This is a presentation that I gave at the 2009 Travel and Tourism Research Association of Canada annual meeting.

1. Mining the Web
how user-generated content (UGC) can become a data
source for tourism research
Peter A. Johnson and Dr. Renee Sieber, McGill University
TTRA Canada Annual Conference, Guelph Ontario
Thursday October 15, 2009

2. Outline
• What is user generated content (UGC)?
• Examples of tourism-related UGC
• Tripadvisor study
• Challenges to UGC

3. What is UGC?

4. • User-generated content is:
• content made publicly available over
the Internet
• reflects creative effort
• created outside of professional
routines and practices (OECD, 2007)
http://www.oecd.org/dataoecd/57/14/38393115.pdf

9. Tripadvisor study
• A popular travel rating site
• Determine the range and nature of reviews
of Nova Scotia
• Start search queries using “nova scotia” and
“halifax nova scotia”
• Web scrape as many reviews as possible

10. Web Scraping
• Specialized computer software (robot or
spider)
• Automated extraction of website data
• Simulates “clicks” to drill down through a
web page
• Outputs thousands of records in hours

23. 5730 total reviews
5000
4064
3750
2500
1513
1250
153
0
Attractions Restaurants Accommodations
Reviews

24. Web Scraping Results

25. Survey vs. UGC
Survey UGC
Sample
Controlled Uncontrolled
Type
Question Open/Close Generally
Type Ended Open-Ended
Research
Investigative Exploratory
Approach

26. 77 Reviewed Locations

27. Accommodation Reviews

28. Attraction Reviews
activity

29. attractions
Restaurant Reviews

30. Total Destination Review Breakdown
Halifax
Annapolis Royal
Baddeck
Lunenburg
Dartmouth
Yarmouth
33%
Digby 40%
Other
3%
4%
4% 6%
5% 5%

31. Accommodation Review Ratings
One Star
Two Stars
Three Stars
Four Stars 7%
Five Stars 8%
10%
53%
22%

32. Attraction Review Ratings
One Star
Two Stars
Three Stars
Four Stars 7%
5%
Five Stars
9%
56%
23%

33. Restaurant Review Ratings
One Star
Two Stars
Three Stars
Four Stars 7%
Five Stars 8%
37%
17%
32%

34. Challenges with UGC
• Quality varies widely
• Vendetta/self promotion
• Legal grey area
• Generalizability?

35. The Future
• Data gathering and analysis:
• geolocate reviewers
• content analysis of reviews
• Secondary UGC: reviews of reviews
• Instant feedback: iPhone effect

36. Tripadvisor iPhone Application

37. Yelp iPhone Application

38. Take home points
• UGC is an emerging source of data for
tourism research
• Challenges:
• getting and using UGC
• how to use results at larger scales

39. Thank You!
Further Reading
• Girardin, F., Dal Fiore, F., Rattic, C, and Blatt, J. (2008) Leveraging explicitly
disclosed location information to understand tourist dynamics: a case study.
Journal of Location Based Services 2(1), 41-56.
• Goodchild, M.F. (2007). Citizens as Sensors: The World of Volunteered
Geography. Geo Journal 69, 211-221.
• Gorman S P, (2007), Is academia missing the boat for the Geo Web
revolution? A response to Harvey’s commentary. Environment and Planning
B: Planning and Design 34(6), 949 – 950
• Haklay, Muki, Alex Singleton and Chris Parker, (2008). Web Mapping 2.0: The
Neogeography of the GeoWeb. Geography Compass 2(6), 2011-2039.
Contact: peter.johnson2@mail.mcgill.ca