Consumer recommendation prediction in online reviews using Cuckoo optimized machine learning models

[1]  Albert A. Barreda,et al.  The impact of social media activities on brand image and emotional attachment , 2020 .

[2]  Eric Gilbert,et al.  VADER: A Parsimonious Rule-Based Model for Sentiment Analysis of Social Media Text , 2014, ICWSM.

[3]  Ravikiran Vatrapu,et al.  Analysing Customer Engagement of Turkish Airlines Using Big Social Data , 2018, 2018 IEEE International Congress on Big Data (BigData Congress).

[4]  Claudia Sevilla-Sevilla,et al.  Progress in information technology and tourism management: 30 years on and 20 years after the internet - Revisiting Buhalis & Law's landmark study about eTourism , 2018, Tourism Management.

[5]  Lobel Trong Thuy Tran.  Online reviews and purchase intention: A cosmopolitanism perspective , 2020 .

[6]  Swagato Chatterjee,et al.  Explaining customer ratings and recommendations by combining qualitative and quantitative user generated contents , 2019, Decis. Support Syst..

[7]  Nadeem Javaid,et al.  A survey on hyperparameters optimization algorithms of forecasting models in smart grid , 2020 .

[8]  Anand Kumar,et al.  Sentiment Classification System of Twitter Data for US Airline Service Analysis , 2018, 2018 IEEE 42nd Annual Computer Software and Applications Conference (COMPSAC).

[9]  Paulo Rita,et al.  Stripping customers' feedback on hotels through data mining: the case of Las Vegas Strip , 2017 .

[10]  Ahmad Jusoh,et al.  Online information bombardment! How does eWOM on social media lead to consumer purchase intentions? , 2020, Int. J. Grid Util. Comput..

[11]  Amit V. Deokar,et al.  Disentangling consumer recommendations: Explaining and predicting airline recommendations based on online reviews , 2018, Decis. Support Syst..

[12]  Panchapakesan Padma,et al.  Guest satisfaction & dissatisfaction in luxury hotels: An application of big data , 2020 .

[13]  Emmanuel Mogaji,et al.  Insights into Online Reviews of Hotel Service Attributes: A Cross-National Study of Selected Countries in Africa , 2018, ENTER.

[14]  Tianqi Chen,et al.  XGBoost: A Scalable Tree Boosting System , 2016, KDD.

[15]  Leandro dos Santos Coelho,et al.  Coyote Optimization Algorithm: A New Metaheuristic for Global Optimization Problems , 2018, 2018 IEEE Congress on Evolutionary Computation (CEC).

[16]  Weiguo Fan,et al.  Understanding the determinants of online review helpfulness: A meta-analytic investigation , 2017, Decis. Support Syst..

[17]  Z. Schwartz,et al.  What can big data and text analytics tell us about hotel guest experience and satisfaction , 2015 .

[18]  Zheng Xiang,et al.  A comparative analysis of major online review platforms: Implications for social media analytics in hospitality and tourism , 2017 .

[19]  Ozgur Turetken,et al.  A comparative assessment of sentiment analysis and star ratings for consumer reviews , 2020, Int. J. Inf. Manag..

[20]  Neelu Khare,et al.  Sentimental Analysis for Airline Twitter data , 2017 .

[21]  Tie-Yan Liu,et al.  LightGBM: A Highly Efficient Gradient Boosting Decision Tree , 2017, NIPS.

[22]  Riccardo Poli,et al.  Particle swarm optimization , 1995, Swarm Intelligence.

[23]  Gautam Srivastava,et al.  Where's @Waldo?: Finding Users on Twitter , 2019, ICAISC.

[24]  Xin-She Yang,et al.  Engineering optimisation by cuckoo search , 2010, Int. J. Math. Model. Numer. Optimisation.