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1
PROTECT: A Pipeline for Propaganda Detection and Classification
In: CLiC-it 2021- Italian Conference on Computational Linguistics ; https://hal.archives-ouvertes.fr/hal-03417019 ; CLiC-it 2021- Italian Conference on Computational Linguistics, Jan 2022, Milan, Italy (2022)
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2
#Bittersweet: Positive, negative, and mixed emotions in twitter posts ...
Langbehn, Andrew. - : Open Science Framework, 2022
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3
Evaluation computergestützter Verfahren der Emotionsklassifikation für deutschsprachige Dramen um 1800 ...
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Evaluation computergestützter Verfahren der Emotionsklassifikation für deutschsprachige Dramen um 1800 ...
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5
MULDASA: Multifactor Lexical Sentiment Analysis of Social-Media Content in Nonstandard Arabic Social Media
In: Applied Sciences; Volume 12; Issue 8; Pages: 3806 (2022)
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6
Lexicon-Based vs. Bert-Based Sentiment Analysis: A Comparative Study in Italian
In: Electronics; Volume 11; Issue 3; Pages: 374 (2022)
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7
A New Ontology-Based Method for Arabic Sentiment Analysis
In: Big Data and Cognitive Computing; Volume 6; Issue 2; Pages: 48 (2022)
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8
COVID-19 Vaccination-Related Sentiments Analysis: A Case Study Using Worldwide Twitter Dataset
In: Healthcare; Volume 10; Issue 3; Pages: 411 (2022)
Abstract: COVID-19 pandemic has caused a global health crisis, resulting in endless efforts to reduce infections, fatalities, and therapies to mitigate its after-effects. Currently, large and fast-paced vaccination campaigns are in the process to reduce COVID-19 infection and fatality risks. Despite recommendations from governments and medical experts, people show conceptions and perceptions regarding vaccination risks and share their views on social media platforms. Such opinions can be analyzed to determine social trends and devise policies to increase vaccination acceptance. In this regard, this study proposes a methodology for analyzing the global perceptions and perspectives towards COVID-19 vaccination using a worldwide Twitter dataset. The study relies on two techniques to analyze the sentiments: natural language processing and machine learning. To evaluate the performance of the different lexicon-based methods, different machine and deep learning models are studied. In addition, for sentiment classification, the proposed ensemble model named long short-term memory-gated recurrent neural network (LSTM-GRNN) is a combination of LSTM, gated recurrent unit, and recurrent neural networks. Results suggest that the TextBlob shows better results as compared to VADER and AFINN. The proposed LSTM-GRNN shows superior performance with a 95% accuracy and outperforms both machine and deep learning models. Performance analysis with state-of-the-art models proves the significance of the LSTM-GRNN for sentiment analysis.
Keyword: COVID-19 vaccination; deep learning; healthcare; lexicon-based approaches; sentiment analysis
URL: https://doi.org/10.3390/healthcare10030411
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9
Exploring Bidirectional Performance of Hotel Attributes through Online Reviews Based on Sentiment Analysis and Kano-IPA Model
In: Applied Sciences; Volume 12; Issue 2; Pages: 692 (2022)
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10
Analysis of Destination Images in the Emerging Ski Market: The Case Study in the Host City of the 2022 Beijing Winter Olympic Games
In: Sustainability; Volume 14; Issue 1; Pages: 555 (2022)
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11
Connecting Text Classification with Image Classification: A New Preprocessing Method for Implicit Sentiment Text Classification
In: Sensors; Volume 22; Issue 5; Pages: 1899 (2022)
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12
Short Text Aspect-Based Sentiment Analysis Based on CNN + BiGRU
In: Applied Sciences; Volume 12; Issue 5; Pages: 2707 (2022)
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13
Climate Change Sentiment Analysis Using Lexicon, Machine Learning and Hybrid Approaches
In: Sustainability; Volume 14; Issue 8; Pages: 4723 (2022)
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14
How We Failed in Context: A Text-Mining Approach to Understanding Hotel Service Failures
In: Sustainability; Volume 14; Issue 5; Pages: 2675 (2022)
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15
Deep Sentiment Analysis Using CNN-LSTM Architecture of English and Roman Urdu Text Shared in Social Media
In: Applied Sciences; Volume 12; Issue 5; Pages: 2694 (2022)
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16
How Do Chinese People View Cyberbullying? A Text Analysis Based on Social Media
In: International Journal of Environmental Research and Public Health; Volume 19; Issue 3; Pages: 1822 (2022)
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17
TBCOV: Two Billion Multilingual COVID-19 Tweets with Sentiment, Entity, Geo, and Gender Labels
In: Data; Volume 7; Issue 1; Pages: 8 (2022)
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18
Detecting Depression Signs on Social Media: A Systematic Literature Review
In: Healthcare; Volume 10; Issue 2; Pages: 291 (2022)
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19
A Novel Method of Generating Geospatial Intelligence from Social Media Posts of Political Leaders
In: Information; Volume 13; Issue 3; Pages: 120 (2022)
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20
Using social media and personality traits to assess software developers' emotions ...
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