Analysis Of COVID-19 Effects On Wellbeing - Study Of Reddit Posts Using Natural Language Processing Techniques
2022 International Conference on Emerging Trends in Electrical, Control, and Telecommunication Engineering, ETECTE 2022
; 2022.
Article
in English
| Scopus | ID: covidwho-2227030
ABSTRACT
The COVID-19 pandemic continues to negatively impact people's mental health worldwide. Due to the rise in unemployment, loss of income, and lack of social interaction, people are now more likely to feel lonely, go on fewer outings, and dread the unexpected nature of viral transmission. Meanwhile, Public Health authorities are interested in monitoring people's mental and emotional well-being. In this paper, natural language processing is used to analyze human sentiments concerning the COVID-19 pandemic that has been dangerously affecting individuals' mental and physical well-being for more than two years now. Even though several waves of COVID-19 have passed, of which the first and third waves i.e., the initial pandemic period from 20th March 2020 and the rise of the Delta variant from January 2020 had the most impact on the mental health of individuals, this is further evident by the results of this paper. This research focuses on how severely this virus has affected people's mental health and emotions. After processing the data i.e., cleaning, formatting, and removing irregularities from the data, feature engineering models are applied to acquire the results. The results through VADER (valence-aware dictionary and sentiment reasoning) indicate an increase in overall negative sentiments between two mentioned periods. Additionally, the NRC-EIL (National Research Council of Canada - Emotion Intensity Lexicon) analysis showed that 'fear' and 'sadness' occurred during those times. © 2022 IEEE.
Context-based analysis; Coronavirus; COVID-19; Health issues; Natural Language Processing; NRC-EIL; Reddit; Sentimental analysis; Social media; VADER; Well-being; Behavioral research; Data handling; Natural language processing systems; Social networking (online); Context-based; Context-based analyse; Coronaviruses; Emotion intensity; Language processing; National Research Council of Canada; National research council of canada - emotion intensity lexicon; Natural languages; Sentimental analyse; Valence-aware dictionary and sentiment reasoning; Well being
Full text:
Available
Collection:
Databases of international organizations
Database:
Scopus
Type of study:
Experimental Studies
Topics:
Variants
Language:
English
Journal:
2022 International Conference on Emerging Trends in Electrical, Control, and Telecommunication Engineering, ETECTE 2022
Year:
2022
Document Type:
Article
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