Utility: Early determination of the gravity of social disruption/protests
Case study: Artificial Intelligence based early determination/duration of the social disruption/protests for news
Protests and agitations are an integral part of any democratic civil society. Not to be left behind when compared with the rest of the world, South Africa in recent years has also seen a massive increase in public protests. The causes of these protest are varied and have ranged from service delivery, labor related issues, crime, education, to environmental issues.
Our work is an implementation of a large variety of semantic and probabilistic text mining models (including advanced modelling such as probabilistic Latent Dirichlet Allocation, Correlated and Structural Topic Modelling techniques, Memory based Neural Networks etc) to teach an AI system to comprehend text, finer nuances of sentiments etc.
Texts in the form of both historical and online news articles (both authentic and click bait/fake websites), blogs from popular social media, tagged repositories etc, are automatically scraped from the internet to create our own repository.
Finally the end output of the developed AI system is: for a user inputting a news of social disruption in free flowing English text, the system automatically predicts the length and impact of the duration to a very high degree of predictive accuracy. For a large variety of such input texts over a duration of time, the system also provides a real time change in sentiment of the topic.
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Artificial Intelligence is the branch of computer science concerned with making computers behave like humans, i.e. with automation of intelligent behaviour.
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