Mining the Web: How user-generated content can become a data source for tourism research
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This is a presentation that I gave at the 2009 Travel and Tourism Research Association of Canada annual meeting.
Mining the Web: How user-generated content can become a data source for tourism research
- 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 re鍖ects 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
- 25. Survey vs. UGC Survey UGC Sample Controlled Uncontrolled Type Question Open/Close Generally Type Ended Open-Ended Research Investigative Exploratory Approach
- 28. Attraction Reviews activity
- 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
- 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 Harveys 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
Editor's Notes
- #3: Outline, what to expect from the next 15 minutes