About

The RecSys Challenge 2020 will be organized by Politecnico di Bari, Free University of Bozen-Bolzano, TU Wien, University of Colorado, Boulder, and Universidade Federal de Campina Grande, and sponsored by Twitter. The challenge focuses on a real-world task of tweet engagement prediction in a dynamic environment. The goal is to predict the probability for different types of engagement (Like, Reply, Retweet, and Retweet with Comment) of a target user for a set of tweets, based on heterogeneous input data.

Publications

Luca Belli, Sofia Ira Ktena, Alykhan Tejani, Alexandre Lung-Yut-Fon, Frank Portman, Xiao Zhu, Yuanpu Xie, Akshay Gupta, Michael Bronstein, Amra Delić, Gabriele Sottocornola, Walter Anelli, Nazareno Andrade, Jessie Smith, and Wenzhe Shi. 2020. Privacy-Preserving Recommender Systems Challenge on Twitter's Home Timeline, arXiv:2004.13715.

Participation and Data

Twitter has released a large public dataset of 160M public tweets, obtained by subsampling within ~2 weeks, that contains engagement features, user features, and tweet features.

Registration & Data Access

If you are experiencing any issues, please notify the organizers.

Participation for this challenge is subject to the acceptance of these Terms & Conditions

IMPORTANT

Due to the reported possible data leakage, we want to emphasize and enrich some of the existing rules in the competition in order to discourage and prevent participants from taking advantage of it.

Please notice that no actual data leakage happened: The Twitter data provided are all publicly available via the API and de-anonymization of the dataset was always possible and expected. The following measures are just intended to ensure a fair competition.

The Terms & Conditions already require that all submissions are accompanied by reproducible code, so that we can inspect winning solutions in detail: “Your Submission must include the source code and any related information used to derive the results contained in your Submission. The source code must be released under an open-source license (Apache 2.0). A third party should be able to use your submitted source to regenerate your results.” Furthermore, we explicitly state in our rules that NO de-anonymization or access to data from Twitter users and user behavior from the Twitter API other than that in the challenge dataset is allowed. Enriching the data with other data sources remains possible.

If any of the rules mentioned in the Terms & Conditions (and explained further above) are broken and thus discovered by the organizers in the code submission, the participant(s) that the submission belongs to will be disqualified from the competition. As mentioned in the Terms and Conditions: “Organizers and Sponsor reserve the right, in their sole discretion, to disqualify any participant who makes a Submission that does not meet the Requirements or is in violation of these Terms.”

Paper Submission Guidelines ^top

Submission website: EasyChair

• All participants of the challenge are invited to submit if they consider their submission particularly effective, novel, otherwise interesting, or exploiting identified particularities of the data.
• Note: paper submission is mandatory if you want to be eligible for a prize (top 5). Accepted papers are given an oral and a poster presentation slot at the workshop. At least one author of each accepted paper must attend the workshop and present their work. Please note that a badly written paper or absence of presence at workshop, may prevent you from being eligible for the prize. Please contact the workshop organization if none of the authors will be able to attend the workshop.
• Page limit: 7 pages + references (ACM SIG Format) Note: This is in reference to the latest single-column ACM template.
• Anonymization of submissions is not required; please include your team name in abstract and text, as well as a link to your code repository, the achieved score, and a reference to the RecSys Challenge Website (http://www.recsyschallenge.com/2020/). Note: This will be replaced with a reference to an overview paper in the RecSys proceedings for the camera-ready version.
• The submitted papers will be evaluated based on novelty, clarity, and presented empirical results.
• Each paper will be reviewed by at least three PC members.
• Our proceedings will be published in the ACM Digital Library within its International Conference Proceedings Series.
• Accepted papers must be presented in the RecSys Challenge Workshop (either as an oral presentation or poster).

Workshop Program and Accepted Papers

The RecSys Challenge Workshop will take place on September 26th, 2020
All times are GMT

Time	Session
2:00 PM - 2:10 PM	Workshop Opening: Vito Walter Anelli, Amra Delic, Gabriele Sottocornola, Jessie Smith, Nazareno Andrade
2:10 PM - 2:40 PM	Introduction to the Challenge: Twitter Team
2:40 PM - 3:10 PM	3rd place - A Stacking Ensemble Model for Prediction of Multi-type Tweet Engagements: Shuhei Goda, Naomichi Agata and Yuya Matsumura 25 min Presentation + 5 min Q&A
3:10 PM - 3:30 PM	A combination of classification based methods for recommending tweets: Sumit Sidana 15 min Presentation + 5 min Q&A
3:30 PM - 4:30 PM	Break
4:30 PM - 4:50 PM	Engaging with Tweets: The Missing Dataset On Social Media: Seyed Ali Alhosseini, Raad Bin Tareaf and Christoph Meinel 15 min Presentation + 5 min Q&A
4:50 PM - 5:20 PM	2nd place - Predicting Twitter Engagement With Deep Language Models: Maksims Volkovs, Zhaoyue Cheng, Mathieu Ravaut, Hojin Yang, Kevin Shen, Jin Peng Zhou, Anson Wong, Saba Zuberi and Aidan Gomez 25 min Presentation + 5 min Q&A
5:20 PM - 5:40 PM	Leveraging User Embeddings and Text to Improve CTR Predictions With Deep Recommender Systems: Carlos Patiño, Camilo Velásquez, Juan Muñoz, Juan Gutiérrez, David Valencia and Cristian Bartolome Aramburu 15 min Presentation + 5 min Q&A
5:40 PM - 6:00 PM	Multi-Objective Blended Ensemble For Highly Imbalanced Sequence Aware Tweet Engagement Prediction: Nicolò Felicioni, Andrea Donati, Luca Conterio, Luca Bartoccioni, Davide Yi Xian Hu, Cesare Bernardis and Maurizio Ferrari Dacrema 15 min Presentation + 5 min Q&A
6:00 PM - 7:00 PM	Break
7:00 PM - 7:30 PM	1st place - GPU Accelerated Feature Engineering and Training for Recommender Systems: Benedikt Schifferer, Gilberto Titericz, Chris Deotte, Christof Henkel, Kazuki Onodera, Jiwei Liu, Bojan Tunguz, Even Oldridge, Gabriel De Souza Pereira Moreira and Ahmet Erdem 25 min Presentation + 5 min Q&A
7:30 PM - 7:50 PM	Gradient Boosting and Language Model Ensemble for Tweet Recommendation: Pere Gilabert and Santi Seguí 15 min Presentation + 5 min Q&A
7:50 PM - 8:10 PM	Why Are Deep Learning Models Not Consistently Winning Recommender Systems Competitions Yet?: Dietmar Jannach, Gabriel de Souza Pereira Moreira and Even Oldridge 15 min Presentation + 5 min Q&A
8:10 PM - 8:30 PM	Final Remarks & Panel Discussion Dietmar Jannach (University of Klagenfurt) Chris Deotte (NVIDIA RAPIDS.AI) Maksims Volkovs (Layer 6) Luca Belli (Twitter) Wenzhe Shi (Twitter)

Program Committee ^top

• Francesco Ricci, Free University of Bozen-Bolzano, Italy
• David Massimo, Free University of Bozen-Bolzano, Italy
• Fabio Stella, University of Milano-Bicocca, Italy
• Markus Zanker, Free University of Bozen-Bolzano, Italy
• Ludovik Coba, Free University of Bozen-Bolzano, Italy
• Julia Neidhardt, Vienna University of Technology, Austria
• Thuy Ngoc Nguyen, Carnegie Mellon University, USA
• Marko Tkalčič, University of Primorska, Slovenia
• Linus Dietz, Technical University of Munich, Germany
• Wolfgang Worndl, Technical University of Munich, Germany
• Dietmar Jannach, University of Klagenfurt, Austria
• Mehdi Elahi, University of Bergen, Norway
• Peter Knees, TU Wein, Austria
• Alejandro Bellogin, Universidad Autónoma de Madrid, Spain
• Pablo Castells, Universidad Autónoma de Madrid, Spain
• Ivan Cantador, Universidad Autónoma de Madrid, Spain
• Tommaso Di Noia, Polytechnic University of Bari, Italy
• Ludovico Boratto, ACM
• Luca Belli, Twitter
• Michael Bronstein, Twitter
• Frank Portman, Twitter
• Wenzhe Shi, Twitter
• Alykhan Tejani, Twitter
• Xiao Zhu, Twitter
• Yuanpu Xie, Twitter
• Sofia Ira Ktena, Twitter
• Alexandre Lung-Yut-Fong, Twitter

Academic Organizers ^top

• Nazareno Andrade, Universidade Federal de Campina Grande, Brazil
• Walter Anelli, Politecnico di Bari, Italy
• Amra Delic, TU Wien, Austria & University of Sarajevo, Bosnia and Herzegovina
• Jessie Smith, University of Colorado, Boulder
• Gabriele Sottocornola, Free University of Bozen-Bolzano, Italy

Sponsor Mentors ^top

• Luca Belli, Twitter
• Michael Bronstein, Twitter
• Alexandre Lung-Yut-Fong, Twitter
• Sofia Ira Ktena, Twitter
• Frank Portman, Twitter
• Wenzhe Shi, Twitter
• Alykhan Tejani, Twitter
• Yuanpu Xie, Twitter
• Xiao Zhu, Twitter

Advisors ^top

• Yashar Deldjoo, Polytechnic University of Bari, Italy
• Peter Knees, TU Wien, Austria