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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)
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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)
Abstract: This paper describes the construction a short-text aspect-based sentiment analysis method based on Convolutional Neural Network (CNN) and Bidirectional Gating Recurrent Unit (BiGRU). The hybrid model can fully extract text features, solve the problem of long-distance dependence on the sequence, and improve the reliability of training. This article reports empirical research conducted on the basis of literature research. The first step was to obtain the dataset and perform preprocessing, after which scikit-learn was used to perform TF-IDF calculations to obtain the feature word vector weight, obtain the aspect-level feature ontology words of the evaluated text, and manually mark the ontology of the reviewed text and the corresponding sentiment analysis polarity. In the sentiment analysis section, a hybrid model based on CNN and BiGRU (CNN + BiGRU) was constructed, which uses corpus sentences and feature words as the vector input and predicts the emotional polarity. The experimental results prove that the classification accuracy of the improved CNN + BiGRU model was improved by 12.12%, 8.37%, and 4.46% compared with the Convolutional Neural Network model (CNN), Long-Short Term Memory model (LSTM), and Convolutional Neural Network (C-LSTM) model.
Keyword: aspect-level; bidirectional gating recurrent unit (BiGRU); convolutional neural network (CNN); sentiment analysis; short text
URL: https://doi.org/10.3390/app12052707
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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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