quality, original content.  Table 9 provides a detailed overview of ProWritingAid’s properties and functionality, consistent with the format used for other tools.

Table 9. An overview of ProWritingAid.

3.9. Unicheck

Unicheck is a robust software that effectively detects and deters plagiarism across various types of academic work, including essays, research papers, theses, and dissertations, both online and offline. It provides comprehensive reports detailing instances of detected plagiarism, empowering users to uphold high standards of academic integrity. Beyond detection, Unicheck offers tools like a plagiarism checker, citation generator, reference checker, author index, and citation guide to help students and educators properly credit sources ^[30].

Unicheck is dedicated to fostering a future where knowledge is respected and intellectual property is protected. The company aims to equip educational institutions with the tools necessary to prevent plagiarism and academic fraud. Using sophisticated algorithms, Unicheck compares documents with online sources to quickly identify potential plagiarism and generate detailed reports that help users understand the origins and reasons for plagiarism.

Additional features include student progress tracking, custom assignment creation, and automatic citation generation for borrowed content. Unicheck is renowned for its efficiency and reliability in enhancing academic integrity, capable of scanning millions of documents worldwide. Its user-friendly interface simplifies the plagiarism checking process, while its detailed reporting system aids users in addressing any detected issues. Although its exact efficiency can vary, Unicheck typically detects between 90-95% of plagiarism instances ^[22].  Table 10 provides a comprehensive overview of Unicheck's capabilities, features, and mission.

Table 10. An overview of Unicheck.

3.10. DupliChecker

Duplichecker is an online plagiarism and duplicate content checker launched in 2011 by the Duplichecker.com team from Autofill SEO Solutions. It has become popular among students, educators, writers, and professionals for ensuring the originality of their work. This free online tool allows users to detect duplicate content and check for plagiarism by scanning and comparing text against billions of web pages and published documents. It provides detailed reports highlighting matched or similar text, making it useful for articles, blog posts, research papers, and other documents ^[31].

Utilizing advanced technology, Duplichecker can search over 20 trillion web pages within seconds, offering fast and accurate plagiarism detection. Users receive detailed reports with options to export them in various formats for further review and action. The tool also features a keyword density checker, grammar checker, and spell checker. Available for free, it also offers various packages, including an enterprise option for businesses needing bulk checks. Regular updates with new features ensure Duplichecker remains comprehensive.

Known for its efficiency, Duplichecker can scan thousands of websites and documents quickly, detecting subtle similarities due to its advanced algorithms. On average, it checks a 2000-word text for plagiarism in about 5 minutes. While generally accurate, the reliability of its results can vary based on the quality of the input content ^[18][22].  Table 11 presents a comprehensive overview of Duplichecker's features and capabilities.

Table 11. An overview of Duplichecker

3.11. Quetext

Quetext utilizes advanced algorithms to identify copied text segments from various sources and offers features such as citation and similarity detection to help users prevent plagiarism and detect potential copyright violations. Each scan provides a comprehensive report that assists users in improving content quality ^[32].

Quetext is efficient in detecting plagiarism, scanning multiple sources quickly to identify potential matches. Its accuracy is notable, capable of detecting even minor plagiarism instances. Additional features include a real-time progress tracker and a customizable list of accepted sources, enhancing its functionality. While the exact efficiency of Quetext's proprietary algorithms is not publicly disclosed, the company claims a 98% accuracy rate, supported by user feedback indicating high satisfaction with the tool’s results ^[18][22].  Table 12 offers a structured overview of Quetext's key features and capabilities.

Table 12. An overview of Quetext.

3.12. Small SEO tools

Small SEO Tools Plagiarism Checker offers comprehensive text scanning and generates reports indicating the percentage of content that is plagiarized. It includes a side-by-side comparison feature, making it easy for users to identify similarities. The tool is particularly useful for individuals, small businesses, and organizations seeking to ensure content originality and compliance with copyright laws ^[33].

Renowned for its high accuracy rate and efficiency, this plagiarism checker can detect copied content even when it has been slightly modified or reworded. However, its accuracy may vary depending on the type of content checked and the tool's quality. Overall, Small SEO Tools Plagiarism Checker is an effective solution for detecting plagiarism across various types of written material ^[18][22].  Table 13 provides a structured overview of the key features and capabilities of the Small SEO Tools Plagiarism Checker.

Table 13. An overview of the Small SEO Tools Plagiarism Checker

Table 14 shows a comparative table summarizing the key features and characteristics of all the plagiarism detection tools discussed. The table provides a comprehensive comparison of the available plagiarism detection tools, highlighting their unique attributes and intended audiences.

Table 14. A comparative summary

4. Comparing Tools to Determine Suitability

Comparing different tools allows us to identify the most suitable option for a specific task by considering factors such as features, performance, cost, and user experience. This assessment not only aids in selecting the appropriate tool but also highlights how various solutions can be integrated to enhance workflow efficiency. In this section, plagiarism detection tools are evaluated and ranked based on several performance measures.

4.1. Accuracy

Accuracy is a critical parameter when evaluating plagiarism checking tools. It measures a tool's ability to correctly identify and flag instances of plagiarism within a text. This is calculated by dividing the number of accurately identified plagiarized phrases or sentences by the total number of checked phrases or sentences.

When ranking plagiarism detection tools based on accuracy, it's important to consider several key criteria that collectively determine how effectively a tool identifies and flags instances of plagiarism. Here are some criteria that have been used for evaluating accuracy:

Detection Capabilities:

Range of Detection: Ability to identify various types of plagiarism, including direct copying, paraphrasing, and idea theft.

Content Types: Coverage across different formats (e.g., text, code, multimedia) to ensure comprehensive detection.

Database Scope:

Size and Diversity: Access to a large and diverse database of sources, including academic journals, books, websites, and other publications.

Frequency of Updates: Regular updates to the database to include new content and reflect current publications.

Precision and Recall:

Precision: The percentage of true plagiarism cases correctly identified by the tool (low false positives).

Recall: The percentage of actual plagiarism cases detected by the tool (low false negatives).

Contextual Understanding:

Semantic Analysis: Ability to analyze context and semantics to prevent misidentifying quotations or common phrases as plagiarism.

Language Support: Competence in handling various languages and translation-based plagiarism.

Algorithm Sophistication:

Machine Learning Integration: Use of machine learning algorithms to improve accuracy over time by learning from past detections.

Natural Language Processing: Advanced NLP techniques to better understand text nuances.

User Feedback and Testing:

Independent Reviews: Evaluation through independent tests and user reviews to validate accuracy claims.

User Impact Analysis: Feedback from educators and professionals regarding the tool's efficacy in different environments.

Error Rate:

False Positives and Negatives: Analysis of instances where the tool incorrectly flags or misses plagiarism.

By evaluating plagiarism detection tools against these criteria, users can more accurately determine which tool best meets their needs in terms of identifying and addressing plagiarism comprehensively and reliably. This systematic approach ensures that the chosen tool not only detects plagiarism effectively but also does so with minimal errors and broad applicability.

High accuracy is essential for selecting a reliable plagiarism checker. Although the accuracy of each tool can vary, a general ranking of the tools based on this criterion ^[5][15]. is shown in table 15.  Note that 1 is the highest rank and 12 is the lowest rank.

4.2. Efficiency

Efficiency is a crucial factor in evaluating plagiarism checking tools, referring to how quickly and accurately they can process documents and detect instances of plagiarism.

When ranking plagiarism detection tools based on efficiency, it is crucial to consider a range of factors that collectively determine how quickly and effectively a tool can process documents and detect plagiarized content. Here are some criteria that we used for evaluating efficiency:

Processing Speed:

Response Time: The time it takes for the tool to process a document and return results.

Batch Processing Capability: Ability to handle multiple documents simultaneously without significant delays.

Scalability:

Performance Under Load: How well the tool maintains speed and accuracy when handling large volumes of data or high server traffic.

Adaptability to Various Document Sizes: Consistent performance regardless of document length or complexity.

Resource Utilization:

System Requirements: The computational resources required to run the tool efficiently (e.g., CPU, memory).

Network Dependency: Reliance on internet connectivity for processing; tools with offline capabilities might offer more versatility.

User Interface and Experience:

Ease of Navigation: Efficiency of completing tasks with minimal clicks or steps.

Report Generation: Speed and clarity in generating comprehensive reports that are easy to interpret and act upon.

Real-Time Detection:

Immediate Feedback: Ability to provide real-time alerts or updates as the document is being reviewed.

Continuous Monitoring: Options for ongoing checks and updates without needing to re-submit documents.

Integration Capabilities:

Compatibility with Platforms: Seamless integration with word processors, CMS, or LMS for streamlined workflows.

API Access: Availability of APIs for custom integration, allowing automated checks within existing systems.

User Feedback and Satisfaction:

User Ratings: Efficiency ratings from educators, students, and professionals who regularly use the tool.

Support and Updates: Quality of customer support and promptness of updates that ensure optimal tool performance.

Evaluating plagiarism detection tools using these efficiency criteria helps users choose a solution that not only detects plagiarism accurately but also does so in a timely and resource-effective manner, enhancing overall user experience and value.

An efficient plagiarism checker effectively identifies copied words and phrases, accurately flags plagiarized content, and differentiates between original and duplicated material. While the efficiency of each tool can vary, a general ranking based on this criterion ^[1][34][35] is shown in table 15.

4.3. Cost

Cost is an important factor when selecting a plagiarism checking tool. It refers to the financial investment required to purchase a plagiarism detection software or service.

When evaluating plagiarism detection tools based on cost, several criteria should be considered to determine the overall value and affordability of each tool. Here's a list of criteria that was used to help with this ranking assessment:

Pricing Model:

Subscription vs. One-Time Fee: Determine whether the tool requires a recurring subscription or a one-time purchase, and identify any additional costs associated with updates or upgrades.

Free vs. Paid Features: Analyze which features are available for free and which require payment, including the existence of a free trial.

Cost per User/License:

Individual vs. Institutional Pricing: Compare pricing structures for individual users versus institutions such as universities or businesses, which might receive bulk or group discounts.

Scalability: Assess whether the cost scales with the number of users or documents, especially for organizations with varying needs.

Feature Set:

Inclusion of Essential Features: Consider if the basic price covers essential features such as comprehensive plagiarism checks, detailed reports, and integrations.

Premium Features: Evaluate the cost-effectiveness of premium features and their added value compared to the base offering.

Hidden Costs:

Additional Fees: Identify any hidden costs such as fees for extensive database access, priority support, or additional document submissions.

Upgrade Costs: Check for costs associated with upgrading to higher-tier plans for enhanced functionality.

Value for Money:

Cost-Benefit Analysis: Consider the overall effectiveness and accuracy of the tool relative to its cost.

Usage Limits:

Document Limitations: Understand any limitations on the number of documents or word count that can be checked within a given pricing tier.

Flexibility in Pricing Plans:

Customizable Plans: Availability of customizable plans tailored to different user needs, and the flexibility to scale up or down as needed.

By evaluating plagiarism detection tools against these cost criteria, users can better gauge which tool offers the best value for their specific needs and budgetary constraints. This approach ensures that users select a tool that not only fits their financial resources but also meets their functional requirements effectively.

The cost generally varies depending on the features and capabilities offered by the tool. Some tools provide basic features such as checking for plagiarism in articles and papers, while others offer advanced functionalities like detecting plagiarism in code and multimedia files. Although the cost of each tool can differ, a general ranking based on pricing ^[1][34][35] is shown in table 15.

4.4. Coverage

The coverage of a plagiarism checking tool refers to the breadth of online and offline sources it can scan to detect plagiarism. These sources include websites, databases, journals, books, magazines, newspapers, and other published materials. Plagiarism checkers employ algorithms and artificial intelligence to identify and flag content that has been copied or closely paraphrased from another source.

When ranking plagiarism detection tools based on coverage, it's important to evaluate how comprehensively each tool scans for potential plagiarism across various sources and content types. Here are some of the criteria that we considered:

Scope of Sources:

Online Databases: Evaluate the range of online databases accessed by the tool, including academic journals, articles, and websites.

Offline Sources: Consider whether the tool can scan offline sources such as textbooks and printed materials through OCR (Optical Character Recognition) technology.

Content Types:

Different Formats: Check if the tool supports scanning of various document formats (e.g., PDF, Word, HTML).

Multimedia Analysis: Determine the tool's ability to detect plagiarism in non-text content such as images, code, or audiovisual material.

Regular Updates to Database:

Frequency: Assess how frequently the tool updates its source database to include the latest publications and web content.

Breadth of Data: Evaluate the comprehensiveness of the data added during updates to ensure coverage includes emerging topics and publications.

Language Support:

Multilingual Capability: Identify the number of languages supported by the tool, which impacts its ability to handle multilingual plagiarism detection.

Translation Detection: Consider whether the tool can recognize translated plagiarism.

Search Depth:

Historical Content: Determine the tool's ability to compare against historical content that may still be relevant but not widely published online.

Partnerships and Licenses:

Academic and Institutional Collaboration: Evaluate partnerships that may enhance the database's breadth, such as collaborations with libraries, publishers, or educational institutions.

User Feedback on Coverage:

User Reviews: Consider insights from users about how well the tool covers various sources and the reliability of its findings.

Real-time Web Crawling:

Dynamic Content Scanning: Check if the tool can perform real-time web crawling to detect newly published content during the scanning process.

By assessing these criteria, users can gain a comprehensive understanding of each tool's capability to cover a broad range of sources and content types, ensuring effective detection of potential plagiarism across diverse materials.

The coverage of sources is crucial when evaluating a plagiarism checker, as it affects the comprehensiveness and reliability of the results. While each tool's coverage varies, the ranking of the tools based on their source coverage ^[1][34][35] is shown in table 15.

3.5. Ease of Use

Ease of use refers to how simple and intuitive a plagiarism detection tool is to operate. This encompasses factors such as user interface design, navigation, learning curve, and the time required to effectively use the program. It also involves the quality of results and the accuracy of plagiarism checks.

When ranking plagiarism detection tools based on ease of use, it is important to consider factors that contribute to a smooth and straightforward user experience. Here are some criteria that we used:

User Interface Design:

Clarity and Aesthetics: Evaluate the visual design of the interface for clarity, attractiveness, and lack of clutter.

Intuitive Layout: Check if the tool's layout is logical and easy to navigate, with clear menus and buttons.

Onboarding and Learning Curve:

Ease of Setup: Assess how easy it is to register, set up, and start using the tool.

Guided Tutorials: Availability of tutorials or walkthroughs that help new users understand how to use features effectively.

Navigation and Workflow:

Streamlined Processes: Determine if the tool allows users to perform tasks with minimal steps and clicks.

Consistency: Ensure that navigation elements are consistent across different sections of the tool.

Access to Features:

Visibility of Key Features: Check if the most commonly used features are easily accessible.

Customization Options: Availability of preferences or settings that can be adjusted to suit individual user needs.

Speed and Responsiveness:

Loading Times: Evaluate how quickly pages and features load, especially during document uploads and analysis.

Real-Time Feedback: Presence of real-time updates or results that enhance user engagement and satisfaction.

Error Handling and Support:

Clear Error Messages: Ensure that error messages are clear and provide guidance to resolve issues.

Availability of Help Resources: Assess the ease of accessing FAQs, help articles, or support channels when needed.

Report Generation:

Ease of Interpretation: Check if reports are easy to read and interpret, with clear visuals and summaries.

Format Options: Availability of multiple report formats for export, such as PDF or HTML.

Compatibility and Integration:

Cross-Platform Compatibility: Evaluate if the tool works smoothly on different devices and operating systems.

Integration with Other Software: Presence of plugins or extensions that allow integration with word processors, content management systems, and learning platforms.

By evaluating plagiarism detection tools against these criteria, users can select a solution that provides a user-friendly experience, making it easier to incorporate the tool into everyday workflows and enhancing overall satisfaction.

Evaluating ease of use is essential, as a user-friendly tool can significantly enhance the experience and efficiency of plagiarism detection. The ranking of the tools based on their ease of use ^[1][34][35] is shown in table 15.

3.6. Reporting Options

Reporting options refer to the different ways users can view the results of a plagiarism check. These typically include a side-by-side comparison of the original and detected plagiarized text, an overview of text matches, a list of sources with matching content, and a summary of the plagiarism report. Some tools may also offer additional reporting features, such as identifying potential offenders or providing a detailed breakdown of the percentage of plagiarized content.

When evaluating plagiarism detection tools based on reporting options, it's important to focus on aspects that provide detailed, clear, and actionable insights into detected plagiarism. Here are criteria that was considered for ranking tools based on their reporting capabilities:

Depth of Analysis:

Detailed Match Information: Reports should include specific details about matched content, such as highlighted text or sentence-level comparisons.

Source Identification: Ability to identify and list all sources where matched content is found, with links or references.

Clarity and Readability:

Visual Representation: Use of charts, graphs, or color coding to represent data and insights clearly.

Structured Layout: Logical organization of information to make it easy to follow and understand.

Customization Options:

Report Customization: Ability to tailor reports to include or exclude specific details based on user preferences or requirements.

Summary and Detailed Views: Options to view high-level summaries or dive into detailed analysis.

Comparison Features:

Side-by-Side Comparison: Functionality to compare original and matching content side by side for easy identification of copied sections.

Paraphrasing and Similarity Detection: Indications of paraphrased content and levels of similarity.

Export and Sharing:

Export Formats: Availability of various export options such as PDF, Word, or HTML to facilitate sharing and documentation.

Sharing Capabilities: Easy sharing of reports via email or integration with other platforms for collaborative review.

Timeliness and Accessibility:

Real-Time Updates: Speed at which reports are generated and any real-time re-evaluation options available.

Accessibility: Easy access to reports from multiple devices or platforms.

Additional Insights:

Statistical Data: Inclusion of statistics such as plagiarism percentage, unique content percentage, and other relevant metrics.

Suggested Actions: Recommendations or actions users can take to rectify or address instances of identified plagiarism.

User Feedback and Customization:

Interactive Elements: Elements within the report that allow users to provide feedback or reasons for matches (e.g., citations, legitimate uses).

By focusing on these criteria, users can assess which plagiarism detection tools offer the most comprehensive and user-friendly reporting options, aiding in better decision-making and understanding of the results.

Evaluating reporting options is crucial, as comprehensive reports can aid in understanding and addressing plagiarism issues effectively. The ranking of the tools based on their reporting capabilities ^[1][34][35] is shown in table 15.

3.7. Support

Customer support is a critical aspect of using plagiarism checking tools, involving the provision of technical assistance to users who have questions or need help with their software. This support can include troubleshooting issues, offering detailed explanations of the software’s functionality, and addressing questions regarding the accuracy of results. Additionally, customer support may assist users in understanding copyright law and the implications of plagiarism.

When assessing plagiarism detection tools based on support, it's essential to focus on the quality, accessibility, and responsiveness of the customer support services offered. Here's a list of criteria that was considered for evaluating the support provided by these tools:

Availability:

24/7 Support: Whether support is available around the clock, which is particularly important for users in different time zones.

Multiple Channels: Access to support through various channels such as email, live chat, phone, and a support ticket system.

Responsiveness:

Response Time: How quickly the support team responds to inquiries and issues, indicating efficiency and reliability.

Problem Resolution: The support team's ability to effectively resolve user issues and provide helpful solutions.

Expertise:

Knowledgeable Staff: Support representatives should have a thorough understanding of the tool and be able to address technical questions proficiently.

Detailed Explanations: Ability to provide clear and detailed explanations or instructions for complex issues.

Resources and Documentation:

Comprehensive FAQs: An extensive FAQ section that covers common questions and troubleshooting steps.

User Guides and Tutorials: Access to detailed user manuals and step-by-step tutorials to assist with learning and troubleshooting.

Community and Forums:

Active User Community: The presence of active user forums or communities where users can share experiences and solutions.

Official Support Forums: Availability of moderated forums where users can seek advice and share feedback with both peers and support staff.

Customer Feedback:

User Satisfaction Ratings: Ratings and reviews from users regarding their experience with the support services.

Feedback Mechanism: Opportunities for users to provide feedback on the quality of support received, contributing to continual improvement.

Training and Onboarding:

Training Sessions: Availability of webinars or training sessions to help users get acquainted with the tool.

Onboarding Assistance: Personalized onboarding support to help new users set up and navigate the tool effectively.

Additional Services:

Follow-Up: Proactive follow-up communications to ensure that issues have been resolved satisfactorily.

Customization Support: Assistance with customizing the tool to better fit organizational needs.

By evaluating plagiarism tools against these support-related criteria, users can choose a solution that offers robust, responsive, and user-centered assistance, enhancing their overall experience and satisfaction.

Effective support services can enhance user experience and ensure that the tools are used appropriately. The ranking of the tools based on their customer support offerings ^[1][34][35] is shown in table 15.

Table 15 compares the different plagiarism checking tools based on multiple performance measures: Accuracy, Efficiency, Cost, Coverage, Ease of Use, Reporting Options, and Support. The table provides a clear comparison of the tools across multiple performance measures, helping to evaluate and select the most suitable option based on user specific requirements. Note that 1 is the highest rank and 12 is the lowest rank.

Table 15. Comparison of the different plagiarism checking tools

The comparative analysis presented in table 15 provides a clear overview of how each plagiarism detection tool performs across seven critical dimensions. This structured assessment allows users to align their selection of tools with their specific needs and priorities.

Accuracy:
Turnitin and Copyscape lead in accuracy, reflecting their strong track record in educational and professional environments. Their extensive databases and refined algorithms contribute to their top rankings. Meanwhile, tools like Small SEO Tools, which rank lower, may be more suitable for basic needs or initial checks rather than comprehensive academic or institutional use.

Efficiency:
The efficiency ranking highlights tools like Turnitin and Copyleaks as optimal for users who need prompt and effective processing of large volumes of documents. These tools efficiently handle complex comparisons, making them preferable for time-sensitive or high-volume scenarios.

Cost:
Plagiarism Checker X and Small SEO Tools score highly in cost-effectiveness, appealing to users or organizations with budget constraints. Conversely, more expensive tools like ProWritingAid and Turnitin might offer extensive features and greater accuracy, justifying their higher cost for those who require robust functionality.

Coverage:
Tools such as Turnitin and Grammarly excel in coverage, benefiting from broad access to diverse sources and extensive databases. This makes them particularly useful for academic institutions and writers seeking thorough analysis across multiple content types.

Ease of Use:
Grammarly and ProWritingAid top the ease of use rankings, thanks to their intuitive interfaces and streamlined navigation. These tools often integrate seamlessly with other applications, offering a user-friendly experience that is accessible to both beginners and experienced users.

Reporting Options:
The top-ranked tools, Grammarly and Turnitin, excel in providing detailed, customizable reports, which help users quickly understand and address potential plagiarism issues. These comprehensive reporting capabilities are crucial for educators and professionals who need precision in documentation.

Support:
Grammarly and Turnitin also lead in customer support, offering round-the-clock assistance and a wide range of resources. High-quality support ensures that users can effectively resolve issues and maximize the benefits of the tools, making them more reliable options for organizations requiring dependable service.

Overall, the table demonstrates that while no single tool is the leader across all categories, each offers distinct advantages based on user needs. Tools like Turnitin and Grammarly are strong contenders for users who prioritize accuracy, comprehensive coverage, and robust support systems. On the other hand, those seeking budget-friendly options with simplicity and basic features may find tools like Plagiarism Checker X and Small SEO Tools more suitable. Users should consider their specific requirements and constraints when selecting the most appropriate plagiarism detection tool.

Table 15 provides insights into the relative strengths and weaknesses of each tool based on multiple performance measures, helping users identify the best option for their specific needs.

5. Discussion

The evaluation of AI-based plagiarism detection tools reveals a diverse landscape where each tool offers unique strengths and addresses specific needs. By examining the tools across several key performance measures—such as accuracy, efficiency, cost, coverage, ease of use, reporting options, and support—certain patterns emerge that align with and expand upon existing literature.

Research consistently highlights the importance of accuracy in plagiarism detection tools (e.g., Turnitin and Copyscape), which have demonstrated high effectiveness due to their vast databases and sophisticated algorithms. These findings are consistent with studies like those by Sharma et al. ^[1], which underscore the utility of extensive datasets combined with advanced matching algorithms for detecting nuanced instances of plagiarism.

In terms of efficiency, tools such as Copyleaks and Turnitin stand out, providing rapid processing times and the ability to handle large document volumes. This corroborates previous research that emphasizes the significance of real-time processing and scalability in educational environments, as noted by Maltseva and Pavlova ^[29].

Cost remains a critical determinant in the selection of plagiarism detection tools, with solutions like Plagiarism Checker X and Small SEO Tools offering cost-effective alternatives for individuals and organizations with budget constraints. This aligns with observations by Naudiyal et al. ^[5], who noted that affordability often drives adoption among smaller academic institutions and non-profit organizations.

Regarding coverage, Grammarly and Turnitin are noted for their comprehensive source databases, which include both online and offline materials. This capability aligns with findings from Koltovskaia ^[20], who emphasized the importance of broad coverage to ensure thorough detection across diverse forms of content, including unpublished documents.

Ease of use and robust reporting options significantly influence user satisfaction and adoption rates. Tools like Grammarly and ProWritingAid, which prioritize user-friendly interfaces and detailed reports, align with literature emphasizing the need for intuitive design and actionable feedback to enhance the user experience ^[21].

The study also highlights that while customer support may vary among tools, those like Grammarly and Turnitin, which offer extensive support resources, are better positioned to assist users in navigating complex issues, as evidenced by Daoud et al. ^[24].

Implications for Future Research

This review indicates several areas for future exploration. First, as linguistic diversity grows, enhancing multilingual support and cultural sensitivity in plagiarism detection tools will be crucial. Second, integrating AI advancements such as deep learning and NLP in evolving tool capabilities presents an opportunity for more context-aware and adaptive systems. Finally, fostering collaborations between tool developers and educational institutions could drive innovations tailored to academic integrity challenges.

Potential Challenges

Despite the benefits, there are notable challenges associated with the use of AI in plagiarism detection. One primary concern is the dependency on underlying datasets, which must be continually updated to account for newly published material and evolving writing styles. Additionally, AI algorithms can sometimes lack nuanced understanding of context, leading to false positives or negatives, especially when interpreting complex expressions or idiomatic language. Addressing privacy concerns and ensuring the ethical use of submitted documents for detection purposes are crucial to maintaining trust in these technologies.

However, several challenges accompany the incorporation of AI into plagiarism detection. A primary concern is the dynamic nature of language; AI systems must continuously evolve to understand new linguistic trends, regional dialects, and nuanced expressions. The rigidity of some AI algorithms may misinterpret the context, resulting in false positives that accuse innocent parties of misconduct, or false negatives that overlook genuine instances of plagiarism.

Another challenge is the ethical use of AI tools. The privacy of individuals whose work is being analyzed must be safeguarded, and transparency regarding data usage and storage must be prioritized. Additionally, access to powerful AI tools may be economically prohibitive for some institutions, creating a disparity in how different organizations handle plagiarism.

Future Directions

Looking ahead, future research in AI-driven plagiarism detection could focus on enhancing context awareness, allowing tools to not only identify similar content but also understand the intent behind it. Developments in unsupervised learning and more robust language models could improve comprehension of subtle variations in writing styles. Furthermore, integrating plagiarism detection into broader academic and professional writing platforms will facilitate seamless usage and foster greater accessibility.

Collaborations between AI researchers, educators, and technologists will be essential in refining these tools and addressing existing limitations. By fostering multi-disciplinary approaches, future advancements can ensure that AI technologies continue to uphold academic integrity, deter misconduct, and protect intellectual property across diverse fields.

To overcome these challenges, future research must invest in developing AI systems that are more adaptive and context-aware. Enhancing unsupervised learning methodologies and integrating deeper semantic analysis could lead to systems that better recognize intent and originality in text. Moreover, cross-institutional collaborations can facilitate the development of shared databases, improving coverage and reducing costs.

Integrating AI tools into existing educational and professional workflows is also paramount. By embedding plagiarism detection into word processors and learning management systems, these tools can offer real-time feedback and learning opportunities for users, fostering a proactive approach to integrity.

Furthermore, engaging in international dialogue to establish ethical standards and best practices will ensure that AI tools are used responsibly and inclusively. Through these efforts, AI-driven plagiarism detection tools can continue to evolve, supporting a future where originality and academic honesty are universally upheld.

In conclusion, the landscape of AI-based plagiarism detection tools is rich with options, each offering distinct features that cater to varying user needs. By understanding these tools in light of both performance metrics and existing research, educators and organizations can better select tools that align with their specific requirements, thereby promoting integrity and originality in academic and professional settings.

6. Conclusion

This paper has examined a range of AI-based plagiarism detection tools, evaluating their performance across key criteria such as accuracy, efficiency, cost, coverage, ease of use, reporting options, and support. The analysis highlights that while no single tool excels in every category, each offers unique strengths tailored to specific user needs and contexts.

Turnitin and Copyscape emerged as leaders in accuracy and coverage, benefiting from extensive databases and sophisticated algorithms that provide reliable detection across various content types. Their comprehensive approaches make them particularly suitable for educational institutions and professional settings where thorough plagiarism checks are essential.

In terms of efficiency, Copyleaks and Turnitin demonstrated rapid processing times and scalability, aligning with the needs of environments that handle large document volumes. These tools' abilities to integrate smoothly into existing workflows enhance their usability and appeal.

Economical options such as Plagiarism Checker X and Small SEO Tools provide cost-effective solutions for individuals and smaller organizations, demonstrating that affordability does not necessarily compromise basic functionality and effectiveness.

Ease of use and detailed reporting, as offered by tools like Grammarly and ProWritingAid, significantly impact user satisfaction, making them popular choices for those seeking intuitive interfaces and actionable insights.

The review also underscores the importance of robust customer support, as exemplified by Grammarly and Turnitin, which can significantly enhance the user experience by facilitating effective navigation of complex tools.

While these tools have advanced considerably, the study suggests further areas for development. Future research should focus on enhancing multilingual support, integrating cutting-edge AI technologies for more nuanced detection, and fostering collaborations with educational institutions to meet evolving academic integrity challenges.

In summary, AI-driven plagiarism detection tools are vital in preserving the integrity and originality of academic and professional work. By selecting tools that align with their specific performance needs, stakeholders can effectively leverage these technologies to promote ethical practices in writing and content creation.