no code implementations • 21 Feb 2024 • Preni Golazizian, Ali Omrani, Alireza S. Ziabari, Morteza Dehghani
In subjective NLP tasks, where a single ground truth does not exist, the inclusion of diverse annotators becomes crucial as their unique perspectives significantly influence the annotations.
no code implementations • 24 Jan 2024 • Benjamin A. T. Grahama, Lauren Brown, Georgios Chochlakis, Morteza Dehghani, Raquel Delerme, Brittany Friedman, Ellie Graeden, Preni Golazizian, Rajat Hebbar, Parsa Hejabi, Aditya Kommineni, Mayagüez Salinas, Michael Sierra-Arévalo, Jackson Trager, Nicholas Weller, Shrikanth Narayanan
Interactions between the government officials and civilians affect public wellbeing and the state legitimacy that is necessary for the functioning of democratic society.
1 code implementation • 29 Sep 2023 • Ali Omrani, Alireza S. Ziabari, Preni Golazizian, Jeffery Sorensen, Morteza Dehghani
Detecting problematic content, such as hate speech, is a multifaceted and ever-changing task, influenced by social dynamics, user populations, diversity of sources, and evolving language.
no code implementations • 10 Aug 2022 • Jackson Trager, Alireza S. Ziabari, Aida Mostafazadeh Davani, Preni Golazizian, Farzan Karimi-Malekabadi, Ali Omrani, Zhihe Li, Brendan Kennedy, Nils Karl Reimer, Melissa Reyes, Kelsey Cheng, Mellow Wei, Christina Merrifield, Arta Khosravi, Evans Alvarez, Morteza Dehghani
Moral framing and sentiment can affect a variety of online and offline behaviors, including donation, pro-environmental action, political engagement, and even participation in violent protests.
no code implementations • LREC 2020 • Seyed Arad Ashrafi Asli, Behnam Sabeti, Zahra Majdabadi, Preni Golazizian, reza fahmi, Omid Momenzadeh
Active Learning models can achieve the baseline performance (the accuracy of the model trained on the whole dataset), with a considerably lower amount of labeled data.
no code implementations • LREC 2020 • Preni Golazizian, Behnam Sabeti, Seyed Arad Ashrafi Asli, Zahra Majdabadi, Omid Momenzadeh, reza fahmi
In the current research, which is the first attempt at irony detection in Persian language, emoji prediction is used to build a pretrained model.
no code implementations • LREC 2020 • Zahra Majdabadi, Behnam Sabeti, Preni Golazizian, Seyed Arad Ashrafi Asli, Omid Momenzadeh, reza fahmi
In order to overcome this issue and extract trends using all tweets, we propose a graph-based approach where graph nodes represent tweets as well as words and hashtags.