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Developing a web application to understand the tourist dynamics using social media data (Softcopy is also available)

By: Contributor(s): Material type: TextTextPublication details: 2021Description: xi,45pDDC classification:
  • MG TH-0215 GAD
Contents:
Contents Certificate of original authorship i Certificate of Dissertation Advisor’s consent iii Acknowledgments v Abstract vii List of figures ix List of tables xi 1 INTRODUCTION 1 2 RESEARCH PROPOSAL 4 2.1 Aim 4 2.2 Objectives 4 2.3 Data Used 4 3 Literature Review 5 3.1 What is Crowdsourced Data? 5 3.1.1 Available Data Sources 5 3.1.2 Comparison Between Data Providers 6 3.2 Who is a Tourist? 7 3.2.1 Differentiate Tourist and Resident in The Crowdsourced Data. ..7 3.3 Demographic and Socioeconomic Biases of Crowdsourced Data 8 4 Methodology 10 4.1 Comparing Data Sources 10 4.1.1 Standard Access API 11 4.1.2 Academic Research API 12 4.1.3 Application Development 13 4.2 Data Acquisition 17 4.3 Data Processing 17 4.3.1 Sentiment Analysis 19 4.4 Spatial Analysis 20 5 Study Area 22 5.1 Selection Criteria 22 6 Data Extraction and Processing 26 6.1 Data Acquisition 26 6.2 Data Cleaning 27 7 Results and Discussions 28 7.1.1 Goa 28 7.1.2 Miami 32 7.2 Observations 35 7.3 Dashboard For Monitoring 35 7.4 Applications 36 7.5 Conclusion 37 7.6 Limitations 37 References xxxix Appendix 1: Code Used To Building Application For Downloading Tweets xli Appendix 2: Geocoding Location Attribute To Get Coordinates 44
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Thesis CEPT Library Faculty of Technology MG TH-0215 GAD Not For Loan 023715
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Contents
Certificate of original authorship i
Certificate of Dissertation Advisor’s consent iii
Acknowledgments v
Abstract vii
List of figures ix
List of tables xi
1 INTRODUCTION 1
2 RESEARCH PROPOSAL 4
2.1 Aim 4
2.2 Objectives 4
2.3 Data Used 4
3 Literature Review 5
3.1 What is Crowdsourced Data? 5
3.1.1 Available Data Sources 5
3.1.2 Comparison Between Data Providers 6
3.2 Who is a Tourist? 7
3.2.1 Differentiate Tourist and Resident in The Crowdsourced Data. ..7
3.3 Demographic and Socioeconomic Biases of Crowdsourced Data 8
4 Methodology 10
4.1 Comparing Data Sources 10
4.1.1 Standard Access API 11
4.1.2 Academic Research API 12
4.1.3 Application Development 13
4.2 Data Acquisition 17
4.3 Data Processing 17

4.3.1 Sentiment Analysis 19
4.4 Spatial Analysis 20
5 Study Area 22
5.1 Selection Criteria 22
6 Data Extraction and Processing 26
6.1 Data Acquisition 26
6.2 Data Cleaning 27
7 Results and Discussions 28
7.1.1 Goa 28
7.1.2 Miami 32
7.2 Observations 35
7.3 Dashboard For Monitoring 35
7.4 Applications 36
7.5 Conclusion 37
7.6 Limitations 37
References xxxix
Appendix 1: Code Used To Building Application For Downloading Tweets xli
Appendix 2: Geocoding Location Attribute To Get Coordinates 44

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