Classification of Remote Sensing Image Scenes Using Double Feature Extraction Hybrid Deep Learning Approach
Volume-3 | Issue-2
Light Weight CNN based Robust Image Watermarking Scheme for Security
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Principle of 6G Wireless Networks: Vision, Challenges and Applications
Volume-3 | Issue-4
PROGRESS AND PRECLUSION OF KNEE OSTEOARTHRITIS: A STUDY
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Is Internet becoming a Major Contributor for Global warming - The Online Carbon Footprint
Volume-2 | Issue-4
Augmented Reality in Education
Volume-2 | Issue-4
A Study on Various Task-Work Allocation Algorithms in Swarm Robotics
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IoT based Biotelemetry for Smart Health Care Monitoring System
Volume-2 | Issue-3
Tungsten DiSulphide FBG Sensor for Temperature Monitoring in Float Glass Manufacturing
Volume-2 | Issue-4
GUI based Industrial Monitoring and Control System
Volume-3 | Issue-2
AUTOMATION USING IOT IN GREENHOUSE ENVIRONMENT
Volume-1 | Issue-1
Principle of 6G Wireless Networks: Vision, Challenges and Applications
Volume-3 | Issue-4
Classification of Remote Sensing Image Scenes Using Double Feature Extraction Hybrid Deep Learning Approach
Volume-3 | Issue-2
Light Weight CNN based Robust Image Watermarking Scheme for Security
Volume-3 | Issue-2
VIRTUAL REALITY GAMING TECHNOLOGY FOR MENTAL STIMULATION AND THERAPY
Volume-1 | Issue-1
Design of Digital Image Watermarking Technique with Two Stage Vector Extraction in Transform Domain
Volume-3 | Issue-3
Analysis of Natural Language Processing in the FinTech Models of Mid-21st Century
Volume-4 | Issue-3
PROGRESS AND PRECLUSION OF KNEE OSTEOARTHRITIS: A STUDY
Volume-3 | Issue-3
Image Augmentation based on GAN deep learning approach with Textual Content Descriptors
Volume-3 | Issue-3
Comparative Analysis for Personality Prediction by Digital Footprints in Social Media
Volume-3 | Issue-2
Volume - 2 | Issue - 2 | june 2020
Published
27 May, 2020
Scrutinizing the emotions of customers and social media analytics are gaining popularity in the recent days. However, analysis of the emotions of visitors in theme parks are done on a lesser scale. In this paper, based on social media messages, the emotions of the visitors of a theme park is analyzed using geospatial as well as social media analytics convergence and visualization of cohesive places where expressions are gathered. Based on the Russell's Circumplex Model of Affect, the words and emotions are analyzed in around 50,000 tweets collected of which 20,400 tweets contained one or more such words. Analysis of exploratory spatial data based on GIS and analysis of text mining represents various emotion in each quadrant based on the tweets. The visitor emotions are associated to various topics and emotions of considerable spatial variations. Based on the significant clustering of emotions in each quadrant, the areas of riding attraction in the theme park are identified and displayed using this research approach. Based on the analysis and implications of this research work, it is possible to develop ways in which the pleasant emotions of the visitors can be evoked by practitioners.
KeywordsTheme Park Twitter Social media analytics Geospatial analytics Customer emotion
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