Social media analysis to manage community behaviors during crisis
During crisis periods such as outbreaks, wars and uprisings, opinion divergence and misinformation tend to largely increase causing an epidemic of fear and a trouble in decision making. By the information age, these phenomena are reflected in social media such as Facebook and Twitter where people dynamically show their thoughts and beliefs on a daily basis. In this discussion, we will try to show how the recent advances in machine learning, data analytics and natural language processing can be used to identify the social thoughts of a given society about a particular topic and consequently to guide sociopolitical decisions through the recommendation of several actions or of several research publications to fight misinformation and make the general opinion more reasonable and efficient.
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