Predicting Mobility Patterns of Tourists Based on Social Media User's Profiles

Authors

  • M Vineela  Associate Professor, Department of CSE, Bhoj Reddy Engineering College for Women, Hyderabad, India
  • Vankudoth Sravani  Department of CSE, Bhoj Reddy Engineering College for Women, Hyderabad, India
  • Gudupally Sai Preethi  Department of CSE, Bhoj Reddy Engineering College for Women, Hyderabad, India

Keywords:

Social Media, Analytics, Domains, Recommendations, Posts.

Abstract

Social media is becoming a powerful data source for analytics in many domains. This is owing to an increase in quantity and quality of extractable data. Quantitatively, more people seem to find themselves as social media users. Quality wise, users tend to share more personal information and experiences which makes their profile more informative. Tourism is one of the main industries to utilize social media, as users posts useful information as they are traveling. The purpose of this research is to identify tourists from social media data and analyze their movement in the Netherlands. This study can be divided into three tasks. Firstly, the detection of tourists, followed by extracting their movement and lastly creating route recommendations for tourists.

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International Journal of Scientific Research in Science, Engineering and Technology

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Published

2023-06-30

Issue

Volume 10, Issue 3, May-June-2023

Section

Research Articles

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This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
M Vineela, Vankudoth Sravani, Gudupally Sai Preethi "Predicting Mobility Patterns of Tourists Based on Social Media User's Profiles" International Journal of Scientific Research in Science, Engineering and Technology (IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 10, Issue 3, pp.70-73, May-June-2023.