Monitoring of user‐generated reviews via a sequential reverse joint sentiment‐topic model

[1]  Alice H. Oh,et al.  Aspect and sentiment unification model for online review analysis , 2011, WSDM '11.

[2]  M. Marcucci MONITORING MULTINOMIAL PROCESSES , 1985 .

[3]  X. Zhang,et al.  Impact of Online Consumer Reviews on Sales: The Moderating Role of Product and Consumer Characteristics , 2010 .

[4]  Yang Yu,et al.  User-Generated Content : Using Sentiment Analysis Technique to Study Hotel Service Quality , 2012 .

[5]  Victor R. Prybutok,et al.  Quantitative quality control from qualitative data: control charts with latent semantic analysis , 2015 .

[6]  Michael I. Jordan,et al.  Hierarchical Dirichlet Processes , 2006 .

[7]  Shuchuan Lo,et al.  Web service quality control based on text mining using support vector machine , 2008, Expert Syst. Appl..

[8]  Yang Yu,et al.  Exploring the Impact of Social Media on Hotel Service Performance , 2016 .

[9]  Yasushi Sakurai,et al.  Online multiscale dynamic topic models , 2010, KDD.

[10]  Douglas C. Montgomery,et al.  Some Current Directions in the Theory and Application of Statistical Process Monitoring , 2014 .

[11]  Mohamed M. Mostafa,et al.  More than words: Social networks' text mining for consumer brand sentiments , 2013, Expert Syst. Appl..

[12]  Armin Shmilovici,et al.  Context-Based Statistical Process Control , 2003, Technometrics.

[13]  Yulan He,et al.  Joint sentiment/topic model for sentiment analysis , 2009, CIKM.

[14]  T. Landauer,et al.  Indexing by Latent Semantic Analysis , 1990 .

[15]  David M. Pennock,et al.  Mining the peanut gallery: opinion extraction and semantic classification of product reviews , 2003, WWW '03.

[16]  Jon Atle Gulla,et al.  RETRACTED ARTICLE: A joint model for analyzing topic and sentiment dynamics from large-scale online news , 2017, World Wide Web.

[17]  Wei Gao,et al.  Dynamic joint sentiment-topic model , 2013, ACM Trans. Intell. Syst. Technol..

[18]  Pranjal Gupta,et al.  How e-WOM recommendations influence product consideration and quality of choice: A motivation to process information perspective , 2010 .

[19]  Jianhua Lin,et al.  Divergence measures based on the Shannon entropy , 1991, IEEE Trans. Inf. Theory.

[20]  Stefan M. Rüger,et al.  Weakly Supervised Joint Sentiment-Topic Detection from Text , 2012, IEEE Transactions on Knowledge and Data Engineering.

[21]  Andrew McCallum,et al.  Topics over time: a non-Markov continuous-time model of topical trends , 2006, KDD '06.

[22]  Bing Liu,et al.  Mining and summarizing customer reviews , 2004, KDD.

[23]  Ingoo Han,et al.  The Effect of On-Line Consumer Reviews on Consumer Purchasing Intention: The Moderating Role of Involvement , 2007, Int. J. Electron. Commer..

[24]  Mark Steyvers,et al.  Finding scientific topics , 2004, Proceedings of the National Academy of Sciences of the United States of America.

[25]  Sabine Loudcher,et al.  A Joint Model for Topic-Sentiment Evolution over Time , 2014, 2014 IEEE International Conference on Data Mining.

[26]  John D. Lafferty,et al.  Dynamic topic models , 2006, ICML.

[27]  Lucie Sperkova,et al.  How to Measure Quality of Service Using Unstructured Data Analysis: A General Method Design , 2015 .

[28]  Hui Li,et al.  Chinese word segmentation and its effect on information retrieval , 2004, Inf. Process. Manag..

[29]  David B. Dunson,et al.  Probabilistic topic models , 2011, KDD '11 Tutorials.