Deep Learning-based Sentiment Analysis and Topic Modeling on Tourism During Covid-19 Pandemic
The Covid-19 pandemic has disrupted the world economy and significantly influenced the tourism industry. Millions of people have shared their emotions, views, facts, and circumstances on numerous social media platforms, which has resulted in a massive flow of information. The high-density social med...
Enregistré dans:
Auteurs principaux: | Ram Krishn Mishra, Siddhaling Urolagin, J. Angel Arul Jothi, Ashwin Sanjay Neogi, Nishad Nawaz |
---|---|
Format: | article |
Langue: | EN |
Publié: |
Frontiers Media S.A.
2021
|
Sujets: | |
Accès en ligne: | https://doaj.org/article/da63d87333934d989a352c3a04a1c2d7 |
Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
Documents similaires
-
Topic-Based Document-Level Sentiment Analysis Using Contextual Cues
par: Ciprian-Octavian Truică, et autres
Publié: (2021) -
Performance Study of N-grams in the Analysis of Sentiments
par: O. E. Ojo, et autres
Publié: (2021) -
Arabic Aspect-Based Sentiment Analysis: A Systematic Literature Review
par: Ruba Obiedat, et autres
Publié: (2021) -
Deep Bidirectional LSTM Network Learning-Based Sentiment Analysis for Arabic Text
par: Elfaik Hanane, et autres
Publié: (2020) -
Improving sentiment analysis in Arabic: A combined approach
par: Belgacem Brahimi, et autres
Publié: (2021)