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COVID-19 Tweet Analysis using Hybrid Keyword Extraction Approach
10th IEEE International Conference on Communication Systems and Network Technologies, CSNT 2021 ; : 136-140, 2021.
Article in English | Scopus | ID: covidwho-1700084
ABSTRACT
Aim of this paper is to identify the key issues discussed among the people on Twitter using machine learning and NLP techniques regarding COVID-19. One of the most important way to produce these insights is Automatic Keyword Extraction. It is a method to obtain the most important words from the text by summarizing thus providing an insight into the whole context. Text Summarization is the process to condense the content without the loss of significant data. This paper applies a hybrid model of graph-based and topic modeling approaches to extract keywords from a large dataset of approximately 1 million tweets. © 2021 IEEE.
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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: 10th IEEE International Conference on Communication Systems and Network Technologies, CSNT 2021 Year: 2021 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: 10th IEEE International Conference on Communication Systems and Network Technologies, CSNT 2021 Year: 2021 Document Type: Article