What drives the helpfulness of online reviews? A deep learning study of sentiment analysis, pictorial content and reviewer expertise for mature destinations
出版年份 2021 全文链接
标题
What drives the helpfulness of online reviews? A deep learning study of sentiment analysis, pictorial content and reviewer expertise for mature destinations
作者
关键词
Perceived helpfulness, Dual-processing theory, User-generated content, Sentiment analysis, Deep learning, Mature destinations
出版物
Journal of Destination Marketing & Management
Volume 20, Issue -, Pages 100570
出版商
Elsevier BV
发表日期
2021-03-08
DOI
10.1016/j.jdmm.2021.100570
参考文献
相关参考文献
注意:仅列出部分参考文献,下载原文获取全部文献信息。- Enriched Latent Dirichlet Allocation for Sentiment Analysis
- (2020) Amjad Osmani et al. EXPERT SYSTEMS
- Deep Learning for Aspect-Based Sentiment Analysis: A Comparative Review
- (2018) Hai Ha Do et al. EXPERT SYSTEMS WITH APPLICATIONS
- A review of natural language processing techniques for opinion mining systems
- (2017) Shiliang Sun et al. Information Fusion
- Application of social media analytics: a case of analyzing online hotel reviews
- (2017) Wu He et al. ONLINE INFORMATION REVIEW
- Deep Recurrent neural network vs. support vector machine for aspect-based sentiment analysis of Arabic hotels’ reviews
- (2017) Mohammad Al-Smadi et al. Journal of Computational Science
- Research Note: What Makes a Helpful Online Review? A Study of Customer Reviews on Amazon.com
- (2017) Mudambi et al. MIS QUARTERLY
- Arabic tweets sentiment analysis – a hybrid scheme
- (2016) Haifa K. Aldayel et al. JOURNAL OF INFORMATION SCIENCE
- A novel deterministic approach for aspect-based opinion mining in tourism products reviews
- (2014) Edison Marrese-Taylor et al. EXPERT SYSTEMS WITH APPLICATIONS
- Jumping NLP Curves: A Review of Natural Language Processing Research [Review Article]
- (2014) Erik Cambria et al. IEEE Computational Intelligence Magazine
- Techniques and applications for sentiment analysis
- (2013) Ronen Feldman COMMUNICATIONS OF THE ACM
- Helpfulness of Online Consumer Reviews: Readers' Objectives and Review Cues
- (2012) Hyunmi Baek et al. INTERNATIONAL JOURNAL OF ELECTRONIC COMMERCE
- Exploring determinants of voting for the “helpfulness” of online user reviews: A text mining approach
- (2010) Qing Cao et al. DECISION SUPPORT SYSTEMS
- Estimating the Helpfulness and Economic Impact of Product Reviews: Mining Text and Reviewer Characteristics
- (2010) A. Ghose et al. IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
- Sentiment strength detection in short informal text
- (2010) Mike Thelwall et al. JOURNAL OF THE AMERICAN SOCIETY FOR INFORMATION SCIENCE AND TECHNOLOGY
- eWOM overload and its effect on consumer behavioral intention depending on consumer involvement
- (2008) Do-Hyung Park et al. Electronic Commerce Research and Applications
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