While we encourage healthy discussion and debate with students about academic misconduct and the dangers of contract cheating, we would prefer it if Authorship Reports aren't shared outside your institution’s faculty.
Organizing the report
There are various ways you can streamline the data in your report. Try some of these to help you parse the report easier.
Sort
Use the Sort drop down menu to order the files in each section. This will immediately help separate some files that could be potentially problematic.
Filter
Use the Filter dropdown to hide multiple files from your report using submission data and document details. Select the box next to the data that you want to filter out of the report.
Use this feature to filter out files you think may be irrelevant to your investigation, or to single out files you want to look at in more detail.
To remove the filter, select the x next to the filter.
If you would like to view files you have filtered but not remove the filter, select the Show Dismissed button to reveal all dismissed and filtered files.
Labels
You can attach a label to each file. This will allow you to easily identify certain files and track them throughout the report results.
To open the labels menu for a file, select the file symbol to the left of the file name in any of the tables in the report, or on any of the charts.
Label any files that you find suspicious with the Suspicious label. This will highlight those files with a red symbol throughout the report.
Create your own labels to group and track files of interest. For example, you may want to attach a label to files that belong to the same class.
If you would like to hide a file from the report, give it a Dismiss label. If you would like to view files you have dismissed but not remove the label, select the View Dismissed button at the top of the report to reveal all dismissed and filtered files.
Edit Columns
The report has sorted the data into tables in each section of the report. If at any time you would like to add data from another section into the section you are viewing, select the Edit Columns button above a table.
This will open the Edit Column dropdown. From here, add or remove the columns included in this section’s table.
Select Save Columns to save these columns to this section’s table.
To revert the section’s table back to its default setting, open the Edit Column dropdown again and select Restore Defaults.
Download
Report Download
If you would like to download a .csv version of the report, select the Download button in the top right of the report.
This will open a menu with options on how to customize your download by column and file.
Select the Columns drop down to choose what data you would like to include in the download.
Select the Include data from these papers to choose (through labels) which files you would like to include in the download.
Paper Download
If you would like to download all the files included in the report, select the Download all button at the top of any of the sections.
If you would like to download a single file from the report, select the download icon at the far right of the file row in any of the sections.
Summary
The Summary area will contain issues found in the report. Selecting the issue will take you to that section of the report.
The Summary will flag issues such as:
If there are no issues in the Summary that does not mean that the report does not contain valuable data. The Summary is a way to quickly target potentially problematic results.
Review
The review panel will appear on the right side of the report. From here you can set an Investigation Status from the drop-down. The options are Escalate Investigation, Inconclusive, and Dismiss Investigation. The report will remember the status you have chosen and it will be viewable for anyone you share the report with.
The status you set here will also be visible from within the My Reports area or the dashboard.
Below the Investigation Status, you can leave a summary comment to provide additional information and your thoughts about the report. Again, this comment will be visible to anyone you share the report with or opens from the dashboard.
When you share the report with other Investigators and Product Admins, they will be able to edit both the report status and the summary comment. The last person to edit the report, and the time and date they did so, will be visible at the bottom of the review panel.
Submissions
The Submissions section will show you the files in the report and the date where the report was created.
If you have used the submission ID upload method, then this section will include the assignment, class, similarity score, and submission date of each paper. This data is not available when using the file upload method.
If you are an administrator or investigator, you will also have the ability to download all the files, or each file individually.
Document Details
Document metadata is often used by investigators of academic misconduct as key evidence in their cases. The Authorship Report will gather this information quickly.
Files that are .docx can pull the most complete information. If the metadata cannot be found for a file, then there will be a dash.
Files that are .docx can pull the most complete information. If the metadata cannot be found for a file, then there will be a dash.
Author
The 'Author' is the name given to the file creator.
In .docx files the author is the name of the license holder. This could be a parent, peer, or institution.
The data for the author can be retrieved from .docx and .pdf files.
Last Modified By
This is the last user to open the file and make a change before submission. This should be the same as the author name.
A student may ask a parent or peer to spell check a file before submission, or they may make final amendments on a different machine before they submit.
Last modified by data can only be retrieved from .docx.
Page Sizes
Page size can reveal the origin of a document. There are three types of results:
- US Letter
- A4
- Other
US Letter is the paper standard in North America, Central America, and South America, while A4 is standard for the rest of the world. Files listed as Other either use a different page size than US Letter or A4, or use a combination of page sizes.
If you are based in the UK or Australia, the standard paper size is A4. If you are based in the US, the standard paper size is US Letter. It would be unusual if a file was not the standard paper size for your region. It is worth investigating all paper size inconsistencies.
Page sizes can be retrieved from .doc, .docx, .pdf, and .rtf files.
Created With
The Created With column shows the software used to create the file. This data can reveal how many computers have been used to create the files in the report.
Look out for software such as Kingsoft or WPS Office. While popular in Asia, it would be unusual for a student in an English language speaking country to use this software.
Dates
The report will collect dates that are pertinent to the investigation file and comparison files. This is the date that the file was created and the date the file was last modified.
Short turnovers in between date created and date last modified on lengthier files should be noted as they indicated the copying and pasting of content. This section can also reveal about the methodology of a student; do they generally create a file a few months before a due date? Or a few weeks?
If the author has copied content from a document into a new document, or the author has used the ‘Save as…’ functionality to create a fresh copy of a document, the date created will be refreshed.
Dates can be retrieved from .docx and .pdf files.
Company Name
The Company Name column shows the company that the file creation software is registered to. This data can reveal how many computers have been used to create the files in the report.
Company Name can be retrieved from .docx files.
Essay Integrity
Essay mills and authors looking to hinder similarity matching both abuse text manipulation techniques by trying to pass plagiarized content off as genuine. These techniques are commonly found on YouTube and social media platforms as ways of ‘cheating Turnitin’.
The Essay Integrity section of the report gathers data from each file that could indicate the integrity of the file has been compromised and there has been an intent to commit academic misconduct.
Revisions and Editing Time are displayed in graph form at the top of the section. Use this visual representation of the data to look for outliers in the results.
Expand the graph by selecting it. Close the expanded graph by selecting the x in the top left corner of the graph.
Keywords
Keywords are words and phrases that are known to have been found in contract cheated papers. Often a purchased paper will contain prompts to fill in certain details that a student would inadvertently leave in for submission.
If the file contains any of these keywords on the front page, the number of keywords found will be in the Keywords column. Select the number to jump to the keywords table to view which words were found.
We look for the following words on the first page of a file:
|
Affiliation |
Instructor’s Name |
|
Customer’s Name |
Name of the Student |
|
Date |
Name of the University |
|
Insert |
Student’s Name |
|
Insert Name |
Surname |
|
Institution |
Tutor |
|
Institution Affiliation |
Tutor’s Name |
We only look for keywords on the front page of a file. This is commonly where these incriminating keywords will be found.
Text
If the file contains hidden text, there will be a Yes in the Hidden Text column. Select the Yes to jump to the Text table.
The text table contains the following:
Replaced Characters
There are various alphabets available in most word processors. These different alphabets often have very similar characters that can be swapped into words in an attempt to break up a piece of plagiarized text. For example, there is the Latin alphabet character ‘e’ and the Cyrillic character ‘е’. It is difficult to spot the difference when the text is smaller. When these characters are enlarged the difference is easier to detect.
Turnitin will automatically swap these characters out when scanning a submission for plagiarism so they will not affect the Similarity score. The Authorship Report will display how many of these characters have been detected and display them in the Replaced Characters column.
Hidden Text
Changing the color of text to white, rendering it invisible on the white background of a document, is one way of hiding text in a file. This can be done to hide text in order to increase a word count, thus skewering the similarity score, or in order to hide letters in the spacing of plagiarized content, breaking the passage up.
Hidden text highlights white text. If your document uses white text on a colored background (and therefore visible) the Authorship Report will still highlight this for investigation. Hidden text in the Authorship Report should always be investigated further by viewing the paper text and using the Hidden text flag in the side panel to identify where the white text has been placed.
For most file types, you can open the originally uploaded document in a word processor or a PDF viewer. Select all text and remove its formatting or change the text color to black.
Similarity
This data is only available in reports that have been created using the paper ID upload method.
Look out for files with a similarity score less than 5%, as essay mills/contract cheating companies will write essays with the aim to have a low similarity score. These papers should be investigated further to see if they have used sources and references.
Files with a similarity score of more than 80% imply the content of that file has been plagiarized and therefore was likely not written by the student. Consider discounting these files as the results for these files will not accurately reflect the student under investigation’s writing.
% In Quotes
Hidden quotation marks could influence the amount of quoted material recognized in a document. When an instructor excludes well-referenced matches using the Exclude Quotes functionality, in a manipulated document this would also hide plagiarized content.
Contract cheating companies will also avoid using quotes and quotations in case it accidentally triggers a high similarity score if not excluded
# Of Revisions
Few revisions on files are suspicious. Use this feature to examine a student’s methodology, but usually you should see multiple revisions for a file. If a file hasn’t had many revisions (less than 5) it is an indication that the content has been copied and pasted in from another file and should be investigated further.
If the author has copied content from a document into a new document, or the author has used the ‘Save as…’ functionality to create a fresh copy of a document, the # of revisions would be one.
Editing Time
Editing time is the amount of time spent with the document open and in front of other windows, whether the author is typing or not. This time is saved and added up each time you save your changes.
Short editing times on files are suspicious. This indicates the bulk of the content has been copied into the file. Editing Time will also allow you to observe the methodology of the author. How long do they usually take to craft their work? Compare this data to Dates and Revisions to find out more about the author’s methodology.
If the author has copied content from a document into a new document, or the author has used the ‘Save as…’ functionality to create a fresh copy of a document, the editing time would be reset to '0' in the new document.
This feature may be disabled in some countries for privacy reasons; if this is the case, the value will always be shown as '0'.
Editing times can be retrieved from .docx files.
Writing Consistency
The Writing Consistency section can only gather data for files written in English. If your paper is written in a language other than English, the data in this section should be disregarded.
How we write is habitual, and molded by many various factors (geographical location, education, etc.). The Writing Consistency section uses linguistic analysis to highlight suspicious behavior in a student's writing, such as an American student using British spelling, or a sudden leap in average sentence length. Looking for outliers in the data is key for this section of the report.
Readability, Vocabulary Richness, Average Sentence Length, and Phrases per Sentence are displayed in graph form at the top of the section. Use this visual representation of the data to look for outliers in the results.
Expand the graph by selecting it. Close the expanded graph by selecting the x in the top left corner of the graph.
Spelling Differences
Spelling differences reveals where words have been spelled differently across the files. The table will tell you if the file contains any spelling differences. If it does, selecting Yes will open the Spelling section.
Once open in the document viewer, easily search the file for spelling differences using Ctrl + F.
The Spelling section will show all the relevant word patterns found throughout the files. The report can identify the following word patterns:
- -ER vs. -RE
For example, meter (American) vs. metre (British) - -OR vs. -OUR
For example, color (American) vs. colour (British) - -SE vs. -CE
For example, realize (American) vs realise (British) - -IZE vs -ISE
For example, organize (American vs. organise (British)
Look for files that contain spelling variants different to the majority, and single files that contain both spelling variants.
Select the pattern to see a breakdown of how this spelling pattern is distributed across the files.
Examine the files that contain variants to see if the discrepancies are the result of quotations or citations.
If a student has used a spell-checking software then they could inadvertently use a spelling variation other than their expected one.
Readability
Readability is calculated using a Flesch-Kincaid readability test. These tests are designed to indicate how difficult an English passage is to understand. There are two tests: the Flesch Reading Ease and the Grade Level. Although they use the same core measures (word length and sentence length), they have different weighting factors.
Assuming the text is grammatically correct, the Authorship Report calculates readability using Flesch–Kincaid Grade Level and translates that into the number of years of education generally required to understand this text. It is important to note that this is not the grade level of the author. This formula can be used by anyone to calculate the grade level of a piece of writing. The Authorship Report will save you time by calculating the grade level for you.
The readability score is displayed as a time-series graph at the top of this section. Years of education is displayed up the y-axis and submission dates or file creation date is along the x-axis. By showing the files in order of submission or file creation, you can more accurately see behavioral trends in the data.
If you have created your report using the paper ID method, the submission date will be used as the display point. If you have used file upload, the file creation data found in the document metadata will be used.
File creation date can only be found in .docx metadata. If you are using the file upload method and upload a file type other than .docx, this data will not be displayed.
A student’s writing should improve over time, but look for files that have dramatically different scores. Contract cheated papers can be purchased at various levels. Cheap papers will often be poorly written and would return a low readability score. Alternatively, if a student wanted a better grade and purchased an expensive paper, the readability score could be much higher than their usual standard of writing.
Variation in subject matter and/or assignment length can also lead to a variation in ‘Readability’ results. For example, a one page personal statement compared to a 4000+ word essay.
Vocabulary Richness
Vocabulary richness (Hapax Legomena ratio) calculates the percentage of words in a document that only occur once.
For example, the following sentence contains 8 words with 4 words occurring only once, resulting in a vocabulary richness score of 50%: “The white cat sat on the white mat”
It is important to remember the different levels of writing that can be purchased when considering Vocabulary Richness results. Look for files that have dramatically different results and then examine the files further. Files with shorter word counts or drastically different subject matter can create outlier scores.
Average Sentence Length
Average sentence length is the average number of words per sentence in a document.
Look for patterns in how long the author makes their sentences. Do they use short succinct sentences, or long, drawn out ones? Does the file under investigation conform to this habit? If not, the file should be investigated further.
Phrases Per Sentence
Phrases per sentence is the average number of phrases per sentence in a document. Phrases are sets of words that form a single grammatical piece of a sentence.
There are several types of phrases: noun phrase, verb phrase, adjective phrase, prepositional phrase, adverb phrase, etc. The phrases per sentence score is calculated using top-level phrases; that is, phrases that are not nested inside another phrase.
For example, the sentence "The cat sat on the mat" has two top-level phrases: a noun phrase (The cat) and a verb phrase (sat on the mat). Therefore, in a document containing 100 sentences split into 200 total phrases, the phrases per sentence would be 2.0.
The amount of phrases we use in a sentence is habitual and usually restrained by our writing level. The phrases per sentence should be similar through work written by the same individual. Any outliers should be investigated further.
Images
If certain requirements are met, the report will be able to pull image paths from .docx files.
Images cannot be pulled from any other file type other than .docx.
If this data is available, examine the image paths from each file for unusual or suspicious results. If the images have been added to the document from a computer other than the students, this will be visible in the file path.
Use this feature to compare image conventions of an author. Does only one of the files submitted contain images? Or does a paper contain an excessive amount compared to the others? Some users may even add an image of text as a way to cheat similarity detection. This information should be used as a vehicle to further examine the papers in question.
Image viewer
The image viewer offers insight into how images have been used by a student in their work. This feature will allow you to inspect image naming conventions across files, view cropped images for unusual hidden content, and uncover interesting file paths.
To open the image viewer, select anywhere in the row for that image to the right of the filename.
Once the image viewer has been launched you will be able to see the full image extracted from the file. If the image has been cropped, there will be a white dotted line displaying the area that the image was cropped to.
To display the image information, select the info icon.
This will display all the information that the Authorship Report could pull from the image. This could include;
- the filename,
- the image size as displayed in the file,
- the original image size,
- the type of image,
- and the file path.
Cropped images
If the image has been cropped, you can display how the image appears in the file by selecting the crop icon. It is common for contract essay writers to take screenshots of their entire screen, and then crop the image in the file accordingly.
The uncropped image could contain evidence of contract cheating in the form of suspicious websites open in tabs, visible user names that do not match the supposed author, content in languages that the supposed author is not known to speak.
File paths
The file path of an image could contain a username that does not match the name of the student or belongs to a company or organizations. This would suggest the image (and therefore the file) was created on a different device than the one the student uses.
Download and zoom
To download the image, select the download button.
Zoom in and out of the image using the zoom icons.
Viewing the paper text
Throughout the report selecting the filename of each file will open it in a document viewer. Viewing the actual text of the files can often be an enlightening process, and we recommend referring to the files throughout your investigation.
Once you have opened the document viewer you can use the Insight Panel on the right side to navigate between Flags found in the document, the Overall Similarity of the file, and the Document Details.
Flags
Turnitin’s algorithms look deeply at a document for any inconsistencies that would set it apart from a normal submission. If we notice something strange, we flag it for you to review. An overview of any Flags that have been found in a document are shown in the Flags section of the Insight Panel.
The two types of flags are replaced characters and hidden text. Select the flag from the side panel learn more about it and to highlight it on the paper text.
Learn more about Flags.
Overall Similarity
Opening the paper text in the viewer will also allow you to see the similarity score of the document and instances of the paper text that have been highlighted as similar to content from Turnitin's database or online.
Select the source from the Sources panel to see it highlighted on the paper text.
Learn more about the similarity score and how to interpret it.
Unlike Turnitin's Similarity Report, users will be unable to make changes to the score by excluding sources and matches when opening the paper text from within the Authorship Report.
The similarity score is only available for files in Authorship Reports created through the Authorship Dashboard or using the Paper ID method.
Document Details
The Document Details side panel will provide insights on a file’s metadata, as well as images and spelling usage.
Learn more about the document details panel.
Access this content via the in-product link
To access this guidance, you will need to follow the link from within the product. This guidance has been hidden due to the sensitive nature of the content. We’d like to keep the data that the report finds secret from essay mills so they cannot bring in measures to circumvent it.
While we encourage healthy discussion and debate with students about academic misconduct and the dangers of contract cheating, we would prefer it if The Authorship Report isn’t shared outside your institution’s faculty.