If you are an administrator or departmental administrator, you can create Deanery, Student or Lecturer type of account. They can be imported using XLS or entered manually. Before importing XLS with user data, the administrator must create organizational units. The names of organizational units must be written in the same language and in the same sequence as they are reflected in the anti-plagiarism system. If there is an error, for example, in the name of an email address or organizational unit, the system will show errors in the file, which will be generated and downloaded immediately after you import the file into the system with user data. Errors and their types will be reflected in the rightmost column of the file.
The Interactive Similarity Report is available to each user in editable and non-editable format depending on the user type. The report is available to the student only in a non-editable format, thus the student cannot change the values of the Similarity Coefficient. The similarity report is available in the list of documents on the user account.
If you have forgot your password, click the “You forgot password” button. Enter the email address you used to log into your Strikeplagiarism.com account and click the "Reset Password" button. The system will automatically generate an email with a link that you should use to receive a new password.
To delete your account registered on the StrikePlagiarism.com website as an individual user, use the "Delete" option available on the user account under the "Edit User Data" tab.
If your account was created by an organization administrator, then only the administrator can delete it. Please contact us if the administrator of the organization does not respond to your requests.
Our system has the option “Search for translation plagiarism”. The system has more than 100 language combinations available.
To use this feature, contact us and we will enable it for you. Please remember that the translated text is not the original text and any similarities found require very careful analysis.
Yes! Our system recognizes more than 200 languages including German, Portuguese, Italian, French, Norwegian, Chinese, Spanish, Urdu, Swedish, Dutch, Arabic, Hebrew, Greek, Turkish, Vietnamese, Filipino, Indonesian, Bulgarian, Romanian and many other languages. If you have any doubts or questions, please contact us!
Yes, our system is capable of recognizing AI-generated text with an accuracy of more than 94%.
We are supported by several of the world's leading AI content search algorithm providers and therefore our search is highly effective. The system recognizes text written by AI tools not only in English, but also in Spanish, German, Portuguese, French, Dutch, Swedish and other languages.
All types of accounts (administrator, unit administrator, deanery, student) have the ability to upload documents for verification. Documents for verification can be uploaded in various ways:
- On your account, if the administrator has placed a certain number of checks on the user’s balance. The user can upload documents for verification within this quantity,
- Through an Assignment as a “student”, if the student has been invited to an Assignment. A student can upload to an Assignment only once per Assignment. The student can re-upload the work to the Assignment if the expert returned the work for checking,
- Through the Assignment as a “Lecturer” (supervisor) or “Deanery”, importing the documents and filling in the metadata of the authors,
- Via LMS (Moodle, Canvas, Brightspace, OJS, Blackboard, Schoology etc.).
Processing documents and searching for similarities usually takes a few minutes. During a session, this may take a little longer than usual. Thus, we make every effort to ensure that the verification is carried out efficiently and with a search in all available resources.
All documents are checked and stored by our system in strict accordance with the GDPR. That is, they are stored on your account in our system. All documents and personal data are protected and anonymized. Our servers are located in the EU (France, Poland and Germany). All data is stored only for the entire duration of the plagiarism check, and after the completion of the service and the end of the contract with the client, all data is permanently deleted.
In some cases, at the client's request, data is stored on client servers using the ASAP system or the Internal Search Module.
To use the anti-plagiarism system via the API, you need to contact us. We will create a corporate account and provide an API key. If you would like to use our system via Moodle or another LMS, please contact us and we will help you. For Moodle, you need to first download our plugin from moodle.org, then we will create an API key and help you with the setup.
Interactive Similarity Report for texts that were checked using the “translated similarity search” module are also found in the list of documents. Reports generated by the Translation Similarity Search module are marked in the upper right corner of the report, which reflects the language combination that was used during the check. This data is also available in the document details if you click on the document name in the list of documents.
To improve the quality of the work, its originality and reduce the level of similarity, it is not enough to change the word order as our system will detect such a way of paraphrasing.
We recommend that you take paraphrase seriously and describe in your own way and do not forget to credit the author if the fragment of text used is subject to copyright, that is, it belongs to some author. The main purpose of the check is to prevent plagiarism and thereby give credit to the authors whose materials were used.
To check your paper for AI content, you must either check it individually by registering on the StrikePlagiarism.com portal, or through a corporate account by purchasing a subscription. To purchase a subscription in the form of an organization, please send your request using the form available under the link - contact form.
The Similarity coefficient means the ratio of the text found as similar to the total volume of the text as a percentage. That is, if the similarity coefficient is 16%, this means that 16% of the entire text was found as similar. The Quotation Coefficient refers to the ratio of text enclosed in quotation marks (in the form of quotations) in relation to the total volume of the text. The similarity coefficient does not indicate the presence of plagiarism in the work, but the extent of similarity. That is, if a text found on the Internet (colored green) is a fragment of a law or legal act, then this fragment cannot be plagiarized. If the text, for example, found at the database (highlighted in red) is the author's, but properly credited and the link is legitimate (the correct author), then this fragment cannot be considered plagiarized. And if a fragment of text is found, say, on the Internet or in a database, is copyrighted, but was credited, then this fragment is plagiarized.
The Quotation Coefficient (QC) reflects the text included in quotation marks. QC colors the text purple. It does not indicate the quality of the written work and is for informational purposes only.
SC 1 and 2 differ from each other in that SC1 divides a similar (found in all sources) text into 5 word segments, and KP2 into 25 word segments. SC2 was created in order to show the volume of such text, consisting of large text blocks.
If the teacher notices text fragments that need to be corrected, he can leave a comment in the similarity report by clicking on the Comment button on the right side of the Interactive Similarity Report. All comments left will be available to the student in the list of comments in the similarity report. If students do not have access to the system, the Similarity Report with comments can be forwarded to them using the report forwarding option available in the Interactive Similarity Report on the right side. If students have access to the system, that is, they have accounts, then it is enough to invite them to the Assignment so that they can upload the necessary document to the Assignment. Thus, after the teacher has returned the work for correction by clicking on the Save|Submit button in the upper right corner of the report, the system will send the report to the student’s email address and to his account in our system.
To view more detailed information related to the presence of AI-generated text in the analyzed work, you must open the Interactive Similarity Report, the “Search for AI-generated content” tab and click on Details.
At the end of the work, you must write down the phrase “Bibliography” in any language, and numerate the list.
Our anti-plagiarism system has an Originality Coefficient, which can be added upon request.
Yes, there is such a possibility.
The “Accepted Fragment List” in the Similarity Report reflects the list of fragments that were accepted by the supervisor and excluded from the Similarity Score for various reasons.
To begin with, it is best to use the Interactive Similarity Report, as an HTML or PDF similarity report will not help you find plagiarism. To find plagiarism, you need to pay attention to whether the text fragment is the author’s or not (legal act, folklore, well-known concepts and definitions, etc.). Next, you need to pay attention to whether the author’s fragment was properly credited, and whether it is formatted correctly (in accordance with accepted citation rules). It is also necessary to check whether the author's name is correct, since your author (student) may have mistakenly given a footnote to the wrong author. Thus, if 1. The author is not indicated, but the text fragment certainly belongs to some author, then this fragment is plagiarized. 2. If the author's name is incorrect, this fragment is also considered plagiarized. 3. If one text fragment was credited correctly, and another fragment of the same author has no footnote, or the wrong author was indicated, then that fragment is also considered as plagiarized, even despite the fact that part of the source has the author indicated, or specified correctly. As you can see, the percentage of similarity does not play a role in this analysis.
AI Probability Coefficient (AIPC) means the probability of whether the text was written by a machine, expressed as a percentage. That is, if the AIPC is 34%, this means that the probability that the text was written by AI is 34%. The probability score is generated based on AI content search algorithms, which very effectively determine whether the text was written by a person or a machine. Since the text can be mixed or translated, the AI content search algorithm divides the entire text into small fragments and reflects the probability for each fragment. This makes it easier for the expert and teacher to find a fragment with a high likelihood that it was written by an AI tool.
The similarity report reflects sources from various databases, combining them into groups:
1. sources from the RefBooks Scientific Database, 2. Sources from the University Database, the so-called home database, 3. Sources from databases of other partners and 4. Sources from open Internet sources.
The following characters must be used: "...", «....».
The anti-plagiarism system reflects exceeding the threshold values that were set by the System Administrator in the Settings section. You can record one value for SC 1 and 2, as well as different values for different types of documents in another section - Document Types.
The similarity report can be downloaded as an HTML file and a PDF file in full and short form. The downloaded similarity report will not be interactive, thus it will not be possible to change the SC values by excluding and accepting fragments.
The interactive Similarity Report can be shared, this function is available in the report itself on the right side. The similarity report can be submitted to reviewer. However, if the document was uploaded to the Assignment it can be shared only in a view only mode, otherwise it can be shared both in editable and a view only mode.
The colors in the similarity report do not indicate the presence or absence of plagiarism. Red text indicates that a fragment similar to it was found in partner databases, orange indicates that the fragment was found in the RefBooks database, green indicates that it was found among open Internet sources. If the text is blue, it means you selected all fragments from the same source. Purple text means text was quoted. If fragments of text have different shades of the same color, this means that they are in different places and do not follow each other in the source.
To exclude fragments from the SC, just open the Interactive Similarity Report (not a report in PDF or HTML format) and click on any fragment, after which a dialog box will appear that will prompt you to exclude only a small fragment of your choice or all fragments from this source.
The student can see the comments left by the teacher in the lower left side of the similarity report (Interactive, PDF and HTML).
The system is able to recognize more than 100 different text manipulations. There are so many types of manipulations that we decided to reflect in the Similarity Report only the most frequently occurring ones, including the use of letters from another alphabet, micro-spaces, white characters and spreads. Our system is very successful in resisting text manipulation and is the best in the world in this regard.
The Save|Submit button in the upper right corner of the Interactive Similarity Report has several functions:
1. Allows you to reflect the decision made on the document, for example, if an expert or supervisor decided to accept the work, disqualify it or return it for correction.
2. Once a decision is made, the report status changes to reflect the decision made. Thus, the student or author can see in his list of documents what decision was made regarding the work. This functionality helps when checking a large number of works by one lecturer. Moreover, the system sends a similarity report and information about the decision to the author who uploaded the document by email.
Text colored yellow in the source itself (after you have opened the source in the similarity report) indicates that a similar fragment was found in the work being analyzed. We've simplified the analysis process by loading all sources into the report and displaying them on the left side. That is, by clicking on the source, the system will open the entire source on the left and color all similar fragments yellow. If the source is an Internet page, click on the yellow fragment and the system will reflect it in the analyzed work. Thus, an expert or scientific supervisor needs significantly less time to analyze sources and compare sources with the document being analyzed, as well as analyze to what extent the author legitimately cited the source.
The expert or supervisor can add comments to the similarity report. To add a comment, you must enter the Interactive Similarity Report and select Commenting on the right side of the report.
The system searches among a huge number of sources (more than 2 billion websites, 200 million documents), which at some point in time may be available, but after some time may not be available to the system for objective reasons. Reasons may include: unavailability of the website or database, deletion of data from the website, database, etc.
Cross-checking is a comparative analysis of the papers uploaded into the Assignment. That is, the system shows which fragments of work coincide with each other, despite the fact that the work has not been added to the database.
Anti-plagiarism verification is carried out in the following databases:
- Client database,
- Databases of other client-partners, without the right to access the contents of documents and without indicating the names of the authors,
- Open Internet sources,
- RefBooks scientific database, which contains millions of scientific publications, theses and other types of works in various languages.
The system displays a similar fragment within the source to simplify the process of content search, work analysis and evaluation.
A document can be removed from the database without deleting it from the system by selecting the “Withdraw from database” option in the list of documents in “Actions”. The teacher and administrators can remove a document from the database.
User data on our system is encrypted and protected in accordance with the GDPR. All data is anonymized. The system has passed all the necessary tests and is ISO 27001: 2023 certified.
Documents can be transferred to the StrikePlagiarism.com system in several ways:
1. FTTP access to a section of the database on the client’s server from where we will transfer the data to our server,
2. Using Google drive and a separate Excel sheet with metadata,
3. Manually uploaded by users directly to StrikePlagiarism.com accounts.
There are no such restrictions. Only documents of a readable format, such as Doc, Docx, PDF, RTF, etc. can be added to the StrikePlagiarism.com database.
The system administrator, as well as our technical support team, can delete documents and the entire database.
The system searches for similarities with priority to the internal database; if a document was found in the database, the system will not search for a the same text fragment or a document among open Internet sources.
Sometimes the system does not find some text, despite the fact that a similar fragment is on the Internet. As a rule, the reason may be the fact that the analyzed fragment is very short, for example several sentences. We try not to include a large number of short fragments found similar in the similarity report, because they are not significant for plagiarism analyze.
Another reason may be the “invisibility” of the source for our search engine, in this case, we ask you to contact us for further indexing of the resource.
Yes, the system searches among documents also found in Scopus, Web of Science, EBCO, and so on. The database contains documents from leading scientific publishers, such as Oxford University Press, Hindawi, Nature, Biomed, Springer, BMC and so on. In total, the system has access to materials from more than 20,000 scientific journals and more than 5,000 publishing houses.
Documents are added to the database in three ways:
- Using the feedback button available in the similarity report, when selecting the "Accept" option,
- Automatically after a certain number of days, which is set by the system administrator.
- Automatically immediately after verification.
Access to documents and personal data is restricted. Thus, users of other clients cannot have access to your data or the content of your work. When we compare documents to each other and find similarities between user documents from different clients, we display only the title of the work, the name of the organization and the publication date in the similarities report, anonymizing the information.
The user database is stored in the EU (Germany, France, Poland). We use OVHcloud server resources. US user data is stored on AWS resources.
Document data is stored in the StrikePlagiarism.com database for the duration of the contractual obligations. All user data and documents must be permanently deleted from the StrikePlagiarism.com database in accordance with the GDPR.
It is possible to check documents against the client's database without transferring documents to the StrikePlagiarism.com database. To do this, the documents have to be available for Internet search. However, we do not guarantee that all documents will be found, since at some point in time the website with the client's documents may not be accessible due to dynamic internet and other reasons. As an alternative, we offer installation of our search module in the client's database, thereby, the search will be implemented on the client's server without transferring documents to the StrikePlagiarism.com database. The search module will send us the available metadata of the found document to be reflected in the similarity report.
As a rule, verification process is carried out within a few minutes. A document of more than 100 pages takes longer to check than a document of 10 pages. The larger the document, the longer the verification. The speed of verification is also affected by the seasonal factor. During the summer and winter sessions, documents are checked a little longer than usual. Thus, we ask our clients to take all these factors into account and check the documents in advance, long before the deadlines.
The Assignments module allows to more effectively organize the process of verification of numerous student works for plagiarism, define deadlines, enroll students of specific groups (classes) to the Assignment, monitor the process of uploading works to the Assignment, and view a list of documents for a specific Assignment. One of the main advantages is notification of the status of the work sent directly to the student who uploaded the document.
The Assignments module also allows the teachers cross-check works within a single assignment. Thus, the system allows the teachers to find similar fragments, even when the works have not yet been added to the database.
The teacher can edit the Assignment by clicking on “Edit” in the Actions of Assignment. Thus, the teacher can change the due date and other parameters of the Assignment.
Students can be assigned to the Assignment using the Assignment short code, through which the student can log in and upload a document to the Assignment. The short code is generated automatically by the system when the Assignment is created. Assignments are created for each group (class) separately.
After the teacher clicks on the feedback button in the Interactive Similarity Report and makes a decision on the work, whether the work is disqualified, accepted, or returned for correction, the status of the similarity report changes and the system sends a notification to the student by email about the decision made by the teacher. The notification contains a hyperlink to the similarity report.
It depends on the client settings.
The Assignment in the anti-plagiarism system can be created by a teacher, administrator, or group (department) administrator. To create the assignment, the teacher needs to log in to the account and then select Add at the Assignments.
Yes, it is possible, if the teacher has a sufficient number of “documents” on the balance. To add documents to the user’s balance, the user shall contact the system administrator (for example, through the Help section and the feedback form).
The Assignment Short Code allows to submit a document to a specific Assignment only once. To resubmit a document to the same Assignment (for example, a corrected version of the work), it is necessary for the teacher to change the status of the document to “returned for correction” by clicking on the feedback button in the Interactive Similarity Report. The teacher can return work as many times as was set up by the administrator globally for all Assignments.
Yes, it is possible. The teacher can collect all the works and convert them into a ZIP file, and then upload it to the Assignment, having previously filled in the names and surnames of the authors of the works in the system itself.
The cause of the problem may be a document size limit, a file format that our system does not support, the end of the contract, the end of the client’s (organization’s) balance, and so on. In case of problems, we ask you to go to the Help section and select the feedback form at the bottom of the panel. The user can contact the university system administrator or directly us. We recommend that before contacting us, address your questions to the administrator of the anti-plagiarism system.
Our module detects an AI content generated by all latest versions of ChatGPT, as well as other AI tools such as Bard, Claude 2 and other popular systems.
Yes, it can, since numerous tests have shown its effectiveness. However, we underline that this is just an information system and, like any other system, it cannot give 100% guarantee in accuracy. Additionally, the text that is checked for AI content may be mixed with human text, or it may be human text but paraphrased by an AI tool or another machine. Texts can also be translated by an AI tool while being human texts.
To view more detailed information related to the presence of AI-generated text in the analyzed work, you have to open the Interactive Similarity Report, the “AI content detection” tab and click on Details.
Our module can find AI content in more than 100 languages, including English, Spanish, Italian, French, German, Portuguese, Dutch, Traditional Chinese, Simplified Chinese, Greek, Polish, Vietnamese, Turkish, Ukrainian, Japanese, Korean, Persian, Swedish, Finnish, Estonian, Lithuanian, Latvian, Czech, Romanian, Indonesian, Russian and so on.
The maximum document size that can be checked for AI is 1000 pages.
The tests included 10,000 samples generated by GPT-3 and 20,000 samples each for the other models. As a result of the tests, the detector correctly identified 94% text created by GPT-3,94% text written by GPT-J and 95% text generated by GPT-Neo. The false positive rate is approx 2% for English.
The accuracy of AI content detection is more than 90%.
An AI-generated text must be assessed strictly in accordance with the educational institution's procedures. Our AI content detection module shows text fragments and how likely they are to contain AI generated text. We believe that if a text fragment has a probability of AI content above 60%, it is necessary to pay attention to such text. It is worth discussing this with the student. For example, whether the AI tool was used, in what form and to what extent the AI tool was used. If an educational institution has implemented a rule for citing AI content, then it is necessary to ask the student to make appropriate changes to the text. For example, add a reference to the AI text, so that the independence of the work will not be questioned.
The AI Content Report is contained within the Interactive Similarity Report. In the interactive similarity report, we have added a section - AI content detection, which displays the AI Probability Coefficient, as well as a Details button, by clicking on which you can open the AI content report available in many languages. When you upload a document for review and have the option to search for AI content, the AI content report will be generated automatically, meaning there is no need to take additional action.
Our report displays both the AI Probability Ratio (API) and the AI probability for each piece of text, coloring the pieces in different colors. Each color represents a certain probability of whether the text was written by an AI or a human. The report shows a list of fragments and the AI Probability Ratio for each fragment.
If the text is green, then the probability that it was written by a machine is minimal, if it is red, then the likelihood is maximum.
These colors cannot be manually changed, accepted or rejected by changing the AI Probability Factor. The likelihood that the text was written by a machine is checked by modules and algorithms that are the best at the moment.
Our AI content search module is built into the API and LTI. We decided to develop the module by creating the ability to turn AI search on and off for each task, quiz or discussion. Enabling or disabling AI content search is available when creating an assignment in the LMS.
It is recommended that the student consults the scope, goals and method of using artificial intelligence tools in his/her work with the supervisor or teacher of the course.
The student should describe the tools used and the scope (e.g. literature analysis, creating an introduction, linguistic editing, etc.).
All fragments of the work created using artificial intelligence tools should be provided with a footnote or indicated in an attachment to the work.
We recommend that the supervisor verifies the scope, goals and methods of using artificial intelligence tools by the Student and determines the degree of independence in preparing the thesis at the stage of its acceptance.
In order to verify the use of artificial intelligence tools in written works, the work is checked using the AI detector in the Antiplagiarism system.
If the use of AI tools is detected contrary to the provided guidelines, it is recommended to first clarify the matter with the Student and then make a decision to accept, correct the work or disqualify it, taking into account the Student's overall contribution to the completion of the subject or course of study.
Teachers may define their own rules during classes, then they should be communicated to students either in the class syllabus or in another written form.
StrikePalgiarism.com is integrated with a large number of LMSs, for example, Moodle (all versions), OJS, Canvas, Brightspace, Blackboard, Schoology, Arcanic, Itslearning, Ilias and so on. StrikePalgiarism.com has LTI 1.3, REST API as well as SAML 2.0 and OAuth 2.0. StrikePalgiarism.com can be customized with any LMS via API or LTI.
You shall register on the portal lti.strikeplagiarism.com, then enter the portal and fill out the form. We will receive a notification and activate your account to test the integration.
By following the link you can find information about some integrations. The instructions for all types of integrations are available in our knowledge base.
If you cannot find information about integration with a specific system, please contact us using the form.
It’s very simple, just download the plugin from the website https://moodle.org/plugins/plagiarism_strike and contact us to get an API key.
As a rule, the most common cause of problems with integration is the Cron settings. We ask you to carefully read the administration (installation) instructions to check the settings.
StrikePalgiarism.com supports integration with many LMSs via API. Our Rest API provides ample opportunities for integration with any LMS.