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ai-based Automated Extraction of Location-Oriented COVID-19 Sentiments

Computers, Materials & Continua 2022年第8期72卷 3631-3649页

作者： Fahim K.Sufi Musleh Alsulami Federal Government MelbourneVIC3000Australia Information Systems Department Umm Al-Qura University(UQU)Makkah24382Saudi Arabia

The coronavirus disease(COVID-19)pandemic has affected the lives of social media users in an *** are constantly posting their satisfaction or dissatisfaction over the COVID-19 situation at their location of ***,understanding location-oriented sentiments about this situation is of prime importance for political leaders,and strategic *** this end,we present a new fully automated algorithm based on artificial intelligence(ai),for extraction of location-oriented public sentiments on the COVID-19 *** designed the proposed system to obtain exhaustive knowledge and insights on social media feeds related to COVID-19 in 110 languages through ai-based translation,sentiment analysis,location entity detection,and decomposition tree *** deployed fully automated algorithm on live Twitter feed from July 15,2021 and it is still running as of 12 January,*** system was evaluated on a limited dataset between July 15,2021 to August 10,*** this evaluation timeframe 150,000 tweets were analyzed and our algorithm found that 9,900 tweets contained one or more location *** total,13,220 location entities were detected during the evaluation period,and the rates of average precision and recall rate were 0.901 and 0.967,*** of 12 January,2022,the proposed solution has detected 43,169 locations using entity *** to the best of our knowledge,this study is the first to report location intelligence with entity detection,sentiment analysis,and decomposition tree analysis on social media messages related to COVID-19 and has covered the largest set of languages.

关键词： Entity recognition ai-based social media monitoring sentiment analysis decision support system COVID-19

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