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Psychological Well-Being of Left-Behind Children in China: Text Mining of the Social Media Website Zhihu.
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In: International journal of environmental research and public health, vol 19, iss 4 (2022)
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| 2 |
Mining an English-Chinese parallel Dataset of Financial News
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In: Journal of Open Humanities Data; Vol 8 (2022); 9 ; 2059-481X (2022)
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| 3 |
“Thou Shalt Not Take the Lord’s Name in Vain”: A Methodological Proposal to Identify Religious Hate Content on Digital Social Networks
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In: International Journal of Communication; Vol 16 (2022); 22 ; 1932-8036 (2022)
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| 4 |
WS16: Italian heritage: Using corpus data to map phonological patterns in Brazilian Veneto ...
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| 5 |
LASSO Regression Modeling on Prediction of Medical Terms among Seafarers’ Health Documents Using Tidy Text Mining
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In: Bioengineering; Volume 9; Issue 3; Pages: 124 (2022)
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| 6 |
A Corpus-Based Sentence Classifier for Entity–Relationship Modelling
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In: Electronics; Volume 11; Issue 6; Pages: 889 (2022)
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| 7 |
Text Mining from Free Unstructured Text: An Experiment of Time Series Retrieval for Volcano Monitoring
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In: Applied Sciences; Volume 12; Issue 7; Pages: 3503 (2022)
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| 8 |
A Novel Approach for Semantic Extractive Text Summarization
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In: Applied Sciences; Volume 12; Issue 9; Pages: 4479 (2022)
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| 9 |
Using Conceptual Recurrence and Consistency Metrics for Topic Segmentation in Debate
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In: Applied Sciences; Volume 12; Issue 6; Pages: 2952 (2022)
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| 10 |
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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| 11 |
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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| 12 |
Psychological Well-Being of Left-Behind Children in China: Text Mining of the Social Media Website Zhihu
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In: International Journal of Environmental Research and Public Health; Volume 19; Issue 4; Pages: 2127 (2022)
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| 13 |
Study of the Yahoo-Yahoo Hash-Tag Tweets Using Sentiment Analysis and Opinion Mining Algorithms
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In: Information; Volume 13; Issue 3; Pages: 152 (2022)
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| 14 |
Preparing Legal Documents for NLP Analysis: Improving the Classification of Text Elements by Using Page Features
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| 17 |
Corona-Rechtsprechung des Bundesverfassungsgerichts (BVerfG-Corona) ...
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| 18 |
[R] Source Code der Corona-Rechtsprechung des Bundesverfassungsgerichts (BVerfG-Corona-Source) ...
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[R] Source Code der Corona-Rechtsprechung des Bundesverfassungsgerichts (BVerfG-Corona-Source) ...
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Corona-Rechtsprechung des Bundesverfassungsgerichts (BVerfG-Corona) ...
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