Group: Big Hero 5Dennis Schmidt (A0145262L)

Jean Pierre Castillo (A0145472E)Liu Xu (A0047258Y)

Piyush Varanjani (A0105178H)Yin Xiao Ran(A0117980Y)

Social Network Analysis of Travel

Patterns of Tourists in Southeast

Asia

Agenda

• Introduction

• Methodology

• Findings

• Popularity

• Duration

• Patterns

• Seasons

• Limitations and Conclusion

Social Media influences travel decisions

Source: https://econsultancy.com

Motivation

Source: WTTC Travel & Tourism Economic Impact 2015

Hypothesis

“Based on blog data we are able to predict when and

WHERE

individuals will travel to in Southeast Asia”

Sources: www.tripadvisor.com, wikitravel.org, www.flightradar24.com, www.travelpod.com

Methodology - Data Source

Requirement: information about leisure trips with all stages of the trip

Methodology - Data Collection

Source: http://www.travelpod.com/travel-blog-entries/wanderinwonder/1/1426347504/tpod.html

Methodology - Data Collection

Source: http://www.travelpod.com/travel-blog-entries/wanderinwonder/1/1426347504/tpod.html

• Cleaning

• Country names

• City names Regions

• Compiling of matrices and tables

Methodology - Data Preprocessing

Methodology - Data Analysis and Visualization

Sources: www.r-project.org, nodexl.codeplex.com, products.office.com/en-us/excel

Data Collected

Data Findings - Popularity

Popularity: Median Days Duration of SEA Visits

0 5 10 15 20 25

Brunei (301)

Singapore (913)

East Timor (10)

Cambodia (808)

Laos (836)

Myanmar (279)

Malaysia (872)

Vietnam (778)

Thailand (1308)

Indonesia (566)

Philippines (254)

Popularity before and after 2010 (P<0.05)

Origin of trips before and after 2010 (P<0.05)

Seasons for traveling to SEA

Seasons for traveling to SEA

Limitations

• Data collection

• Data analysis

Summary (Key Findings)

Popular Route: Singapore – Malaysia – Thailand – Laos

Most important transit: Thailand

Longest duration: Philippines

Busy Seasons: December - February

Increased number of European Tourists since 2010