Technology has been very kind to the plagiarist.
Where once the plagiarist would have to re-type the paper or repaint the portrait, content theft now is just a mouse click or a keyboard shortcut away. Worse yet, whole technologies have been built around content theft. For example, RSS scraping applications can steal the content from thousands of feeds in a single hour, creating countless spam blogs.
However, technology is a double-edged sword. At the same time it has made content theft easier than ever, it has also empowered content producers with new, more powerful means of monitoring and enforcing their content rights.
No longer does a copyright holder have to wait to accidentally discover plagiarism or hope that a bystander will alert them, no longer is enforcement a long, arduous process. Every Webmaster, no matter how small, has the tools they need to track and stop theft of their content.
It is simply a matter of knowing where to look.
Prevention
Preventing content theft is something of a holy grail. It is the perfect solution, but also the least practical. The tools needed to prevent copying of work generally do more to annoy legitimate users than to stop plagiarists. That being said, there are a few prevention tools worth taking a look at.
Pictureshark – A hard to remove transluscent watermark is by far the most effective method of preventing image theft. Pictureshark is a fast, free and powerful batch image watermarking tool that can process hundreds of images with a variety of effects.
Devpapers .htaccess Hotlink Protection- For Webmasters that pay their bandwidth bills, image hotlinking is a double problem. Not only is it a form of content theft, but also of bandwidth theft as every load of the plagiarist’s page requires the image be pulled from the original server.Webmasters should test to see if their images can be hotlinkied and, if they can, consider editing the .htaccess file to prevent hotlinking or use a PHP script to achieve that end.
Bad Behavior – A PHP script available for most CMS platforms, Bad Behavior is an anti-spam tool that can also be used to stop some forms of automated content theft. Though not necessarily useful against RSS scraping, any “evil” bots that visit your sites, no matter for what reason, are likely to be caught in Bad Behavior’s net. This can stop malicious spidering and automated saving of content.
Watermark.Ws – Don’t have time to download software to watermark your images? Use Watermark.ws and add your overlays on the Web. Watermark.Ws lets you add text or an image over your copyrighted work and set the alpha level, enabling centrally-located and more powerful watermarks.
Detection
Detecting content theft, though not as desireable as prevention, is a much easier method. There are many tools that can easily detect content theft and, from there, one can easily follow up on it. Best of all, this has no impact on the legitimate readers of your site, just the those that abuse your content.
Google Alerts – Rather than searching for your own content by hand from time to time, let Google Alerts do it for you. Punch in a few unique phrases from your work, set Google Alerts to inform you when those phrases appear on the Web and relax. Best of all, it can be combined with other tools below for an even more powerful experience.
Copyscape – Based upon the Google API, Copyscape enables you to search for plagiarism of an entire page. It looks for content theft that traditional Google searches and Google Alerts may miss including sites that take only a part of your work. The free version is very limited and will only display the top ten results. Thus, it may not be practical for sites that allow some reuse of their content.
Digital Fingerprint Plugin – Maxpower’s Digital Finger Plugin for Wordpress appends a unique phrase or key to the end of every post in your RSS feed. It then offers tools to help you search for that fingerprint on the Web. The plugin also works well with Google Alerts.
Technorati Watchlists – Much like Google Alerts, Techorati watchlists can be used to inform you instantly when unique keywords or a fingerprint appears on another blog. A very powerful tool for blogs.
Google Image Search – Detecting image plagiarism is very difficult, however, if you give your images unique file names you can search for that name in Google image search and locate duplicates of it that way. Most plagiarists do not bother to change image names when putting it up on their site, making it very easy to spot such infringements.
Cessation
Once plagiarism has been detected, it has to be stopped before the detection is of any use. Fortunately, there are several tools to help.
Copyfeed – A veritable swiss-army knife of content protection, Copyfeed not only adds a digital fingerprint to detect infringement, but also can be used to embed IP address of RSS scrapers in the posts andt hen, in turn, ban them from accessing the feed. For Wordpress users, this plugin is practically a must-have.
Ebay VeRO Program – If your content regularly appears on Ebay, it might be worth your time to sign up for Ebay’s Verified Rights Owner Program to enable you to easily close auctions that infringe upon your rights. VeRO is easily the most powerful program of its kind on the Web and worthwhile for any Webmaster that finds a great deal of their work on Ebay.
Reporting
Sometimes, when stopping plagiarism or content theft, you can not take action yourself and, instead, have to report it to someone else. In those cases, there are many different tools and resources to help.
Domain Tools – Need to quickly find out who the host is of a dot com? Domain Tools can help. Just type in the domain and you’ll get all of the information you need about the site. Under “Server Data” you can easily locate all of the information about the server, including who operates it.
DMCA Templates – If you’re going to report a site to a U.S.-based host, you are going to need to file a DMCA notice. To do that, you’ll need a DMCA template. Fortunately, Ian McAnerin has posted templates of DMCA notices on his site, including one for each of the major search engines and a generic ISP one.
Plagiarism Today’s DMCA Contact Information – Once you know who the host is, the question becomes who to contact there. On my site, I’ve compiled a list of links to over 100 of the largest hosts, advertising networks and search engines. If you notice infringing content on a site hosted by one of these companies, just follow the link to report it. Odds are the company you need is somewhere on the list.
U.S. Copyright Office DMCA List – Similar to the list on my site, the United States Copyright Office maintains a list of DMCA contact information for various hosts. Though their list has many more companies, many major hosts have not registered and others have let their information fall out of date. However, it remains an excellent backup. This site requires Acrobat Reader or another PDF viewer to use.
Signature Extension – Instead of copying and pasting the template in every time it is needed, it is much easier to use the Signature Firefox extension and drop it in. Works great with shorter blocks of text and any template you might have use for. Functions well with Webmail systems as well as online reporting systems such as what is found at LiveJournal.
Non-Repudiation
Finally, in the event of a dispute regarding the ownership of the work, it may be important to have some evidence that the work is truly yours. With that in mind, there are some great services to help you verify the creation of your work.
Numly – Numly’s ESN system enables users to register their content, which is then fingerprinted and timestamped, and receive a special number that can be used to retrieve all of the pertinent information on it. Free accounts offer three ESNs per month. A Wordpress plugin is available.
Registered Commons – From the Creative Commons team comes Registered Commons. Like Numly, RC lets you register your work, receive a certificate and an identification number and gives you a timestamp plus a fingerprint of the work. Both Numly and RC allow you to embed Creative Commons Licenses into your work. RC is completely free to use.
Archive.org – The Web Archive, which famously indexes and preserves old versions of Web pages, makes it possible to backtrack and see roughly how long a page was up. Though not as exact as an ESN or a Registered Commons registration, it can be useful in cases where the work was not registered and only a rough answer is needed.
Furl – Though not a non-repudiation service, Furl can be useful in preserving evidence against a plagiarist. A social bookmarking site, Furl also saves a cached copy of every page saved to it, this can be very useful if the plagiarist changes the page or removes the content. It is also valuable for your own records to have a file of what you did and why, just in case the issue comes up again later.
Conclusions
While technology has been kind to the plagiarist, it has been at least as kind to the author. For the first time in history and individual, without any great expense, can reach a worldwide audience and get his message out in numbers never before dreamed of.
Yes, with it comes a risk of plagiarism and content theft, but solutions are being created to mitigate that risk and streamline the process of protecting content and securing author’s rights.
It is and will continue to be a bumpy road, but if one knows how to navigate it, the ride can be more than tolerable.
3.
What is CopyGator ?
This is a free service designed to monitor your RSS feed and find where your content has been republished in the blogosphere. We automatically notify you when a new post of yours is copied to another feed, we also build an overview page you can view to see how/when/where your content is being duplicated, quoted or plagiarized. This is an entirely free service and is powered by the feed spidering power of ://URLFAN. Learn more on how the CopyGator does what he does. or view an example of our content overview page for Gizmodo.com
http://www.copygator.com/
4. Related competitions
1st International Competition on Plagiarism Detection http://www.webis.de/pan-09/competition.php
The detection of plagiarism by hand is a laborious retrieval task---a task which can be aided or automatized. The PAN competition on plagiarism detection shall foster the development of new solutions in this respect.
Competition Tasks
The competition divides into two tasks:
- External Plagiarism Analysis.
Given a set of suspicious documents and a set of source documents the task is to find all text passages in the suspicious documents which have been plagiarized and the corresponding text passages in the source documents. - Intrinsic Plagiarism Analysis.
Given a set of suspicious documents the task is to identify all plagiarized text passages, e.g., by detecting writing style breaches. The comparison of a suspicious document with other documents is not allowed in this task.
Participants may submit results for one or both of the tasks.Award
Yahoo! Research will award a cash prize of 500 Euros to the winner of the competition.
Final Results
In total, we received submissions from 13 out of 21 registered participants. There were 10 submissions for the external plagiarism analysis task and 4 for the intrinsic plagiarism analysis task (1 participant submitted results for both tasks). The competition corpus contains 46,946 plagiarism cases, 36,475 of them in the corpus for the external analysis task, and the remaining 10,471 in the corpus for the intrinsic analysis task.
The following three tables summarize the detection performances of the participants: the first table lists the participants who took part in the external analysis task, the second table lists the participants who took part in the intrinsic analysis task, and the third table lists each participant's overall performance in both tasks. The participants are ranked according to the overal score, which is computed based on the F-measure, precision, recall, and granularity.
How to interpret the results? Take the first row of the first table as an example, and concentrate on the columns Precision, Recall, and Granularity. In this case the participant's precision is 0.7418 which means that 74.18% of his detections are correct, i.e., 25.82% of his detections are incorrect. The recall, on the other hand, is 0.6585 which means that the participant detected 65.85% of the plagiarism which is actually in the test collection, and 34.15% of the plagiarism has gone unnoticed. The granularity value is about 1.0 which, roughly speaking, means that one can expect that the participant's algorithm will detect each plagiarism case at most once.
The column F-measure is a combination of Precision and Recall. Note that here, the absolute values have no semantics attached; it can only be said that the closer the value is to 1, the better the participant's performance is. Likewise, the Overall score is a combination of F-measure and Granularity, so that, again, values close to 1 indicate good performance. In particular, these values cannot be interpreted as percentages. We computed these values to allow for an absolute ranking among the participants which would not have been possible based on Precision, Recall, and Granularity only. The latter, however, are what counts.
External Plagiarism Analysis Task |
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Rank | Overall score | F-measure | Precision | Recall | Granularity | Participant |
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| | | | | | | |
1 | 0.6957 | 0.6976 | 0.7418 | 0.6585 | 1.0038 | C. Grozea Fraunhofer FIRST, Germany |
2 | 0.6093 | 0.6192 | 0.5573 | 0.6967 | 1.0228 | J. Kasprzak, M. Brandejs, and M. Křipač Masaryk University, Czech Republic |
3 | 0.6041 | 0.6491 | 0.6727 | 0.6272 | 1.1060 | C. Basile*, D. Benedetto°, E. Caglioti°, and M. Degli Esposti* *Università di Bologna and °Università La Sapienza, Italy |
4 | 0.3045 | 0.5286 | 0.6689 | 0.4370 | 2.3317 | Y. A. Palkovskii, A. V. Belov, and I. A. Muzika Zhytomyr State University, Ukraine |
5 | 0.1885 | 0.4603 | 0.6051 | 0.3714 | 4.4354 | M. Granitzer, M. Muhr, M. Zechner, and R. Kern Know-Center Graz, Austria |
6 | 0.1422 | 0.6190 | 0.7473 | 0.5284 | 19.4327 | V. A. Scherbinin* and S. Butakov° *American University of Nigeria, Nigeria, and °Solbridge International School of Business, South Korea |
7 | 0.0649 | 0.1736 | 0.6552 | 0.1001 | 5.3966 | R. C. Pereira, V. P. Moreira, and R. Galante Universidade Federal do Rio Grande do Sul, Brazil |
8 | 0.0264 | 0.0265 | 0.0136 | 0.4586 | 1.0068 | E. Vallés Balaguer, using WCopyFind Private, Spain |
9 | 0.0187 | 0.0553 | 0.0290 | 0.6048 | 6.7780 | J. A. Malcolm, P. C. R. Lane, and A. Rainer Ferret, University of Hertfordshire, UK |
10 | 0.0117 | 0.0226 | 0.3684 | 0.0116 | 2.8256 | J. Allen Southern Methodist University in Dallas, USA |
Intrinsic Plagiarism Analysis Task |
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Rank | Overall score | F-measure | Precision | Recall | Granularity | Participant |
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| | | | | | | |
1 | 0.2462 | 0.3086 | 0.2321 | 0.4607 | 1.3839 | E. Stamatatos University of the Aegean, Greece |
2 | 0.1955 | 0.1956 | 0.1091 | 0.9437 | 1.0007 | B. Hagbi and M. Koppel Bar Ilan University, Israel |
3 | 0.1766 | 0.2286 | 0.1968 | 0.2724 | 1.4524 | M. Granitzer, M. Muhr, M. Zechner, and R. Kern Know-Center Graz, Austria |
4 | 0.1219 | 0.1750 | 0.1036 | 0.5630 | 1.7049 | L. M. Seaward and S. Matwin University of Ottawa, Canada |
Overall Tasks |
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Rank | Overall score | F-measure | Precision | Recall | Granularity | Participant |
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| | | | | | | |
1 | 0.4871 | 0.4884 | 0.5193 | 0.4610 | 1.0038 | C. Grozea Fraunhofer FIRST, Germany |
2 | 0.4265 | 0.4335 | 0.3901 | 0.4877 | 1.0228 | J. Kasprzak, M. Brandejs, and M. Křipač Masaryk University, Czech Republic |
3 | 0.4229 | 0.4544 | 0.4709 | 0.4390 | 1.1060 | C. Basile*, D. Benedetto°, E. Caglioti°, and M. Degli Esposti* *Università di Bologna and °Università La Sapienza, Italy |
4 | 0.2131 | 0.3700 | 0.4682 | 0.3059 | 2.3317 | Y. A. Palkovskii, A. V. Belov, and I. A. Muzika Zhytomyr State University, Ukraine |
5 | 0.1833 | 0.4001 | 0.4826 | 0.3417 | 3.5405 | M. Granitzer, M. Muhr, M. Zechner, and R. Kern Know-Center Graz, Austria |
6 | 0.0996 | 0.4333 | 0.5231 | 0.3699 | 19.4327 | V. A. Scherbinin* and S. Butakov° *American University of Nigeria, Nigeria, and °Solbridge International School of Business, South Korea |
7 | 0.0739 | 0.0926 | 0.0696 | 0.1382 | 1.3839 | E. Stamatatos University of the Aegean, Greece |
8 | 0.0586 | 0.0587 | 0.0327 | 0.2831 | 1.0007 | B. Hagbi and M. Koppel Bar Ilan University, Israel |
9 | 0.0454 | 0.1216 | 0.4586 | 0.0701 | 5.3966 | R. C. Pereira, V. P. Moreira, and R. Galante Universidade Federal do Rio Grande do Sul, Brazil |
10 | 0.0366 | 0.0525 | 0.0311 | 0.1689 | 1.7049 | L. M. Seaward and S. Matwin University of Ottawa, Canada |
11 | 0.0184 | 0.0185 | 0.0095 | 0.3210 | 1.0068 | E. Vallés Balaguer, using WCopyFind Private, Spain |
12 | 0.0131 | 0.0387 | 0.0203 | 0.4234 | 6.7780 | J. A. Malcolm, P. C. R. Lane, and A. Rainer Ferret, University of Hertfordshire, UK |
13 | 0.0081 | 0.0157 | 0.2579 | 0.0081 | 2.8256 | J. Allen Southern Methodist University in Dallas, USA |
Winner
We are happy to announce the following winners:
- Task winner of the external analysis task is Cristian Grozea from Fraunhofer FIRST.
- Task winner of the intrinsic analysis task is Efstathios Stamatatos from the University of the Aegean.
- Overall winner of the 1st International Competition on Plagiarism Detection is Cristian Grozea from Fraunhofer FIRST.
Congratulations!Competition Corpus
We have set up a large-scale corpus of artificial plagiarism for the competition. The corpus contains primarily English documents in which all types of plagiarism cases can be found, namely monolingual plagiarism with varying degrees of obfuscation, and translation plagiarism from Spanish or German source documents. The corpus is self-contained, i.e., the source documents of all plagiarism cases are part of the corpus.
To generate artificial plagiarism cases we have employed a random plagiarist: given a text the plagiarist decides whether or not he will plagiarize, from which documents he will plagiarize, how many passages will be plagiarized, and for each plagiarized passage of which type and length it will be. The type of a plagiarized passage may either be obfuscated plagiarism or translated plagiarism. The random plagiarist attempts to obfuscate his plagiarism by applying a random sequence of text operations such as shuffling a word, deleting a word, inserting a word from an external source, or replacing a word with a synonym, antonym, hypernym, or hyponym. Translated plagiarism is created using machine translation.
Corpus Statistics
- Corpus size: 20 611 suspicious documents, 20 612 source documents.
- Document lengths: small (up to paper size), medium, large (up to book size).
- Plagiarism contamination per document: 0%-100% (higher fractions with lower probabilities).
- Plagiarized passage length: short (few sentences), medium, long (many pages).
- Plagiarism types: monolingual (obfuscation degrees none, low, and high), and multilingual (automatic translation).
Corpus Format
In the corpus you will find plain text files encoded in UTF-8, and along each text file an XML file with meta information. The documents are divided into two folders, one with the suspicious documents and the other one with the source documents. Details about the available meta information can be found within the corpus.
Release Plan
The corpus will be released partially during the competition, and in full after competition. For each of the competition tasks a development corpus and a competition corpus will be released. The development corpus will contain annotated artificial plagiarism cases, the competition corpus will contain artificial plagiarism cases without annotation. The former can be used to develop and evaluate your plagiarism detection software while the latter will be used to determine the best plagiarism detection approach. Note that only your success in detecting the plagiarism in the competition corpus will be considered when selecting the winner of the competition.
Download
The full corpus, including annotations of all plagiarism cases for both tasks, can be found here.
The version of the corpus which was used during the comeptition is available on demand.
Performance Measures
The success of a plagiarism detection software will be measured in terms of its precision, recall, and granularity on detecting the plagiarized passages in the corpus. Let s denote a plagiarized passage from the set S of all plagiarized passages. Let r denote a detection from the set R of all detections and let S_R be the subset of S for which detections exist in R. Let |s|, |r| denote the char lengths of s, r and let |S|, |R|, |S_R| be the sizes of the respective sets. The formulas compute as follows:
Remarks.
- We use the character counts in the formulas for precision and recall instead of, for instance, word counts to meet the fact that we cannot know what kind of tokenization approach you will be using. Thus, counting the characters which overlap with plagiarized passages is the safest way to compute these values.
- Recall and precision are well-known measures to assess retrieval performance, but granularity is not. We have added this performance measure to determine whether your plagiarism detection algorithm reports a plagiarized passage as a whole, or rather divided into many small and/or overlaping phrases. The former is preferable since it accounts for a better usability of your tool.
- External plagiarism cases and external detections comprise the chars of both the plagiarized passage and the source passage.
- An external detection r must overlap by at least one char with both the plagiarized passage and the source passage of the corresponding s, otherwise it will not contribute to the recall of s and the precision of r will be set to 0.
Registration
The registration is closed.
To register for participation in the competition send an e-mail to pan09@webis.de which includes the following information:
- name of your group (optional),
- full names, affiliations, and e-mail addresses of all group members,
- the designated group leader, and
- the competition tasks you will be participating in.
You will receive a short notification of you registration from one of the organizers.Result Submission
The deadline for submitting detection results on the competition corpus is June 11, 2009.
The results of your plagiarism detection algorithm are required to be formatted in XML:
<document reference="..."> <!-- 'reference' refers to the analysed suspicious document -->
<feature name="detected-plagiarism" <!-- plagiarism which was detected in an external analysis -->
this_offset="5" <!-- the char offset within the suspicious document -->
this_length="1000" <!-- the number of chars beginning at the offset -->
source_reference="..." <!-- reference to the source document -->
source_offset="100" <!-- the char offset within the source document -->
source_length="1000" <!-- the number of chars beginning at the offset -->
/>
... <!-- more external analysis results in this suspicious document -->
<feature name="detected-plagiarism" <!-- plagiarism which was detected in an intrinsic analysis -->
this_offset="5" <!-- just like above but excluding the "source"-attributes -->
this_length="1000"
/>
... <!-- more intrinsic analysis results in this suspicious document -->
</document>
The result document must be valid with respect to the XML schema found here.
In order to upload your results, please follow this tutorial.
Participant Network
We have set up a mailing list to connect prospective participants. Feel free to join!
Competition Rules
- Agreement. Participation in the competition constitutes the participant's full and unconditional agreement and acceptance of these rules.
- Eligibility. The contest is open to any party planning to attend the PAN competition. A person can participate in only one group. Multiple submissions per group are allowed for each task. We will not provide feedback on the performance at the time of submission: only the last submission before the deadline will be evaluated and all other submissions will be discarded.
- Integrity. The exploitation of potential flaws in the competition corpus to gain advantages in the competition is prohibited.
- Winner Selection. There will be one winner of the "External Plagiarism Analysis" task, one winner of the "Intrinsic Plagiarism Analysis" task, and one winner of the whole competition. The winners will be determined according to the following method. All participants are ranked according to their overall performance on the competition corpus for each task which is measured as F-measure (harmonic mean of precision and recall) divided by granularity. Winner of a task is the participant who has the highest score on the respective part of the corpus. Winner of the competition is the participant who has the highest score on the whole competition corpus.
- Award. The winner of the whole competition will be awarded the prize money. We expect that one member of the winning group attends the forthcoming PAN workshop and presents his approach. The winner is also encouraged to submit a research paper about his approach to the workshop.
FAQ
- My software will not be able to detect cross-language plagiarism. Can I participate anyway?
Yes, definitely! The corpora contain only a small percentage of cross-language plagiarism. However, when selecting the winner we will not distinguish participants who claim to detect cross-language plagiarism from those who don't. - Is it mandatory to also submit a research paper to the workshop when participating in the competition?
No, but we strongly encourage you to do so since this is a great opportunity for you to present your approach. - Do I need to submit my paper in Spanish?
No, unlike the SEPLN conference the PAN workshop will be held in English only. - How often can I submit detection results?
As often as you like, however, only the last submission counts for the competition. - Is it possible to register only for the PAN workshop and not for the SEPLN conference?
Yes. - Can vendors of commercial plagiarism detection software participate?
Yes.
Competition Organization
Martin Potthast, and Andreas Eiselt (Bauhaus University Weimar), and
Alberto Barrón-Cedeño (Universidad Politécnica de Valencia)
5.other tools
Duplichecker ... Free plagiarism checker http://www.duplichecker.com Duplichecker ... Free plagiarism checker Check plagiarism for free on several search engines. Check with and without quotes making sure content is not indexed before. |
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Viper - easy, accurate, free - plagiarism checker http://www.scanmyessay.com This easy, accurate and free plagiarism checker will help you stay plagiarism-free! |
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Teacher and Student Plagiarism Checking http://www.assignmentproof.com Whether you want to check plagiarism against a submitted set of documents, cached or live internet resources, publications, books, articles, magazines or billions of student papers submitted in universities and colleges world wide...we can offer a solution which is both budget friendly and guarantees results with a full money back warranty. Free trial |
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Chimpsky http://chimpsky.uwaterloo.ca Chimpsky detects plagiarism in text documents. It finds duplicated content within a set of uploaded documents, and it facilitates Google searches for web-derived content. |
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Plagiarism Checking http://www.checkforplagiarism.net/ http://www.checkforplagiarism.net Choosing An Online Plagiarism Detector To Check For Plagiarism With so many online plagiarism detectors, choosing one may seem like an overwhelming task, but it can be easy if you know what you're looking for. |
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Plagiarism Detection : List at PlagiarismAdvice (UK) http://www.plagiarismadvice.org/plagiarismdetection.php Plagiarism Detection : List at PlagiarismAdvice (UK) |
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ImageStamper (really a citation tool) http://s1.imagestamper.com/ ImageStamper is a free tool for keeping dated, independently verified copies of license conditions associated with creative commons images. You can use it to safeguard your use of free images from license changes, or to prove you are the original image creator. Simply paste the URL of the page that contains the image you intend to use. ImageStamper will produce a timestamp of the image's license and will store this timestamp permanently in your account. The timestamp proves you obtained the image under that license and you can show it to others using a unique permalink. |
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Plagium http://www.plagium.com Plagium is a fast, and easy-to-use means to check text against possible plagiarism or possible sources of origination. User can simply enter text that he would like to analyze into the text box and let Plagium do the rest of the work or he can also check the contents of an entered URL for its sources. |
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Plagiarism Detection Tool : iScan http://www.plagiarism.uk.com Plagiarism detection tool iScan makes checking for problem easy. Scan your essay against Wikipedia, e-zines, article databases, Google books and other popular sources of plagiarism. |
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The Plagiarism Checker http://www.dustball.com/cs/plagiarism.checker/ This educational software was designed as a project for the University of Maryland at College Park Department of Education. It looks like it is basically doing a Google search. |
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Plagiarism Detector http://www.plagiarism-detector.com Plagiarism Detector - is a personal software tool to effectively discover, trace and in this way prevent unauthorized copy-pasting of any textual material taken from the world wide web. It uses the Google database to send hundreds of requests per second to verify the text originality. Free demo version is avaliable for download! |
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Copyscape http://www.copyscape.com/ Defending your rights online, Copyscape is the leading provider of services that protect your content against online plagiarism and theft. The free Copyscape service makes it easy to find copies of your content on the Web. Simply type in the address of your web page, and Copyscape does the rest. Copyscape finds sites that have copied your content without permission, as well as those that have quoted you. Copyscape Premium provides more powerful searching than the free service with no monthly limit. You may also search for copies of your offline content by copying and pasting the text. |
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Free online plagiarism detection tool http://www.plagiarismdetect.com Free online plagiarism detection tool. Upload text file future. Live ajaxified search. |
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DOC Cop http://www.doccop.com/ DOC Cop is a plagiarism detection tool that creates reports displaying the correlation and matches between documents or a document and the web. DOC Cop does not take ownership or copyright of your material. It does not retain your material beyond the time it takes to generate your report. DOC Cop is lightning fast, capable of processing one million words or a thousand thousand-word documents within 20 minutes. DOC Cop gathers the evidence, and provides the information required for you to judge whether or not plagiarism has occurred. |
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Free Plagiarism Detection Tool http://www.englishessays.org.uk/free-plagiarism-scanner-scan.php Our free plagiarism scanner will scan your essays or other documents against online sources, as well as any text documents on your local computer or server. The plagiarised fragments will be outlined and highlighted by the scanning software so you can easily edit your work and make it plagiarism free! You will need to register to use the software. |
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My Drop Box http://www.mydropbox.com MyDropbox Suite integrates a renowned plagiarism prevention technology with a versatile digital learning environment that enables instructors to manage online assignments, organize electronic submissions and mark papers on the Web. |
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Plagiarism and Copyright: Videos and PowerPoints http://plagiarismvideos.blogspot.com/ The link above goes to one of the Shambles "Forest of Theme Blogs" pages that provides videos and other multimedia resources to support the topic here. If you would like to see all of the Theme Blogs then go to the full list athttp://www.shambles.net/blogforest or click where you see this button |
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Article Checker http://www.articlechecker.com Article Checker is a new tool that searches Google, Yahoo and MSN for your content. Or, you can use the shortcut of articlechecker.com/URL |
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Project Analyzer (for Visual Basic) http://www.aivosto.com/project/project.html Program source code analyzer that finds duplicated code blocks. Can be used to detect plagiarism in software written in Visual Basic, VB.NET and VBA. |
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CodeMatch (for computer software) http://www.ZeidmanConsulting.com/CodeSuite.htm CodeMatch (for computer software) CodeMatch has become the standard tool in software copyright cases. It compares thousands of source code files in multiple directories and subdirectories to determine which files are the most highly correlated. This can be used to significantly speed up the work of finding source code plagiarism, because it can direct the examiner to look closely at a small amount of code in a handful of files rather than thousands of combinations. CodeMatch is also useful for finding open source code within proprietary code, determining common authorship of two different programs, and discovering common, standard algorithms within different programs. |
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EssayFraud http://www.essayfraud.org/ EssayFraud.org is a watchdog organization that investigates hypocrisy involving plagiarism in academia. We also dissuade plagiarism by enabling consumers and freelance writers to publish complaints about term paper mills. List of Fraudulent Companies that Consumers should Avoid 350 Scam Sites - Warning Signs - Complaint Forum - Plagiarism - Verification Criterion |
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Numly http://numly.com/numly/default.asp Numly assigns Numly Numbers (Electronic Serial Numbers / ESNs) for all things digital. These unique identifiers provide digital rights management capabilities as well as third-party, non-repudiation measures for proof of copyright via real-time verifications. Numly Numbers are simple to generate and act as an electronic timestamp. They also allow you to track who is viewing your content and when it is accessed, monitor ratings, and can be used as permalinks! |
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Issues Raised by the Use of Turnitin http://cyberdash.com/plagiarism-detection-software-issues-gvsu Issues Raised by Use of Turnitin Plagiarism Detection Software |
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Moss : A System for Detecting Software Plagiarism http://www.cs.berkeley.edu/~aiken/moss.html Moss : A System for Detecting Software Plagiarism To date, the main application of Moss has been in detecting plagiarism in programming classes. Since its development in 1994, Moss has been very effective in this role. The algorithm behind moss is a significant improvement over other cheating detection algorithms (at least, over those known to us). |
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Pl@giarism : a plagiarism detection tool http://www.plagiarism.tk/ Pl@giarism : a plagiarism detection tool At the Law Faculty of the University of Maastricht we used this plagiarism detection tool for screening student-documents on the same subject. Success is guaranteed. First because the students knowing that we used this tool became careful in copying each others work. And secondly because the program detects even the smallest form of plagiarism (such as the most common paraphrases of some lines out off a textbook all students used). The program makes a table where documents are sorted on their resemblance percentage (figure 1) and by clicking in the table the clicked document-pair will be shown in two RTF-boxes with the matches colored in blue (figure 2). The Plagiarism detection program is available for downloading .. free. |
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Plagiarism Checker http://www.plagiarismchecker.com/ Plagiarism Checker Check for Plagiarism On the Web for Free Plagiarism Checker can help you find out whether a student's paper has been copied from the Internet. |
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iThenticate http://www.ithenticate.com/static/home.html iThenticate is a system that combats the piracy of intellectual property and ensures the originality of written work for publishers, news agencies, corporations, law firms, and non-profit entities. Unlike some other plagiarism detection systems, iThenticate requires no installation or maintenance of additional software. Because iThenticate is completely web-based, compatibility between different computers and operating systems is never a problem. |
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Firefox (Web browser) : Plagiarism Plugin http://www.1hs.org/blog/?p=23 Firefox (Web browser) : Plagiarism Plugin |
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Google as a Plagiarism Tool http://www.google.com Google as a Plagiarism Tool ... sometimes just copying and pasting some text from a students work into Google (or other search engine) and doing a search can identify plagiarism. Probably not the best individual tool ... but it is free. |
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Software for Detecting Plagiarism (Free) http://www.plagiarism.phys.virginia.edu/ Software for Detecting Plagiarism (Free) The goal of this web site is to help reduce the impact of plagiarism on education and educational institutions. At present, it distributes free software to detect plagiarism and provides links to other resources. This site's sole author is Lou Bloomfield, Professor of Physics, University of Virginia, |
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LexisNexis CopyGuard http://www.lexisnexis.com/copyguard/ LexisNexis CopyGuard LexisNexis has teamed with iParadigms, LLC to create LexisNexis CopyGuard, a revolutionary new plagiarism deterrent solution. LexisNexis CopyGuard uses pattern-matching technology to identify suspect passages in submitted documents. An easy-to-read report underlines and color codes questionable sentences, with links to the original sources. Ultimately you spend less time verifying content and improve your organization? productivity. LexisNexis CopyGuard searches against more than five billion relevant, searchable documents available through the LexisNexis news services and the archived Web pages indexed by IParadigms, LLC so that you can be confident that you are getting the most accurate results possible. |
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Glatt Plagiarism Self-Detection Program (GPSD) http://www.plagiarism.com/self.detect.htm Glatt Plagiarism Self-Detection Program (GPSD) A Screening Program to help detect inadvertent instances of plagiarism. This Test is designed to help you become more sensitive to your own writing style. It is also hoped that you will gain some insight into how to detect and avoid plagiarism. The Glatt Plagiarism Self-Detection Test provides a ROUGH estimate that plagiarism has or has not occurred. Based on the percentage of correct answers, the test results are intended to be used to help you become aware of text which you may have inadvertently plagiarized. |
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Glatt Plagiarism Screening Program (GPSP) http://www.plagiarism.com/screening.htm Glatt Plagiarism Screening Program (GPSP) The Glatt Plagiarism Screening Program is the first comprehensive computer software program specifically designed for detecting plagiarism. Objective. Reliable. Valid. Educators will appreciate being able to focus on teaching and not worry about dishonest writing. |
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Turnitin : Anti-Plagiarism Service http://www.turnitin.com/ Turnitin : Anti-Plagiarism Service Papers are sent to the Turnitin web site and then comapred to files/text on the internet and in their own database. Turnitin instantly identifies papers containing unoriginal material and acts as a powerful deterrent to stop student plagiarism before it starts. |
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My DropBox : Anti-Plagiarism Service http://www.mydropbox.com/ My DropBox : Anti-Plagiarism Software MyDropbox Suite integrates a renowned plagiarism prevention technology with a versatile digital learning environment that enables instructors to manage online assignments, organize electronic submissions and mark papers on the Web. MyDropBox is a family of innovative and easy-to-use online tools created to enhance collaborative learning at your institution. Designed for rapid implementation, our products include a world? leading plagiarism prevention system, one-of-its-kind online grading solution and other innovative online tools. Papers are also sent to 'My Dropbox's' site which prepares reports. |
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Scriptum : Anti-Plagiarism Service http://www.scriptum.ca/ Scriptum : Anti-Plagiarism Service You can use Scriptum's Plagiarism Detector to deter students from cheating on assignments, which raises the quality of work for your course. Instructors can see at a glance assignments that are original and ones that contain content copied from the Internet. By storing assignments on the Internet and moving away from paper, you can mark assignments wherever you are - no more delays because the papers are in the office and you're at home. Every time a student uploads an assignment, Scriptum's plagiarism detector compares it against content found on the Internet. Scriptum's plagiarism detector looks at word-for-word content as well as content that has been changed slightly (such as changing verbs and using synonyms). |
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EVE : Anti-Plagiarism Software http://www.canexus.com/eve/ EVE : Anti-Plagiarism Software EVE Plagiarism Detection System EVE2 is a very powerful tool that allows professors and teachers at all levels of the education system to determine if students have plagiarized material from the World Wide Web. EVE2 accepts essays in plain text, Microsoft Word, or Corel Word Perfect format and returns links to web pages from which a student may have plagiarized. EVE2 has been developed to be powerful enough to find plagiarized material while not overwhelming the professor with false links. Once the search has completed, the teacher is given a full report on each paper that contained plagiarism, including the percent of the essay plagiarized, and an annotated copy of the paper showing all plagiarism highlighted in red. Licence about US$30 |
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WCopyfind 2.5 : Anti-Plagiarism Software http://www.plagiarism.phys.virginia.edu/Wsoftware.html WCopyfind 2.5 : Anti-Plagiarism Software This program examines a collection of document files. It extracts the text portions of those documents and looks through them for matching words in phrases of a specified minimum length. When it finds two files that share enough words in those phrases, WCopyfind generates html report files. These reports contain the document text with the matching phrases underlined. It cannot search the web or internet to find matching documents for you. Free to download |
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Anti-Plagiarism Tools http://wwwlb.aub.edu.lb/~eplagio/Anti_plag.htm Anti-Plagiarism Tools The best free tools for plagiarism detection are Internet search engines. Most of them allow searching exact phrases or even whole sentences (through 'advanced search'). Thus, if you suspect a paper has plagiarized text, choose some unusual phrases in the text and copy them in a search engine. The engine will bring to you all Internet documents in which the phrase appears AND which were indexed in its huge database. |
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Copyscape http://www.copyscape.com Copyscape : Search for copies of a specific page on your site by entering its URL. |
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