Analyzing the Impact of COVID-19 on Economy from the Perspective of Users Reviews
Fatemeh Salmani, Hamed Vahdat-Nejad, Hamideh Hajiabadi

TL;DR
This study analyzes COVID-19 related social media comments using NLP to understand public economic sentiment, revealing impacts of the pandemic and restrictions on global and top economies' sentiments over time.
Contribution
It introduces a method combining geo-location and economic sentiment analysis of tweets using RoBERTa, providing insights into pandemic-related economic public opinion.
Findings
Economic tweets increase with COVID-19 cases and restrictions
Sentiment analysis shows economic downturn correlates with pandemic events
Public opinion varies across countries and over time
Abstract
One of the most important incidents in the world in 2020 is the outbreak of the Coronavirus. Users on social networks publish a large number of comments about this event. These comments contain important hidden information of public opinion regarding this pandemic. In this research, a large number of Coronavirus-related tweets are considered and analyzed using natural language processing and information retrieval science. Initially, the location of the tweets is determined using a dictionary prepared through the Geo-Names geographic database, which contains detailed and complete information of places such as city names, streets, and postal codes. Then, using a large dictionary prepared from the terms of economics, related tweets are extracted and sentiments corresponded to tweets are analyzed with the help of the RoBERTa language-based model, which has high accuracy and good…
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Taxonomy
MethodsMulti-Head Attention · Attention Is All You Need · Linear Layer · Refunds@Expedia|||How do I get a full refund from Expedia? · Weight Decay · Layer Normalization · WordPiece · Adam · Attention Dropout · Dropout
