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

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.

TClustVID: A novel machine learning classification model to investigate topics and sentiment in COVID-19 tweets

“…In current work, we present a well-organized machine learning model that has been employed into common COVID-19 oriented tweets where different regions are not specified like previous studies [18] , [28] , [48] , [49] . Both sentiment analysis and topics modelling were used to explore COVID-19 related themes than many works [18] , [20] , [22] , [24] , [27] , [48] , [49] , [50] , [51] . However, many machine learning classifiers have been implemented in which we compared our proposed model with more traditional analyses to evaluate performance.…”

IoT-enabled stacked ensemble of deep neural networks for the diagnosis of COVID-19 using chest CT scans

“…Besides, a few research efforts [ 37 , 45 ] have contributed by developing models with interpretability results for wider acceptability of the models among front line clinical professionals. Yet, some research efforts [ 18 , 21 , 26 , 29 ] introduced the privacy-aware energy-efficient framework for data collection, data fusion, visualization, and secure communication in COVID-19 application environments.…”

A Survey on Big Data Research in Fighting COVID-19: Contributions and Techniques

“…Studies on COVID-19 discussed social psychology, examining people's behavior in social situations and their capability to adapt to certain conditions' social environments [14]. Research topics in social psychology covered in the past studies include the relationship between trust and the presence of infectious disease [70]; psychological needs and their satisfaction level during the pandemic [71]; the effect of fear and collectivism on the public prevention against COVID-19 [72]; peoples' preferences to protect the environment they live in [73]. Some of the harmful effects of the pandemic have been studied, including family violence [21], increasing racial sentiment toward Asian people [23], the emergence of incivility and fake news on social media [74,29], and emotional tendency and emotional symptoms of mental disorder facing the outbreak [75,76].…”

“…Further, people's psychological needs during the pandemic in a particular area can be observed from user-generated content posted on Twitter. Long et al [71] applied Natural Language Processing (NLP) and Support Vector Machine (SVM) algorithm to research this subject. A similar technique was utilized to investigate the shifts in anti-Asian racial sentiment regarding the emergence of COVID-19 [23].…”

“…MongoDB Document oriented, NoSQL, crossplatform distributed database to store data in JSON-like documents Healthcare monitoring remote system [37]. Classification of residents' psychological needs [71].…”