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<pre>
Preface

This is the 11th edition of the Forum for Information Retrieval Evaluation (FIRE 2019).
Continuing the tradition of the last 10 years, the evaluation tracks at FIRE have expanded to
encompass new domains and new languages. With five evaluation tracks and participation
from over 60 teams, this is one of the biggest FIRE workshops to date.

In tune with the global trend, this year a special focus was on social media analysis, with
four out of the five tracks focusing specifically on issues and challenges related to social
media. Hate Speech and Offensive Content Identification in Indo-European Languages
(HASOC), focused on identifying various categories of hate speech from social media posts.
HASOC saw the maximum participation for a single track in the history of FIRE, with 25
teams submitting working notes. The track also introduces the German language in FIRE
evaluation tracks.

This year’s edition saw the return of the Arabic language, after first being introduced in
FIRE 2015. ’Author Profiling & Deception detection in Arabic (APDA)’ and ‘Irony
detection in Arabic Tweets (IDAT)’ both focused on specific challenges of detecting false
positives in a system for detecting cyber-threats. Artificial Intelligence for Legal Assistance
(AILA) is a continuation of previous tracks on Legal Information Retrieval and aims to build
a system for identifying relevant cases and laws related to a legal scenario. Finally,
Classification of Insincere Questions (CIQ) focused on identifying and categorizing of
insincere questions on community question answering platforms. More details about the
evaluation tracks and participating teams are available in the respective overview papers.

We express our gratitude to all the track organizers for their efforts in organizing these
tracks, as well as to the participants for their enthusiastic participation. A special thanks to
our sponsors ‘ACM SIGIR Special Interest Group on Information Retrieval’ and ‘Microsoft
India’, for their continued support.




                                                                                   Parth Mehta
                                                                                   Paolo Rosso
                                                                            Prasenjit Majumder
                                                                                 Mandar Mitra
                      List of Reviewers

Artificial Intelligence for Legal Assistance

Parth Mehta, DA-IICT Gandhinagar, India
Saptarshi Ghosh, IIT Kharagpur, India
Kripabandhu Ghosh, TCS Innovations Lab Pune, India
Paheli Bhattacharya, IIT Kharagpur, India


Author profiling and deception detection in Arabic

Francisco Rangel, Universitat Politècnica de València, Spain
Paolo Rosso, Universitat Politècnica de València, Spain
Bilal Ghanem, Universitat Politècnica de València, Spain
Javier Sánchez-Junquera, Universitat Politècnica de València, Spain


Hate Speech and Offensive Content Identification in Indo-European Languages

Christa Womser Hacker- University of Hildesheim, Germany
Thomas Mandl - University of Hildesheim, Germany
Sukomal Pal - Indian Institute of Technology Varanasi, India
Kripabandhu Ghosh - TCS Innovations Lab Pune, India
Marcos Zampieri - Rochester Institute of Technology, USA
Lea Wöbbekind - University of Hildesheim, Germany
Linda Achilles - University of Hildesheim, Germany
Sandip Modha - DAIICT & LDRP, India
Ritesh Kumar - Bhimrao Ambedkar University, India
Anand Kumar M - NITK Surathkal, India
Surupendu Gangopadhyay – DAIICT Gandhinagar, India


Classification of Insincere Questions

Manjira Sinha, IIT Kharagpur, India
Monnie Parida, IIT Kharagpur, India


Irony Detection in Arabic Tweets

Farah Benamara, IRIT-CNRS, Université de Toulouse, France
Véronique Moriceau, IRIT-CNRS, Université de Toulouse, France

</pre>