CLEF 2019
CLEF 2019 Working Notes

Table of Contents

• Preface
  Linda Cappellato, Nicola Ferro, David E. Losada, Henning Müller

CENTRE@CLEF - CLEF/NTCIR/TREC Reproducibility

• CENTRE@CLEF2019: Overview of the Replicability and Reproducibility Tasks
  Nicola Ferro, Norbert Fuhr, Maria Maistro, Tetsuya Sakai, Ian Soboroff
• Replicability and Reproducibility of Automatic Routing Runs
  Timo Breuer, Philipp Schaer

CheckThat! - Automatic Identification and Verification of Claims

• Overview of the CLEF-2019 CheckThat! Lab: Automatic Identification and Verification of Claims. Task 1: Check-Worthiness
  Pepa Atanasova, Preslav Nakov, Georgi Karadzhov, Mitra Mohtarami, Giovanni Da San Martino
• Overview of the CLEF-2019 CheckThat! Lab: Automatic Identification and Verification of Claims. Task 2: Evidence and Factuality
  Maram Hasanain, Reem Suwaileh, Tamer Elsayed, Alberto Barrón-Cedeño, Preslav Nakov
• TOBB-ETU at CLEF 2019: Prioritizing Claims Based on Check-Worthiness
  Bahadir Altun, Mucahid Kutlu
• CheckThat! 2019 UAICS
  Lucia Georgiana Coca, Ciprian-Gabriel Cusmuliuc, Adrian Iftene
• A Hybrid Model to Rank Sentences for Check-worthiness
  Rudra Dhar, Subhabrata Dutta, Dipankar Das
• TheEarthIsFlat’s Submission to CLEF’19CheckThat! Challenge
  Luca Favano, Mark J. Carman, Pier Luca Lanzi
• UPV-UMA at CheckThat! Lab: Verifying Arabic Claims using a Cross Lingual Approach
  Bilal Ghanem, Goran Glavaš, Anastasia Giachanou, Simone Paolo Ponzetto, Paolo Rosso, Francisco Rangel
• The IPIPAN Team Participation in the Check-Worthiness Task of the CLEF2019 CheckThat! Lab
  Jakub Gąsior, Piotr Przybyła
• Neural Weakly Supervised Fact Check-Worthiness Detection with Contrastive Sampling-Based Ranking Loss
  Casper Hansen, Christian Hansen, Jakob Grue Simonsen, Christina Lioma
• bigIR at CLEF 2019: Automatic Verification of Arabic Claims over the Web
  Fatima Haouari, Zien Sheikh Ali, Tamer Elsayed
• Check That! Automatic Identification and Verification of Claims: IIT(ISM) @CLEF'19 Check Worthiness
  Ritesh Kumar, Shivansh Prakash, Shashank Kumar, Rajendra Pamula
• Using External Knowledge Bases and Coreference Resolution for Detecting Check-Worthy Statements
  Salar Mohtaj, Tilo Himmelsbach, Vinicius Woloszyn, Sebastian Möller
• Entity Detection for Check-worthiness Prediction: Glasgow Terrier at CLEF CheckThat! 2019
  Ting Su, Craig Macdonald, Iadh Ounis
• Automatic Verification of Political Claims Based on Morphological Features
  Ibtissam Touahri, Azzeddine Mazroui,

CLEF eHealth

• CLEF 2019 Technology Assisted Reviews in Empirical Medicine Overview
  Evangelos Kanoulas, Dan Li, Leif Azzopardi, Rene Spijker
• Overview of the CLEF eHealth 2019 Multilingual Information Extraction
  Mariana Neves, Daniel Butzke, Antje Dörendahl, Nora Leich, Benedikt Hummel, Gilbert Schönfelder, Barbara Grune
• DEMIR at CLEF eHealth 2019: Information Retrieval based Classification of Animal Experiments Summaries
  Nizar Ahmed, Alirıza Arıbaş, Adil Alpkocak
• Ranking Studies for Systematic Reviews Using Query Adaptation: University of Sheffield’s Approach to CLEF eHealth 2019 Task 2
  Amal Alharbi, Mark Stevenson
• MLT-DFKI at CLEF eHealth 2019: Multi-label Classification of ICD-10 Codes with BERT
  Saadullah Amin, Guenter Neumann, Katherine Dunfield, Anna Vechkaeva, Kathryn Annette Chapman, Morgan Kelly Wixted
• Classification of Animal Experiments: A Reproducible Study. IMS Unipd at CLEF eHealth Task 1
  Giorgio Maria Di Nunzio
• A Distributed Effort Approach for Systematic Reviews. IMS Unipd At CLEF 2019 eHealth Task 2
  Giorgio Maria Di Nunzio
• Deep Learning Approach for Semantic Indexing of Animal Experiments Summaries in German Language
  Kayalvizhi S, Thenmozhi D, Aravindan Chandrabose
• Automatic Thresholding by Sampling Documents and Estimating Recall
  Dan Li, Evangelos Kanoulas
• Classifying German Animal Experiment Summaries with Multi-lingual BERT at CLEF eHealth 2019 Task 1
  Mario Sänger, Leon Weber, Madeleine Kittner, Ulf Leser

eRisk - Early Risk Prediction on the Internet

• Overview of eRisk at CLEF 2019: Early Risk Prediction on the Internet (extended overview)
  David E. Losada, Fabio Crestani, Javier Parapar
• Transfer Learning for Depression: Early Detection and Severity Prediction from Social Media Postings
  Pegah Abed-Esfahani, Derek Howard, Marta Maslej, Sejal Patel, Vamika Mann, Sarah Goegan, Leon French
• INAOE-CIMAT at eRisk 2019: Detecting Signs of Anorexia using Fine-Grained Emotions
  Mario Ezra Aragon, Adrian Pastor Lopez-Monroy, Manuel Montes-Y-Gomez
• UNSL at eRisk 2019: a Unified Approach for Anorexia, Self-harm and Depression Detection in Social Media
  Sergio G. Burdisso, Marcelo Errecalde, Manuel Montes-Y-Gómez
• Uppsala University and Gavagai at CLEF eRISK: Comparing Word Embedding Models
  Elena Fano, Jussi Karlgren, Joakim Nivre
• UDE at eRisk 2019: Early Risk Prediction on the Internet
  Razan Masood, Faneva Ramiandrisoa, Ahmet Aker
• Quick and (maybe not so) Easy Detection of Anorexia in Social Media Posts
  Elham Mohammadi, Hessam Amini, Leila Kosseim
• A Baseline Approach for Early Detection of Signs of Anorexia and Self-harm in Reddit Posts
  Nona Naderi, Julien Gobeill, Douglas Teodoro, Emilie Pasche, Patrick Ruch
• LTL-INAOE's Participation at eRisk 2019: Detecting Anorexia in Social Media through Shared Personal Information
  Rosa María Ortega-Mendoza, Delia Irazu Hernandez Farias, Manuel Montes-Y-Gómez
• Integrating UMLS for Early Detection of Sings of Anorexia
  Flor Miriam Plaza del Arco, Pilar López Úbeda, Manuel Carlos Díaz Galiano, Luis Alfonso Ureňa López, María Teresa Martín Valdivia
• Attentive Multi-stage Learning for Early Risk Detection of Signs of Anorexia and Self-harm on Social Media
  Waleed Ragheb, Jérôme Azé, Sandra Bringay, Maximilien Servajean
• Early Detection of Anorexia using RNN-LSTM and SVM Classifiers
  Akshaya Ranganathan, Haritha A, Thenmozhi D, Chandrabose Aravindan
• Early Risk Prediction by means of DeepLearning
  Pablo Ráez García Retamero, Isabel Segura Bedmar
• A Data-Driven Approach for Measuring the Severity of the Signs of Depression using Reddit Posts
  Paul van Rijen, Douglas Teodoro, Nona Naderi, Luc Mottin, Julien Knafou, Matt Jeffryes, Patrick Ruch
• BioInfo@UAVR at eRisk 2019: delving into Social Media Texts for the Early Detection of Mental and Food Disorders
  Alina Trifan, José Luis Oliveira

LifeCLEF - Biodiversity Identification and Prediction

• Overview of LifeCLEF Plant Identification Task 2019: diving into Data Deficient Tropical Countries
  Hervé Goëau Pierre Bonnet, Alexis Joly
• Overview of BirdCLEF 2019: Large-Scale Bird Recognition in Soundscapes
  Stefan Kahl, Fabian-Robert Stöter, Hervé Goëau, Hervé Glotin, Bob Planque, Willem-Pier Vellinga, Alexis Joly
• Overview of GeoLifeCLEF 2019: Plant Species Prediction using Environment and Animal Occurrences
  Christophe Botella, Maximilien Servajean, Pierre Bonnet, Alexis Joly
• Location-Based Species Recommendation - GeoLifeCLEF 2019 Challenge
  Costel-Sergiu Atodiresei, Adrian Iftene
• Inception-v3 Based Method of LifeCLEF 2019 Bird Recognition
  Jisheng Bai, Bolun Wang, Chen Chen, Jianfeng Chen, Zhonghua Fu
• Plant Identication on Amazonian and Guiana Shield Flora: NEUON submission to LifeCLEF 2019 Plant
  Sophia Chulif, Kiat Jing Heng, Teck Wei Chan, Mohammad Abdullah Al Monnaf, Yang Loong Chang
• Species Recommendation using Machine Learning - GeoLifeCLEF 2019
  Nanda H Krishna, Praveen Kumar R, Ram Kaushik R, Mirunalini P, Aravindan Chandrabose, Jaisakthi S M
• Bird Sound Classification Using Convolutional Neural Networks
  Chih-Yuan Koh, Jaw-Yuan Chang, Chiang-Lin Tai, Da-Yo Huang, Han-Hsing Hsieh, Yi-Wen Liu
• Bird Species Identification in Soundscapes
  Mario Lasseck
• Species Recommendation using Intensity Models and Sampling Bias Correction (GeoLifeCLEF 2019: Lof_of_Lof team)
  Pascal Monestiez, Christophe Botella
• Location-Based Plant Species Prediction Using A CNN Model Trained On Several Kingdoms - Best Method Of GeoLifeCLEF 2019 Challenge
  Mathilde Negri, Maximilien Servajean, Benjamin Deneu, Alexis Joly
• Non-local DenseNet for Plant CLEF 2019 Contest
  Dat Nguyen Thanh, Georges Quénot, Lorraine Goeuriot
• Recognition of the Amazonian flora by InceptionNetworks with Test-time Class Prior Estimation
  Lukáš Picek, Milan Šulc, Jiří Matas
• Plant Recommendation using Environment and Biotic Associations
  Sara Si-Moussi, Mickael Hedde, Wilfried Thuiller

ImageCLEF - Multimedia Retrieval in CLEF

• Overview of ImageCLEFtuberculosis 2019 - Automatic CT-based Report Generation and Tuberculosis Severity Assessment
  Yashin Dicente Cid, Vitali Liauchuk, Dzmitri Klimuk, Aleh Tarasau, Vassili Kovalev, Henning Müller
• Overview of ImageCLEFcoral 2019 Task
  Jon Chamberlain, Antonio Campello, Jessica P Wright, Louis G Clift, Adrian F Clark, Alba García Seco De Herrera
• Overview of ImageCLEFlifelog 2019: Solve My Life Puzzle and Lifelog Moment Retrieval
  Duc-Tien Dang-Nguyen, Luca Piras, Michael Riegler, Liting Zhou, Mathias Lux, Minh-Triet Tran, Tu-Khiem Le, Van-Tu Ninh, Cathal Gurrin
• Overview of the ImageCLEFmed 2019 Concept Detection Task
  Obioma Pelka, Christoph M. Friedrich, Alba G. Seco de Herrera, Henning Müller
• Overview of the ImageCLEFsecurity 2019: File Forgery Detection Tasks
  Konstantinos Karampidis, Nikos Vasilopoulos, Carlos Cuevas, Carlos Roberto Del-Blanco, Ergina Kavallieratou, Narciso García
• VQA-Med: Overview of the Medical Visual Question Answering Task at ImageCLEF 2019
  Asma Ben Abacha1, Sadid A. Hasan, Vivek V. Datla, Joey Liu, Dina Demner-Fushman, Henning Müller
• JUST at ImageCLEF 2019 Visual Question Answering in the Medical Domain
  Aisha Al-Sadi, Bashar Talafha, Mahmoud Al-Ayyoub, Yaser Jararweh, Fumie Costen
• An Encoder-Decoder Model for Visual Question Answering in the Medical Domain
  Imane Allaouzi, Mohamed Ben Ahmed, Badr Benamrou
• A Weighted Rule-Based Model for File Forgery Detection: UA.PT Bioinformatics at ImageCLEF 2019
  João Rafael Almeida, Pedro Freire, Olga Fajarda, José Luís Oliveira
• Medical Visual Question Answering at Image CLEF 2019- VQA Med
  Mohit Bansal, Tanmay Gadgil, Rishi Shah, Parag Verma
• Big Data For Lifelog Moments Retrieval Improvement
  Fatma Ben Abdallah, Ghada Feki, Anis Ben Ammar, Chokri Ben Amar
• Feature and Deep Learning Based Approaches for Automatic Report Generation and Severity Scoring of Lung Tuberculosis from CT Images
  Kirill Bogomasov, Daniel Braun, Andreas Burbach, Ludmila Himmelspach, Stefan Conrad
• A two-staged Approach for Localization and Classification of Coral Reef Structures and Compositions
  Kirill Bogomasov, Philipp Grawe, Stefan Conrad
• Tlemcen University at ImageCLEF 2019 Visual Question Answering Task
  Rabia Bounaama, Mohammed El Amine Abderrahim,
• Automatic Classification of Coral Images using Color and Textures
  Cristina M.R. Caridade, André R.S. Marcal
• BIDAL@imageCLEFlifelog2019: The Role of Content and Context of Daily Activities in Insights from Lifelogs
  Minh-Son Dao, Anh-Khoa Vo, Trong-Dat Phan, Koji Zettsu
• Lung Graph-Model Classification with SVM and CNN for Tuberculosis Severity Assessment and Automatic CT Report Generation
  Yashin Dicente Cid, Henning Müller
• Multimedia Lab @ ImageCLEF 2019 Lifelog Moment Retrieval Task
  Mihai Dogariu, Bogdan Ionescu
• ImageCLEF2019: Tuberculosis - Severity Scoring and CT Report with Neural Networks, Transfer Learning and Ensembling
  Amilcare Gentili
• ImageCLEF2019 Security - Forged File Discovery and Stego Image Discovery Tasks
  Amilcare Gentili, Paolo Gentili
• Informative and Intriguing Visual Features: UA.PT Bioinformatics in ImageCLEF Caption 2019
  Ana Jorge Gonçalves, Eduardo Pinho, Carlos Costa
• ImageSem at ImageCLEFmed Caption 2019 Task: a Two-stage Medical Concept Detection Strategy
  Zhen Guo, Xuwen Wang, Yu Zhang, Jiao Li
• ImageCLEF 2019: Deep Learning for Tuberculosis CT Image Analysis
  Abdelkader Hamadi, Noreddine Belhadj Cheikh, Yamina Zouatine, Si Mohamed Bekkai Menad, Mohamed Redha Djebbara
• Solving Life Puzzle with Visual Context-based Clustering and Habit Reference
  Trung-Hieu Hoang, Mai-Khiem Tran, Vinh-Tiep Nguyen, Minh-Triet Tran
• ImageCLEF 2019: CT Image Analysis for TB Severity Scoring and CT Report Generation using Autoencoded Image Features
  Siarhei Kazlouski
• Leveraging Medical Visual Question Answering with Supporting Facts
  Tomasz Kornuta, Deepta Rajan, Chaitanya Shivade, Alexis Asseman, Ahmet Ozcan
• AUEB NLP Group at ImageCLEFmed Caption 2019
  Vasiliki Kougia, John Pavlopoulos, Ion Androutsopoulos
• Lifelog Moment Retrieval with Advanced Semantic Extraction and Flexible Moment Visualization for Exploration
  Nguyen-Khang Le, Dieu-Hien Nguyen, Vinh-Tiep Nguyen, Minh-Triet Tran
• ImageCLEF 2019: Projection-based CT Image Analysis for TB Severity Scoring and CT Report Generation
  Vitali Liauchuk
• An Xception-GRU Model for Visual Question Answering in the Medical Domain
  Shengyan Liu, Xiaozhi Ou, Jiao Che, Xiaobing Zhou, Haiyan Ding
• Using improved Optical Flow Model to Detect Tuberculosis
  Fernando Llopis, Andrés Fuster-Guilló, Jorge Azorín-López, Irene Llopis
• Recurrent Attention Networks for Medical Concept Prediction
  Sam Maksoud, Arnold Wiliem, Brian Lovell
• Image Steganalysis with Very Deep Convolutional Neural Networks
  Naoya Mamada
• Multi-View CNN with MLP for Diagnosing Tuberculosis Patients Using CT Scans and Clinically Relevant Metadata
  Abdela Ahmed Mossa, Abdulkerim Mohammed Yibre, Ulus Çevik
• LIFER 2.0: Discovering Personal Lifelog Insights using an Interactive Lifelog Retrieval System
  Van-Tu Ninh, Tu-Khiem Le, Liting Zhou, Luca Piras, Michael Riegler, Mathias Lux, Minh-Triet Tran, Cathal Gurrin, Duc-Tien Dang-Nguyen
• Predicting Tuberculosis Related Lung Deformities from CT Scan Images Using 3D CNN
  Anup Pattnaik, Sarthak Kanodia, Rahul Chowdhury, Smita Mohanty
• UA.PT Bioinformatics at ImageCLEF 2019: Lifelog Moment Retrieval based on Image Annotation and Natural Language Processing
  Ricardo Ribeiro, António J. R. Neves, José Luis Oliveira
• ImageCLEF 2019: A 2D Convolutional Neural Network Approach for Severity Scoring of Lung Tuberculosis using CT Images
  Kavitha S, Nandhinee P R, Harshana S, Jahnavi Srividya S, Harrinei K
• Coral Reef Annotation and Localization using Faster R-CNN
  Jaisakth S M, Mirunalini Palaniappan, Aravindan Chandrabose
• Deep Multimodal Learning for Medical Visual Question Answering
  Lei Shi, Feifan Liu, Max P. Rosen
• Biomedical Concept Detection in Medical Images: MQ-CSIRO at 2019 ImageCLEFmed Caption Task
  Sonit Singh, Sarvnaz Karimi, Kevin Ho-Shon, Len Hamey
• Full Training versus Fine Tuning for Radiology Images Concept Detection Task for the ImageCLEF 2019 Challenge
  Priyanshu Sinha, Saptarshi Purkayastha, Judy Gichoya
• LSTM in VQA-Med, is It Really Needed? JCE Study on the ImageCLEF 2019 Dataset
  Avi Turner, Assaf Spanier
• Forged File Detection and Steganographic content Identification (FFDASCI) using Deep Learning Techniques
  M. Srinivas, Akshay Nayak, Abhishek Bhatt
• Deep Segmentation: using Deep Convolutional Networks for Coral Reef pixel-wise Parsing
  Aljoscha Steffens, Antonio Campello, James Ravenscroft, Adrian Clark, Hani Hagras
• ImageCLEFmed Tuberculosis 2019: Predicting CT Scans Severity Scores using Stage-Wise Boosting in Low-Resource Environments
  Augustus Tabarcea, Valentin Rosca, Adrian Iftene
• Automated Lifelog Moment Retrieval based on Image Segmentation and Similarity Scores
  Stefan Taubert, Stefan Kahl, Danny Kowerko, Maximilian Eibl
• MIT Manipal at ImageCLEF 2019 Visual Question Answering in Medical Domain
  Abhishek Thanki, Krishnamoorthi Makkithaya
• A Multimedia Modular Approach to Lifelog Moment Retrieval
  Maxime Tournadre, Guillaume Dupont, Vincent Pauwels, Bezeid Cheikh Mohamed Lmami, Alexandru Lucian Ginsca
• Ensemble of Streamlined Bilinear Visual Question Answering Models for the ImageCLEF 2019 Challenge in the Medical Domain
  Minh H. Vu, Raphael Sznitman, Tufve Nyholm, Tommy Löfstedt
• AI600 Lab at ImageCLEF 2019 Concept Detection Task
  Xinyi Wang, Ningning Liu
• Concept Detection based on Multi-label Classification and Image Captioning Approach - DAMO at ImageCLEF 2019
  Jing Xu, Wei Liu, Chao Liu, Yu Wang, Ying Chi, Xuansong Xie, Xiansheng Hua
• Zhejiang University at ImageCLEF 2019 Visual Question Answering in the Medical Domain
  Xin Yan, Lin Li, Chulin Xie, Jun Xiao, Lin Gu
• ZJUTCVR Team at ImageCLEFlifelog2019 Lifelog Moment Retrieval Task
  Pengfei Zhou, Cong Bai, Jie Xia
• TUA1 at ImageCLEF 2019 VQA-Med: a Classification and Generation Model based on Transfer Learning
  Yangyang Zhou, Xin Kang, Fuji Ren
• Estimating Severity from CT Scans of Tuberculosis Patients using 3D Convolutional Nets and Slice Selection
  Hasib Zunair, Aimon Rahman, Nabeel Mohammed

PAN Lab on Digital Text Forensics and Stylometry

• Overview of the Celebrity Profiling Task at PAN 2019
  Matti Wiegmann, Benno Stein, Martin Potthast
• Overview of the Style Change Detection Task at PAN 2019
  Eva Zangerle, Michael Tschuggnall, Günther Specht, Benno Stein, Martin Potthast
• Overview of the 7th Author Profiling Task at PAN 2019: Bots and Gender Profiling in Twitter
  Francisco Rangel, Paolo Rosso
• Overview of the Cross-domain Authorship Attribution Task at PAN 2019
  Mike Kestemont, Efstathios Stamatatos, Enrique Manjavacas, Walter Daelemans, Martin Potthast, Benno Stein
• Bots and Gender Prediction Using Language Independent Stylometry-based Approach
  Shaina Ashraf, Omer Javed, Muhammad Adeel, Haider Iqbal, Rao Muhmmad Adeel Nawab
• Author Profiling: Bot and Gender Prediction using a Multi-Aspect Ensemble Approach
  Hamed Babaei Giglou, Mostafa Rahgouy, Taher Rahgooy, Mohammad Karami Sheykhlan, Erfan Mohammadzadeh
• Bot and Gender Detection of Twitter Accounts Using Distortion and LSA
  Andrea Bacciu, Massimo La Morgia, Alessandro Mei, Eugenio Nerio Nemmi, Valerio Neri, Julinda Stefa
• Cross-Domain Authorship Attribution Combining Instance Based and Profile-Based Features
  Andrea Bacciu, Massimo La Morgia, Alessandro Mei, Eugenio Nerio Nemmi, Valerio Neri, Julinda Stefa
• Improving Cross-domain Authorship Attribution by Combining Lexical and Syntactic Features
  Martijn Bartelds, Wietse de Vries
• An Open-Vocabulary Approach to Authorship Attribution
  Angelo Basile
• Bot Or Not: A Two-Level Approach In Author Profiling
  Flora Bolonyai, Jakab Buda, Eszter Katona
• Tlemcen University: Bots and Gender Profiling Task
  Rabia Bounaama, Mohammed El Amine Abderrahim
• Unsupervised Pretraining for Text Classification using Siamese Transfer Learning
  Maximilian Bryan, J. Nathanael Philipp
• A Hierarchical Neural Network Approach for Bots and Gender Profiling
  Andrea Cimino, Felice Dell'Orletta
• Multi-channel Open-set Cross-domain Authorship Attribution
  José Eleandro Custódio, Ivandré Paraboni
• Combined CNN+RNN Bot and Gender Profiling
  Rafael Felipe Sandroni Dias, Ivandré Paraboni
• Bots and Gender Profiling using Character Bigrams
  Daniel Yacob Espinosa, Helena Gómez-Adorno, Grigori Sidorov
• Profiling Twitter Users Using Autogenerated Features Invariant to Data Distribution
  Tiziano Fagni, Maurizio Tesconi
• A Four Feature Types Approach for Detecting Bot and Gender of Twitter Users
  Johan Fernquist
• Identifying Twitter Bots Using a Convolutional Neural Network
  Michael Färber, Agon Qurdina, Lule Ahmedi
• Naive-Bayesian Classification for Bot Detection in Twitter
  Pablo Gamallo, Sattam Almatarneh
• Bot and Gender Detection using Textual and Stylistic Information
  Anastasia Giachanou, Bilal Ghanem
• Using Hashtags and POS-Tags for Author Profiling
  Flurin Gishamer
• Bots and Gender Profiling using a Multi-layer Architecture
  Régis Goubin, Dorian Lefeuvre, Alaa Alhamzeh, Jelena Mitrović, Előd Egyed-Zsigmond, Leopold Ghemmogne Fossi
• Bots and Gender Profiling of Tweets using Word and Character N-Grams
  Yaakov HaCohen-Kerner, Natan Manor, Michael Goldmeier
• An Unsophisticated Neural Bots and Gender Profiling System
  Oren Halvani, Philipp Marquardt
• UniNE at PAN-CLEF 2019: Bots and Gender Task
  Catherine Ikae, Sukunya Nath, Jacques Savoy
• Bots and Gender Profiling using Masking Techniques
  Victor Jimenez-Villar, Javier Sánchez-Junquera, Manuel Montes-Y-Gómez, Luis Villaseñor-Pineda, Simone Paolo Ponzetto
• Supervised Classification of Twitter Accounts Based on Textual Content of Tweets
  Fredrik Johansson
• FOI Cross-Domain Authorship Attribution for Criminal Investigations
  Fredrik Johansson, Tim Isbister,
• Author Profiling on Social Media: An Ensemble Learning Approach using Various Features
  Youngjun Joo, Inchon Hwang
• Twitter User Profiling: Bot and Gender Identification
  Dijana Kosmajac, Vlado Keselj
• Author Profiling using Semantic and Syntactic Features
  György Kovács, Vanda Balogh, Purvanshi Mehta, Kumar Shridhar, Pedro Alonso, Marcus Liwicki
• An Evolutionary Approach to Build User Representations for Profiling of Bots and Humans in Twitter
  Jesus López-Santillán, Luis González-Gurrola, Manuel Montes-Y-Gómez, Graciela Ramírez-Alonso, Olanda Prieto-Ordaz
• Twitter Bots and Gender Detection using Tf-idf
  Asad Mahmood, Padmini Srinivasan
• Who is Hot and Who is Not? Profiling Celebs on Twitter
  Matej Martinc, Blaž Škrlj, Senja Pollak
• Fake or Not: Distinguishing between Bots, Males and Females
  Matej Martinc, Blaž Škrlj, Senja Pollak
• Authorship Attribution through Punctuation n-grams and Averaged Combination of SVM
  Carolina Martín del Campo Rodríguez, Daniel Alejandro Pérez Álvarez, Christian Efraín Maldonado Sifuentes, Grigori Sidorov, Ildar Batyrshin, Alexander Gelbukh
• Celebrity Profiling on Twitter using Sociolinguistic Features
  Luis Gabriel Moreno-Sandoval, Edwin Puertas, Flor Miriam Plaza-del-Arco, Alexandra Pomares-Quimbaya, Jorge Andrés Alvarado-Valencia, L. Alfonso Ureňa-López
• Authorship Attribution in Fan-fictional Texts given Variable Length Character and Word n-grams
  Lukas Muttenthaler, Gordon Lucas, Janek Amann
• Style Change Detection by Threshold Based and Window Merge Clustering Methods
  Sukanya Nath
• Bot and Gender Identification: Textual Analysis of Tweets
  Rodrigo Ribeiro Oliveira, Cláudio Moisés Valiense de Andrade, José Solenir Lima Figuerêdo, João B. Rocha-Junior, Rodrigo Tripodi Calumby, Iago Machado da Conceição Silva, Almir Moreira da Silva Neto
• A Hierarchical Attention Network for Bots and Gender Profiling
  Cristian Onose, Claudiu-Marcel Nedelcu, Dumitru-Clementin Cercel, Stefan Trausan-Matu
• Celebrity Profiling with Transfer Learning
  Björn Pelzer
• Bots and Gender Profiling with Convolutional Hierarchical Recurrent Neural Network
  Juraj Petrik, Daniela Chuda
• Twitter Feeds Profiling with TF-IDF
  Juraj Petrik, Daniela Chuda
• Using N-grams to detect Bots on Twitter
  Juan Pizarro
• Identification Of Bot Accounts In Twitter Using 2D CNNs On User-generated Contents
  Marco Polignano, Marco Giuseppe de Pinto, Pasquale Lops, Giovanni Semeraro
• Bots and Gender Profiling using a Deep Learning Approach
  Jose R. Prieto Fontcuberta, Gretel Liz De La Peňa Sarracén
• Detecting Bot Accounts on Twitter by Measuring Message Predictability
  Piotr Przybyła
• Bots and Gender Profiling on Twitter using Sociolinguistic Features
  Edwin Puertas, Luis Gabriel Moreno-Sandoval, Flor Miriam Plaza-del-Arco, Jorge Andres Alvarado-Valencia, Alexandra Pomares-Quimbaya, L. Alfonso Ureňa-López
• Celebrity Profiling using TF-IDF, Logistic Regression, and SVM
  Victor Radivchev, Alex Nikolov, Alexandrina Lambova
• Cross-domain Authorship Attribution: Author Identification using a Multi-Aspect Ensemble Approach
  Mostafa Rahgouy, Hamed Babaei Giglou, Taher Rahgooy, Mohammad Karami Sheykhlan, Erfan Mohammadzadeh
• Bot and Gender Identification from Twitter
  Radarapu Rakesh, Yogesh Vishwakarma, Akkajosyula Surya Sai Gopal, Anand Kumar M
• Bots and Gender Classification on Twitter
  Usman Saeed, Farid Shirazi
• Bots and Gender Profiling on Twitter
  Muhammad Hammad Fahim Siddiqui, Iqra Ameer, Alexander Gelbukh, Grigori Sidorov
• Bots and Gender Profiling using Character and Word N-Grams
  Mahendrakar Srinivasarao, Siddharth Manu
• Stacked Bots and Gender Prediction from Twitter Feeds
  Todor Staykovski
• Word Distance Approach for Celebrity Profiling
  Muhammad Usman Asif, Muhammad Naeem, Zeeshan Ramzan, Fahad Najib
• Bots and Gender Identification Based on Stylometry of Tweet Minimal Structure and n-grams Model
  Alex I. Valencia Valencia, Helena Gomez Adorno, Christopher Stephens Rhodes, Gibran Fuentes Pineda
• Bot and Gender Recognition on Tweets using Feature Count Deviations
  Hans Van Halteren
• Cross-Domain Authorship Attribution with Federales
  Hans Van Halteren
• Bot and Gender Identification in Twitter using Word and Character N-Grams
  Inna Vogel, Peter Jiang
• Style Change Detection with Feed-forward Neural Networks
  Chaoyuan Zuo, Yu Zhao, Ritwik Banerjee

ProtestNews - Extracting Protests from News

• Overview of CLEF 2019 Lab ProtestNews: Extracting Protests from News in a Cross-context setting
  Ali Hürriyetoğlu, Erdem Yörük, Deniz Yuret, Çağrı Yoltar, Burak Gürel, Fırat Duruşan, Osman Mutlu, Arda Akdemir
• A Comparative Study on Generalizability of Information Extraction Models on Protest News
  Erkan Basar, Simge Ekiz, Antal van den Bosch
• ProTestA: Identifying and Extracting Protest Events in News Notebook for ProtestNews Lab at CLEF 2019
  Angelo Basile, Tommaso Caselli
• Linguistic Parameters and Word Embeddings for Protest News Detection in Text.
  Bechikh Ali Chedi
• ELMo Word Representations For News Protection
  Elizaveta Maslennikova
• Classification and Event Identification Using Word Embedding
  Anais Ollagnier, Hywel Williams
• Multitask Models for Supervised Protest Detection in Texts
  Benjamin J. Radford
• Event Sentence Detection Task Using Attention Model
  Ali Safaya
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