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About the PAN Workshop:
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The workshop shall bring together experts and researchers around the exciting
and future-oriented topics of plagiarism detection, authorship identification,
and the detection of social software misuse. The development of new solutions
for these problems can benefit from the combination of existing technologies,
and in this sense the workshop provides a platform that spans different views
and approaches. The following list gives examples from the outlined fields for
which contributions are welcome, but not restricted to:
Plagiarism detection:
* plagiarism detection in general, in Web communities and social
networks, and
cross-language plagiarism
* identifying near-duplicate and versioned documents of all kinds: text,
software, image, music, video
* technology for high-similarity retrieval such as fingerprinting and
similarity hashing
Authorship identification:
* models for authorship identification, authorship attribution, and
writing style
* NLP- and knowledge-based retrieval models to capture personal traits
and sentiment
* Web forensics, community fraud, and new Web infringements
Social Software Misuse Detection:
* uncovering serial sharing and lobbying
* monitoring vandalism, trolling, or stalking
* trust, psychological and personality-based user studies, social aspects
of Web misuse
Plagiarism analysis is a collective term for computer-based methods to identify
a plagiarism offense. In connection with text documents we distinguish between
corpus-based and intrinsic analysis: the former compares suspicious documents
against a set of potential original documents, the latter identifies
potentially plagiarized passages by analyzing the suspicious document with
respect to changes in writing style.
Authorship identification divides into so-called attribution and verification
problems. In the authorship attribution problem, one is given examples of the
writing of a number of authors and is asked to determine which of them authored
given anonymous texts. In the authorship verification problem, one is given
examples of the writing of a single author and is asked to determine if given
texts were or were not written by this author. As a categorization problem,
verification is significantly more difficult than attribution. Authorship
verification and intrinsic plagiarism analysis represent two sides of the same
coin.
"Social Software Misuse" can nowadays be noticed on many social
software based
platforms. These platforms like Blogs, sharing sites for photos and videos,
wikis and online forums are contributing up to one third of new Web content.
"Social Software Misuse" is a collective term for anti-social
behavior in online communities; an example is the distribution of spam via the
e-mail infrastructure. Interestingly, spam is one of the few misuses for which
detection technology is developed at all, though various forms of misuse exist
that threaten the different online communities. Our workshop shall close this
gap and invites contributions concerned with all kinds of social software
misuse.
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About the Competition on Plagiarism Detection:
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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.
The competition divides into two tracks:
* External Plagiarism Analysis. Given a set of suspicious documents and a
set of potential source documents the task is to find all passages within the
suspiscious documents which have been plagairized from one or more of the
source documents.
* Intrinsic Plagiarism Analysis. Given a set of suspicious documents the
task is to detect paragraphs in the documents which have not been written by
its main author. No source documents are given in this task.
A large corpus of artificial plagiarism containing cases which have been
obfuscated and/or translated will be released for the competition.
A development corpus, to be used in developing a detection software, will be
released two months before the competition starts, a competition corpus will be
used to evaluate and compare detection softwares. The former will contain fully
annotated plagiarism cases, the latter will not.
The succes of a plagiarism detection software will be measured in terms of its
precision, recall, and granularity.
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Important Dates:
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open
Notification of interest for participation
21.03.2009 Release of the
development corpus
21.05.2009 Release of the
competition corpus
07.06.2009 Submission deadline
for the competition
15.06.2009 Notification of
competition results
01.07.2009 Submission deadline
for the papers
15.07.2009 Notification of
reviews
01.08.2009 Submission deadline
for final version of the papers
10.09.2009 (afternoon) PAN Workshop
Benno Stein Bauhaus University
Weimar, Germany
Paolo Rosso Universidad Politécnica
de Valencia, Spain
Efstathios Stamatatos University of the Aegean, Greece
Moshe Koppel Bar-Ilan University,
Israel
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