Second Workshop on Combating Online Hostile Posts in Regional Languages during Emergency Situation
Multimodal Low-Resource Language Processing to Combat COVID-19 Related Online Hostile Content
The increasing accessibility of the Internet has dramatically changed the way we consume information. The ease of social media usage not only encourages individuals to freely express their opinion (freedom of speech) but also provides content polluters with ecosystems to spread hostile posts (hate speech, fake news, cyberbullying, propaganda, etc.). Such hostile activities are expected to increase manifold during emergencies such as the presidential election and COVID-19 pandemic spreading. Most of such hostile posts are written in regional languages, and therefore can easily evade online surveillance engines that are majority trained on the posts written in resource-rich languages such as English and Chinese. Therefore, regions such as Asia, Africa, South America, where low-resource regional languages are used for day-to-day communication, suffer due to the lack of tools, benchmark datasets and learning techniques. Other developing countries such as Italy, Spain, where the used languages (pseudo-low-resource) are not as equipped with sophisticated computational resources as English, might also be facing the same issues.
Following the success of the first edition of CONSTRAINT (collocated with AAAI-21), the second edition will encourage researchers from interdisciplinary domains working on multilingual social media analytics to think beyond the conventional way of combating online hostile posts. The workshop will broadly focus on three major points: