[PPT] - Uncovering Plagiarism, Authorship, and Social Software Misuse PAN PowerPoint Presentation

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Uncovering Plagiarism, Authorship, and Social Software Misuse PAN 2011

[pan.webis.de]

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The PAN Team

Teresa Holfeld Andreas Eiselt Martin Potthast Alberto Barrón-Cedeño Efstathios Stamatatos Moshe Koppel Patrick Juola Shlomo Argamon Paolo Rosso Benno Stein

Bauhaus-Universität Weimar Martin Potthast, Benno Stein, Andreas Eiselt, Teresa Holfeld Universidad Politécnica de Valencia Alberto Barrón-Cedeño, Paolo Rosso University of the Aegean Efstathios Stamatatos Bar-Ilan University Moshe Koppel Illinois Institute of Technology Shlomo Argamon Duquesne University Patrick Juola

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PAN Overview

PAN Plagiarism Detection Authorship Identification Vandalism Detection External Detection Intrinsic Detection Authorship Verification Authorship Attribution

↔

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PAN Overview

Mission & Tasks

❑ Plagiarism Detection

– text plagiarism within and across languages, multimedia plagiarism – text reuse, paraphrasing, information flow, meme tracking – near-duplicates, high-similarity search, fingerprinting, hash-based search

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PAN Overview

Mission & Tasks

❑ Plagiarism Detection

– text plagiarism within and across languages, multimedia plagiarism – text reuse, paraphrasing, information flow, meme tracking – near-duplicates, high-similarity search, fingerprinting, hash-based search

❑ Authorship Identification

– models for authorship verification, authorship attribution, and writing style – models to capture personal traits and sentiment – text forensics, ghostwriting, intrinsic plagiarism detection

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PAN Overview

Mission & Tasks

❑ Plagiarism Detection

– text plagiarism within and across languages, multimedia plagiarism – text reuse, paraphrasing, information flow, meme tracking – near-duplicates, high-similarity search, fingerprinting, hash-based search

❑ Authorship Identification

– models for authorship verification, authorship attribution, and writing style – models to capture personal traits and sentiment – text forensics, ghostwriting, intrinsic plagiarism detection

❑ Social Software Misuse

– serial sharing, lobbyism, spam – trolling, stalking, Wikipedia vandalism – social trust, anonymity and de-anonymization

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PAN Overview

Mission & Tasks

❑ Plagiarism Detection

– text plagiarism within and across languages, multimedia plagiarism – text reuse, paraphrasing, information flow, meme tracking – near-duplicates, high-similarity search, fingerprinting, hash-based search

❑ Authorship Identification

– models for authorship verification, authorship attribution, and writing style – models to capture personal traits and sentiment – text forensics, ghostwriting, intrinsic plagiarism detection

❑ Social Software Misuse

– serial sharing, lobbyism, spam – trolling, stalking, Wikipedia vandalism – social trust, anonymity and de-anonymization

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Plagiarism Detection

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Plagiarism Detection

Plagiarism is the practice of claiming, or implying, original authorship

f someone else’s written or creative work, in whole or in part, into
ne’s own without adequate acknowledgment.

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Plagiarism Detection

Plagiarism is the practice of claiming, or implying, original authorship

f someone else’s written or creative work, in whole or in part, into
ne’s own without adequate acknowledgment.

[Wikipedia: Plagiarism, 2009]

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. . . better technology nowadays ;–)

+

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. . . better technology nowadays ;–)

+

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Authorship Identification

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Authorship Identification

Sub-task: Authorship Attribution Given a text of uncertain authorship and texts from a set of candidate authors, the task is to map the uncertain text onto the true author among the candidates.

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Authorship Identification

Sub-task: Authorship Attribution Given a text of uncertain authorship and texts from a set of candidate authors, the task is to map the uncertain text onto the true author among the candidates.

A

1

A2 A

3

A4 A5 A6 A7 A8 A

9

A10 A

11

A12 A? ... ...

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Authorship Identification

Sub-task: Authorship Verification Given a text of uncertain authorship and text from a specific author, the task is to determine whether the given text has been written by that author.

A? A

3

≠ =

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Authorship Identification

Sub-task: Authorship Verification Given a text of uncertain authorship and text from a specific author, the task is to determine whether the given text has been written by that author.

A? A

3

≠ =

The problem can be considered as a one-class classification problem.

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Vandalism Detection

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Vandalism Detection in Amsterdam

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Vandalism Detection in Amsterdam

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