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PROTECT: A Pipeline for Propaganda Detection and Classification
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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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#Bittersweet: Positive, negative, and mixed emotions in twitter posts ...
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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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MULDASA: Multifactor Lexical Sentiment Analysis of Social-Media Content in Nonstandard Arabic Social Media
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In: Applied Sciences; Volume 12; Issue 8; Pages: 3806 (2022)
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Lexicon-Based vs. Bert-Based Sentiment Analysis: A Comparative Study in Italian
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In: Electronics; Volume 11; Issue 3; Pages: 374 (2022)
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A New Ontology-Based Method for Arabic Sentiment Analysis
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In: Big Data and Cognitive Computing; Volume 6; Issue 2; Pages: 48 (2022)
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COVID-19 Vaccination-Related Sentiments Analysis: A Case Study Using Worldwide Twitter Dataset
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In: Healthcare; Volume 10; Issue 3; Pages: 411 (2022)
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Exploring Bidirectional Performance of Hotel Attributes through Online Reviews Based on Sentiment Analysis and Kano-IPA Model
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In: Applied Sciences; Volume 12; Issue 2; Pages: 692 (2022)
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Analysis of Destination Images in the Emerging Ski Market: The Case Study in the Host City of the 2022 Beijing Winter Olympic Games
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In: Sustainability; Volume 14; Issue 1; Pages: 555 (2022)
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Abstract:
This study aims to propose a text mining framework suitable for destination image (DI) research based on UGC (User Generated Content), which combines the LDA (Latent Dirichlet Allocation) model and sentiment analysis method based on custom rules and lexicon to identify and analyze the DI in the emerging ski market. The ski resorts in the host city of the 2022 Winter Olympic Games are selected as a case study. The findings reveal that (1) 9 image attributes, out of which two image attributes have not been identified before in winter destination studies, namely beginner suitability and ticketing service. (2) In the past seven snow seasons, the negative sentiment of tourists has shown a continuous downward trend. The positive sentiment has exhibited a slow upward trend. (3) For tourists from destination countries affected by the Winter Olympic Games, the destination image will be improved when the destination meets their expectations. When the destination cannot meet their expectations, the tourists still believe that the holding of the Winter Olympic will enhance the destination’s situation. The theoretical and managerial implications of these findings are discussed.
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Keyword:
destination image; LDA model; mega-sport events; sentiment analysis; ski destination
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URL: https://doi.org/10.3390/su14010555
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Connecting Text Classification with Image Classification: A New Preprocessing Method for Implicit Sentiment Text Classification
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In: Sensors; Volume 22; Issue 5; Pages: 1899 (2022)
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Short Text Aspect-Based Sentiment Analysis Based on CNN + BiGRU
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In: Applied Sciences; Volume 12; Issue 5; Pages: 2707 (2022)
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Climate Change Sentiment Analysis Using Lexicon, Machine Learning and Hybrid Approaches
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In: Sustainability; Volume 14; Issue 8; Pages: 4723 (2022)
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How We Failed in Context: A Text-Mining Approach to Understanding Hotel Service Failures
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In: Sustainability; Volume 14; Issue 5; Pages: 2675 (2022)
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Deep Sentiment Analysis Using CNN-LSTM Architecture of English and Roman Urdu Text Shared in Social Media
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In: Applied Sciences; Volume 12; Issue 5; Pages: 2694 (2022)
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How Do Chinese People View Cyberbullying? A Text Analysis Based on Social Media
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In: International Journal of Environmental Research and Public Health; Volume 19; Issue 3; Pages: 1822 (2022)
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TBCOV: Two Billion Multilingual COVID-19 Tweets with Sentiment, Entity, Geo, and Gender Labels
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In: Data; Volume 7; Issue 1; Pages: 8 (2022)
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Detecting Depression Signs on Social Media: A Systematic Literature Review
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In: Healthcare; Volume 10; Issue 2; Pages: 291 (2022)
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A Novel Method of Generating Geospatial Intelligence from Social Media Posts of Political Leaders
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In: Information; Volume 13; Issue 3; Pages: 120 (2022)
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Using social media and personality traits to assess software developers' emotions ...
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