The ResT-UP workshop organizing committee is happy to announce that, despite the cancellation of LREC due to the COVID-19 international situation, ResT-UP will still be held online on Microsoft Teams on May 12th at 4:30 pm (UTC+1).

Please, follow these indications to attend the online ResT-UP workshop.

  • sign up to Microsoft Teams (for a better experience we highly recommend to download the Microsoft Teams app instead of using the web version);
  • fill out and send this form;
  • the “ResT-UP workshop” team in your teams’ list should appear in a few hours;
  • log on Microsoft Teams on May 12 at 4:15pm (UTC +1). You will find a scheduled meeting in the  “ResT-UP workshop” team chat. Simply click “Join” and enjoy ResT-UP!

If you are interested in attending the workshop, please do not hesitate to fill out the form: It is not possible to host more than 100 users in the same team and around 20 slots are already reserved for ResT-UP organizers and paper authors.


  • 4:30 pm (UTC +1) Anita Saroj and Sukomal Pal, An Indian Language Social Media Collection for Hate and Offensive Speech
  • 4:50 pm (UTC +1) Elisabetta Fersini, Debora Nozza and Giulia Boifava, Profiling Italian Misogynist: An Empirical Study
  • 5:10 pm (UTC +1) Juliet van Rosendaal, Tommaso Caselli and Malvina Nissim, Lower Bias, Higher Density Abusive Language Datasets: A Recipe
  • 5:30 pm (UTC +1) Invited speaker:
  • Paolo Rosso, Profiling Bots, Fake News Spreaders and Haters

Invited Speaker

Paolo Rosso, Universitat Politècnica de València

Paolo Rosso

Title: Profiling Bots, Fake News Spreaders and Haters

Author profiling studies how language is shared by people. Stylometry techniques help in identifying aspects such as gender, age, native language, or even personality. Author profiling is a problem of growing importance, not only in marketing and forensics, but also in cybersecurity. The aim is not only to identify users whose messages are potential threats from a terrorism viewpoint but also those whose messages are a threat from a social excusion perspective because containing hate speech, cyberbullying etc.

Bots often play a key role in spreading hate speech, as well as fake news, with the purpose of polarizing the public opinion with respect to controversial issues like Brexit or the Catalan referendum. For instance, the authors of a recent study about the 1 Oct 2017 Catalan referendum, showed that in a dataset with 3.6 million tweets, about 23.6% of tweets were produced by bots. The target of these bots were pro independence influencers that were sent negative, emotional and aggressive hateful tweets with hashtags such as #sonunesbesties (i.e. #theyareanimals).

Since 2013 at the PAN Lab at CLEF ( we have addressed several aspects of author profiling in social media. In 2019 we investigated the feasibility of distinguishing whether the author of a Twitter feed is a bot, while this year we are addressing the problem of profiling those authors that are more likely to spread fake news in Twitter because they did in the past. We aim at identifying possible fake news spreaders as a first step towards preventing fake news from being propagated among online users (fake news aim to polarize the public opinion and may contain hate speech).

In 2021 we specifically aim at addressing the challenging problem of profiling haters in social media in order to monitor abusive language and prevent cases of social exclusion in order to combat, for instance, racism, xenophobia and misoginy. Although we already started addressing the problem of detecting hate speech when targets are immigrants or women at the HatEval shared task in SemEval-2019, and when targets are women also in the Automatic Misogeny Identification tasks at IberEval-2018, Evalita-2018 and Evalita-2020, it was not done from an author profiling perspective. At the end of the keynote I will present some insights in order to stress the importance of monitoring abusive language in social media, for instance, in foreseeing sexual crimes. In fact, previous studies confirmed that a correlation might lay between the yearly per capita rate of rape and the misogynistic language used in Twitter.