Can Tourist Attractions Boost Other Activities Around? A Data Analysis through Social Networks

Area of Science:

• Tourism studies
• Data science
• Urban planning

Background:

• Effective destination promotion relies on understanding visitor travel patterns, preferences, and profiles.
• Tourism data is crucial for statistical records and informed business decisions in the tourism sector.

Purpose of the Study:

• To analyze tourist behavior by examining the relationship between visits to top city attractions and restaurant patronage.
• To differentiate between tourists and locals using social network data.
• To provide insights for destination marketers.

Main Methods:

• Utilized social network data (tweets) and an open-access map service to geolocate user-generated content.
• Developed a pattern recognition technique to distinguish visitors from locals based on social media activity.
• Applied the methodology to analyze tourist behavior in Valencia, Spain, and Berlin, Germany.

Main Results:

• In Valencia, highly frequented restaurants were predominantly located near major tourist attractions.
• In contrast, Berlin's most popular restaurants were generally situated further from prominent tourist sites.
• The study successfully differentiated between visitor and local behavior patterns.

Conclusions:

• Tourist dining preferences exhibit significant geographical variation relative to attractions, differing between cities like Valencia and Berlin.
• Findings offer valuable, data-driven insights for tailoring destination marketing strategies.
• Understanding these nuanced patterns can enhance the effectiveness of tourism promotion efforts.