This is the 18th evaluation lab on digital text forensics. PAN will be held as part of the CLEF conference in Avignon, France, on September 10-14, 2018. Evaluations will commence from January till June. We invite you to take part in any of the three tasks shown below.
Given a document, who wrote it?
One subtask focuses on cross-domain authorship attribution applied in fanfiction and another subtask focuses on style change detection.
Given a document, what're its author's traits?
This task focuses on gender, whereas text and image may be used as information sources of tweets in English, Spanish and Arabic.
Given a document, hide its author.
This task works against identification and profiling by automatically paraphrasing a text to obfuscate its author's style. The tasks offered are author masking and obfuscation evaluation.
University of Santiago de Compostela (Spain)
In this talk I will review some recent results regarding early detection of signs of depression and anorexia. Since 2017, we have been organizing eRisk, a CLEF lab that promotes the development of effective and efficient solutions for early risk prediction on the Internet. eRisk explores the evaluation methodology, effectiveness metrics and practical applications (particularly those related to health and safety) of early risk detection on the Internet. Early detection technologies can be employed in different areas, particularly those related to health and safety. For instance, early alerts could be sent when a predator starts interacting with a child for sexual purposes, or when a potential offender starts publishing antisocial threats on a blog, forum or social network. Our main goal is to pioneer a new interdisciplinary research area that would be potentially applicable to a wide variety of situations and to many different personal profiles. Examples include potential paedophiles, stalkers, individuals that could fall into the hands of criminal organisations, people with suicidal inclinations, or people susceptible to depression. In this talk, I will discuss the lessons learned over these two years and some future lines of work.
Dr. David E. Losada is an Associate Professor in Computer Science & Artificial Intelligence at the University of Santiago de Compostela (Spain). He is currently the Director of the Master's Programme on Big Data Analytics. David E. Losada received his BS in Computer Science (with honors) in 1997, and his PhD in Computer Science (with honors) in 2001, both from the University of A Coruña (Spain). From 2001 to 2002, he was a lecturer in the San Pablo-CEU University (Spain) and, in 2003, he joined the Univ. of Santiago de Compostela as a senior research fellow ("Ramón y Cajal" R&D programme). His current research interests include a wide range of Information Retrieval (IR) and related areas such as: early risk detection, text mining, IR evaluation, IR probabilistic models, summarization, novelty detection, and sentence retrieval. Losada is an active member of the IR community and he regularly serves in the Programme Committee of prestigious international conferences such as SIGIR or ECIR. He has also led several R&D projects and contracts in the area of search technologies. In 2011, Losada was recognized with an ACM senior member award. David started the organization of eRisk in 2017. eRisk is a CLEF lab that promotes the development of effective and efficient solutions for early risk prediction on the Internet.