Covid-Transformer: Detecting COVID-19 Trending Topics on Twitter Using
Universal Sentence Encoder

v1v2v3 (latest)

Covid-Transformer: Detecting COVID-19 Trending Topics on Twitter Using Universal Sentence Encoder

8 September 2020

M. Asgari-Chenaghlu

Narjes Nikzad Khasmakhi

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Papers citing "Covid-Transformer: Detecting COVID-19 Trending Topics on Twitter Using Universal Sentence Encoder"

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Title
A Human Word Association based model for topic detection in social networks Mehrdad Ranjbar-Khadivi Shahin Akbarpour M. Feizi-Derakhshi B. Anari 104 5 0 30 Jan 2023
An Exploratory Study of Tweets about the SARS-CoV-2 Omicron Variant: Insights from Sentiment Analysis, Language Interpretation, Source Tracking, Type Classification, and Embedded URL Detection Nirmalya Thakur Chia Y. Han 64 38 0 20 Jul 2022
An Empirical Study on How Well Do COVID-19 Information Dashboards Service Users' Information Needs Xinyan Li Han Wang Chunyang Chen John C. Grundy 20 6 0 30 May 2022
COVID-19 Modeling: A Review LongBing Cao Qing Liu 96 46 0 16 Apr 2021