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Predicting the Success of Internet Social Welfare Crowdfunding Based on Text Information
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In: Applied Sciences; Volume 12; Issue 3; Pages: 1572 (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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Abstract:
Service failure is inevitable. Although empirical studies on the outcomes and processes of service failures have been conducted in the hotel industry, the findings need more exploration to understand how different segments perceive service failures and the associated emotions differently. This approach enables hotel managers to develop more effective strategies to prevent service failures and implement more specific service-recovery actions. For analysis, we obtained a nine-year (2010–2018) longitudinal dataset containing 1224 valid respondents with 73,622 words of textual content from a property affiliated with an international hotel brand in Canada. A series of text-mining and natural language processing (NLP) analyses, including frequency analysis and word cloud, sentiment analysis, word correlation, and TF–IDF analysis, were conducted to explore the information hidden in the massive amount of unstructured text data. The results revealed the similarities and differences between groups (i.e., men vs. women and leisure vs. business) in reporting service failures. We also carefully examined different meanings of words that emerged from the text-mining results to ensure a more comprehensive understanding of the guest experience.
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Keyword:
gender; group difference; purpose of stay; sentiment analysis; service failure; text-mining approach; TF–IDF analysis; word correlation; word frequency analysis
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URL: https://doi.org/10.3390/su14052675
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| 3 |
Tracing the Legitimacy of Artificial Intelligence – A Media Analysis, 1980-2020
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| 4 |
Dynamics of prescriptivism and lexical borrowings in Contemporary French
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Sentiment Analysis of Arabic Documents
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In: Natural Language Processing for Global and Local Business ; https://hal.archives-ouvertes.fr/hal-03124729 ; Fatih Pinarbasi; M. Nurdan Taskiran. Natural Language Processing for Global and Local Business, pp.307-331, 2021, 9781799842408. ⟨10.4018/978-1-7998-4240-8.ch013⟩ ; https://www.igi-global.com/ (2021)
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On Multi-domain Sentence Level Sentiment Analysis for Roman Urdu ...
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Developing Conversational Data and Detection of Conversational Humor in Telugu ...
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| 10 |
Not All Negatives are Equal: Label-Aware Contrastive Loss for Fine-grained Text Classification ...
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Open Aspect Target Sentiment Classification with Natural Language Prompts ...
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| 12 |
SYSML: StYlometry with Structure and Multitask Learning: Implications for Darknet Forum Migrant Analysis ...
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Connecting Attributions and QA Model Behavior on Realistic Counterfactuals ...
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| 14 |
Solving Aspect Category Sentiment Analysis as a Text Generation Task ...
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CLASSIC: Continual and Contrastive Learning of Aspect Sentiment Classification Tasks ...
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Improving Multimodal fusion via Mutual Dependency Maximisation ...
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Improving Federated Learning for Aspect-based Sentiment Analysis via Topic Memories ...
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| 19 |
How much coffee was consumed during EMNLP 2019? Fermi Problems: A New Reasoning Challenge for AI ...
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