ADR Awareness Centre

Since the formulation of states, political authorities and political parties have sought to gauge public opinion. In recent years, opinion polls have been able to gratify this need rather efficiently.

Sentiment analysis in texts, also known as opinion mining, is a significant Natural Language Processing (NLP) task, with many applications in automated social media monitoring, customer feedback processing, e-mail scanning, etc.

Natural Language Processing (NLP) is a subfield of artificial intelligence and computational linguistics with the goal of “understanding” human language.

This study addresses the lack of a systematic analysis of British COVID-19 discourse during the pandemic, which has sparked intense public debate globally.

The advent of pervasive and connected digital technologies has profoundly affected both the way in which politicians interact with citizens and supporters and the way in which scholars study political communication.

External independent and unobtrusive algorithmic audits offer a fresh perspective for understanding AI-based algorithms used in social media and search engines.

The talk discusses the disinformation study undertaken by the author and commissioned by the Dutch Ministry of Internal Affairs, published in 2020. It introduces the context of the concern for ‘fake news’ in Europe after the U.S.

This paper delves into the critical role of social media in debates surrounding polarization, misinformation, and the state of democracy worldwide.

Computational Politics refers to the application of Information Technologies (IT), including Data Analytics, Artificial Intelligence (AI), and Systems Theory (Cybernetics) in the realm of politics and Political Science.

In contrast with random uniform instances, industrial SAT instances of large size are solvable today by state-of-the-art algorithms.

AI is a rapidly emerging field that has opened up new vistas of innovation and creativity. From intelligent systems to self-driving cars, AI has transformed the way we live and work.

The Propositional Satisfiability problem (SAT) was the first to be shown NP-complete by Cook and Levin. SAT remained the embodiment of theoretical worst-case hardness.