Keyword density helper – This tool comes with a built-in keyword density helper in some ways similar to the likes of SurferSEO or MarketMuse the difference being, ours is free! This feature shows the user the frequency of single or two word keywords in a document, meaning you can easily compare an article you have written against a competitor to see the major differences in keyword densities. This is especially useful for SEO’s who are looking to optimize their blog content for search engines and improve the blog’s visibility.
File compare – Text comparison between files is a breeze with our tool. Simply select the files you would like to compare, hit “Upload” and our tool will automatically insert the content into the text area, then simply hit “Compare” and let our tool show you where the differences in the text are. By uploading a file, you can still check the keyword density in your content.
Comparing text between URLs is effortless with our tool. Simply paste the URL you would like to get the content from (in our example we use a fantastic blog post by Sherice Jacob found here) hit “Submit URL” and our tool will automatically retrieve the contents of the page and paste it into the text area, then simply click “Compare” and let our tool highlight the difference between the URLs. This feature is especially useful for checking keyword density between pages!
You can also easily compare text by copying and pasting it into each field, as demonstrated below.
Ease of use
Our text compare tool is created with the user in mind, it is designed to be accessible to everyone. Our tool allows users to upload files or enter a URL to extract text, this along with the lightweight design ensures a seamless experience. The interface is simple and straightforward, making it easy for users to compare text and detect the diff.
Multiple text file format support
Our tool provides support for a variety of different text files and microsoft word formats including pdf file, .docx, .odt, .doc, and .txt, giving users the ability to compare text from different sources with ease. This makes it a great solution for students, bloggers, and publishers who are looking for file comparison in different formats.
Protects intellectual property
Our text comparison tool helps you protect your intellectual property and helps prevent plagiarism. This tool provides an accurate comparison of texts, making it easy to ensure that your work is original and not copied from other sources. Our tool is a valuable resource for anyone looking to maintain the originality of their content.
User Data Privacy
Our text compare tool is secure and protects user data privacy. No data is ever saved to the tool, the users’ text is only scanned and pasted into the tool’s text area. This makes certain that users can use our tool with confidence, knowing their data is safe and secure.
Compatibility
Our text comparison tool is designed to work seamlessly across all size devices, ensuring maximum compatibility no matter your screen size. Whether you are using a large desktop monitor, a small laptop, a tablet or a smartphone, this tool adjusts to your screen size. This means that users can compare texts and detect the diff anywhere without the need for specialized hardware or software. This level of accessibility makes it an ideal solution for students or bloggers who value the originality of their work and need to compare text online anywhere at any time.
At Originality, our priority 1 is building AI content detection that is as powerful and effective as possible. The AI tech space continues to evolve at an incredible pace, and our team keeps up a constant, thorough practice of research into the state of AI content production and detection so that we can keep our tools operating at peak performance. We also believe that it's essential that AI content detectors be transparent and accountable about the efficacy of their tool, so that users can verify for themselves which tool is best suited to their needs.
To that end, we would like to introduce Orginality's new AI Detector Efficacy Research Tool. This tool adapts some of Orginality's own research techniques for evaluating AI content detectors, and packages them into a simple and accessible user interface for anyone to run on their own machine. Want to see whether a content detector's claims stack up against a particular dataset you'd like to test? This tool makes that easy and straightforward, providing you with helpful graphics to illustrate results, as well as detailed metrics tables to help you to dive deeper.
To start using the tool, first install Docker. The tool runs inside of a Docker container, and this will manage much of the setup for you automatically.
Next, clone or download the github repo for the tool. To download it as a zip file, simply click the green Code button, and select download ZIP from the dropdown. You can extract the contents of the ZIP file into whichever directory you like, but for the rest of this walkthrough I'll assume that it's extracted into the Documents folder.
Alternatively, you can clone the tool by opening the terminal, navigating to your desired directory, and executing the command git clone https://github.com/OriginalityAI/Ai-detector-research-tool-UI
Now, open the terminal and navigate to the directory where you cloned or extracted the github repo. If you used ZIP option extracted to the Documents folder, this can be accomplished by executing the following command:
cd ~/Documents/Ai-detector-research-tool-UI-main
From within this directory, execute the following commands.
docker-compose build
docker-compose up
These will start and configure the Docker environment that manages the tool. After this process is complete, the tool is ready to use by navigating to the URL http://localhost:8080 in your browser.
First, upload a dataset to use for your detector evaluations. Datasets must be a CSV with three headers, input, dataset, and label:
A template for a correctly formatted CSV can be downloaded using the Download Template button. If you don't have a dataset of your own that you'd like to test, you can download our open source default dataset using the Download Default button.
Next, select which detectors you would like to evaluate. Click the name of a detector to include it in testing, and then enter the necessary authentication information for that detector's API. Every detector requires an API key, and some detectors may require additional authentication information, such as Copyleaks' Scan ID. Originality does not provide keys with this tool, so you will need to obtain your own from each service you would like to evaluate before proceeding.
We recommend testing your dataset using the Test button beside the CSV upload before committing to a full evaluation. The Test button will run a trial evaluation against a small subset of your dataset, allowing you to confirm that your CSV is properly formatted, your keys are valid, and the detectors you are evaluating have functioning API endpoints. The test will return a folder containing your results. Be sure to check the output.CSV file to confirm that all rows of the test dataset were submitted successfully - if any rows failed, error details will be given in the error_log column of this CSV.
Click Evaluate to submit your full dataset and begin your evaluation. For especially large datasets, this evaluation can take several minutes. Once the evaluation is complete, results for each detector will appear in the Results field below.
Each detector's results will include a confusion matrix and a score table containing performance on key metrics. Additionally, by clicking the Download button, you can download a ZIP file containing the confusion matrix, score table, and a CSV detailing the result for each datapoint. A ZIP file containing all detector results can be obtained using the Download All button in the top right of the results field.
The tool returns a variety of metrics for each detector you test, each of which reports on a different aspect of that detectors performance, including:
- Sensitivity (True Positive Rate): The percentage of the time the detector identifies AI correctly.
- Specificity (True Negative Rate): The percentage of the time the detector identifies humans correctly.
- Accuracy: The percentage of the detectors predictions that were correct
- F1: The harmonic mean of Specificity and Precision, often used as an agglomerating metric when ranking performance of multiple detectors.
If you'd like a detailed discussion of these metrics, what they mean, how they're calculated, and why we chose them, check out our blog post on AI detector evaluation. For a succinct upshot, though, we think the confusion matrix is an excellent representation of a model's performance.
A confusion matrix is a table that describes the performance of a detector on a particular set of text samples. The upper left cell of the table shows the true positive rate for that detector, meaning how often it was able to accurately identify AI written text as AI written. The lower right cell of the table shows the true negative rate of the model, meaning how often it was able to accurately identify human written text as human written. For these true rates, a higher percentage is better.
The lower left cell of the table shows the false positive rate, meaning how often that detector mistakenly identified human writing as written by AI. The upper right cell of the table shows the false negative rate, meaning how often that detector mistakenly identified AI writing as written by a human. For these false rates, a lower percentage is better.
We hope this tool makes evaluating AI detectors easier and more accessible to the public, which in turn helps to keep generative AI content creation aligned with the interests and values of the companies and users integrating it into their products to achieve their goals. The tool is free and completely open source, and we welcome any feedback on extensions or improvements. Consider giving it a try, and seeing for yourself how the landscape of AI detectors measure up against the content that matters to you.
No, that’s one of the benefits, only fill out the areas which you think will be relevant to the prompts you require.
When making the tool we had to make each prompt as general as possible to be able to include every kind of input. Not to worry though ChatGPT is smart and will still understand the prompt.
Originality.ai did a fantastic job on all three prompts, precisely detecting them as AI-written. Additionally, after I checked with actual human-written textual content, it did determine it as 100% human-generated, which is important.
Vahan Petrosyan
searchenginejournal.com
I use this tool most frequently to check for AI content personally. My most frequent use-case is checking content submitted by freelance writers we work with for AI and plagiarism.
Tom Demers
searchengineland.com
After extensive research and testing, we determined Originality.ai to be the most accurate technology.
Rock Content Team
rockcontent.com
Jon Gillham, Founder of Originality.ai came up with a tool to detect whether the content is written by humans or AI tools. It’s built on such technology that can specifically detect content by ChatGPT-3 — by giving you a spam score of 0-100, with an accuracy of 94%.
Felix Rose-Collins
ranktracker.com
ChatGPT lacks empathy and originality. It’s also recognized as AI-generated content most of the time by plagiarism and AI detectors like Originality.ai
Ashley Stahl
forbes.com
Originality.ai Do give them a shot!
Sri Krishna
venturebeat.com
For web publishers, Originality.ai will enable you to scan your content seamlessly, see who has checked it previously, and detect if an AI-powered tool was implored.
Industry Trends
analyticsinsight.net
Tools for conducting a plagiarism check between two documents online are important as it helps to ensure the originality and authenticity of written work. Plagiarism undermines the value of professional and educational institutions, as well as the integrity of the authors who write articles. By checking for plagiarism, you can ensure the work that you produce is original or properly attributed to the original author. This helps prevent the distribution of copied and misrepresented information.
Text comparison is the process of taking two or more pieces of text and comparing them to see if there are any similarities, differences and/or plagiarism. The objective of a text comparison is to see if one of the texts has been copied or paraphrased from another text. This text compare tool for plagiarism check between two documents has been built to help you streamline that process by finding the discrepancies with ease.
Text comparison tools work by analyzing and comparing the contents of two or more text documents to find similarities and differences between them. This is typically done by breaking the texts down into smaller units such as sentences or phrases, and then calculating a similarity score based on the number of identical or nearly identical units. The comparison may be based on the exact wording of the text, or it may take into account synonyms and other variations in language. The results of the comparison are usually presented in the form of a report or visual representation, highlighting the similarities and differences between the texts.
String comparison is a fundamental operation in text comparison tools that involves comparing two sequences of characters to determine if they are identical or not. This comparison can be done at the character level or at a higher level, such as the word or sentence level.
The most basic form of string comparison is the equality test, where the two strings are compared character by character and a Boolean result indicating whether they are equal or not is returned. More sophisticated string comparison algorithms use heuristics and statistical models to determine the similarity between two strings, even if they are not exactly the same. These algorithms often use techniques such as edit distance, which measures the minimum number of operations (such as insertions, deletions, and substitutions) required to transform one string into another.
Another common technique for string comparison is n-gram analysis, where the strings are divided into overlapping sequences of characters (n-grams) and the frequency of each n-gram is compared between the two strings. This allows for a more nuanced comparison that takes into account partial similarities, rather than just exact matches.
String comparison is a crucial component of text comparison tools, as it forms the basis for determining the similarities and differences between texts. The results of the string comparison can then be used to generate a report or visual representation of the similarities and differences between the texts.
Syntax highlighting is a feature of text editors and integrated development environments (IDEs) that helps to visually distinguish different elements of a code or markup language. It does this by coloring different elements of the code, such as keywords, variables, functions, and operators, based on a predefined set of rules.
The purpose of syntax highlighting is to make the code easier to read and understand, by drawing attention to the different elements and their structure. For example, keywords may be colored in a different hue to emphasize their importance, while comments or strings may be colored differently to distinguish them from the code itself. This helps to make the code more readable, reducing the cognitive load of the reader and making it easier to identify potential syntax errors.
With our tool it’s easy, just enter or upload some text, click on the button “Compare text” and the tool will automatically display the diff between the two texts.
Using text comparison tools is much easier, more efficient, and more reliable than proofreading a piece of text by hand. Eliminate the risk of human error by using a tool to detect and display the text difference within seconds.
We have support for the file extensions .pdf, .docx, .odt, .doc and .txt. You can also enter your text or copy and paste text to compare.
There is never any data saved by the tool, when you hit “Upload” we are just scanning the text and pasting it into our text area so with our text compare tool, no data ever enters our servers.
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This table below shows a heat map of features on other sites compared to ours as you can see we almost have greens across the board!
