Event Detection System Based on User Behavior Changes in Online Social Networks: Case of the COVID-19 Pandemic

• Published in: IEEE access Vol. 8; pp. 158806 - 158825
• Main Authors: Rosa, Renata Lopes, De Silva, Marielle Jordane, Silva, Douglas Henrique, Ayub, Muhammad Shoaib, Carrillo, Dick, Nardelli, Pedro H. J., Rodriguez, Demostenes Zegarra
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.01.2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: affective analysis; Algorithms; Artificial neural networks; Belief networks; Coronaviruses; COVID-19; Diseases; Emotions; Event detection; Industry Applications; Machine learning; Modules; Natural language processing; online social networks; Performance assessment; Public health; Public healthcare; Social Implications of Technology; Social networks; Twitter; User behavior; Viral diseases

People use Online Social Networks (OSNs) to express their opinions and feelings about many topics. Depending on the nature of an event and its dissemination rate in OSNs, and considering specific regions, the users' behavior can drastically change over a specific period of time. In this context...