Litcius/Paper detail

NeedFull – a Tweet Analysis Platform to Study Human Needs During the COVID-19 Pandemic in New York State

Zijian Long, Rajwa Alharthi, Abdulmotaleb El Saddik

2020IEEE Access45 citationsDOIOpen Access PDF

Abstract

Governments and municipalities need to understand their citizens' psychological needs in critical times and dangerous situations. COVID-19 brings lots of challenges to deal with. We propose NeedFull, an interactive and scalable tweet analysis platform, to help governments and municipalities to understand residents' real psychological needs during those periods. The platform mainly consists of four parts: data collection module, data storage module, data analysis module and data visualization module. The four parts interact with each other and provide users with a thorough human needs analysis based on their queries. We employed the proposed platform to investigate the reaction of people in New York State to the ongoing worldwide COVID-19 pandemic.

Topics & Concepts

PandemicCoronavirus disease 2019 (COVID-19)Computer scienceVisualizationScalabilityState (computer science)Data scienceData visualizationData collection2019-20 coronavirus outbreakWorld Wide WebComputer securityDatabaseArtificial intelligenceSociologyVirologyDiseaseMedicineInfectious disease (medical specialty)PathologyAlgorithmBiologyOutbreakSocial scienceSentiment Analysis and Opinion MiningComplex Network Analysis TechniquesAdvanced Text Analysis Techniques