Tourism Websites

Bansal, Sparsh; Agarwal, Aditya

Tourism Websites

dc.contributor.author	Bansal, Sparsh	en
dc.contributor.author	Agarwal, Aditya	en
dc.date.accessioned	2021-12-16T01:53:12Z	en
dc.date.available	2021-12-16T01:53:12Z	en
dc.date.issued	2021-12-15	en
dc.description.abstract	The project is about analyzing and visualizing metadata of tourism websites of three states (Virginia, Colorado, and California) from 1998 to 2018. Each state in the United States has its own state website that is used as a resource to attract new tourists to this location. Each of these sites usually includes great attractions in this state, travel tips and facts about this place, blog posts, and reviews from other people who have been there. Suggestions regarding what might attract potential customers could emerge from examining past tourism websites and looking for any patterns amongst them that would determine what worked and what didn’t. These patterns can then be used to determine what was successful and use that information to make better-informed decisions on the future of state tourism. We will use the historical analysis of past government tourism websites to further support research on content and traffic trends on these websites. The various iterations of each state's tourism website are saved as snapshots in the Internet Archive. Our team was given the Parquet files having the snapshots of data containing the information recording tourism for California, Colorado, and Virginia dating back to 1998. We used a combination of Python’s Pandas library and Beautiful Soup to examine and extract relevant pieces of data from the given Parquet files. This data was scraped to extract the meta tags used for the website as of that date. With this data, we plotted the presence of all the variations on a state's tourism website in chronological order. This made it possible for us to analyze the addition and removal of keywords and to see other changes that were made like using phrases, capitalizations, keywords in languages other than English, and updating of keywords based on internet trends. This led us to conclude that meta tags play a very important role in a website's search engine ranking and a lot of analysis needs to be done keeping in mind the primary user base of the website.	en
dc.description.notes	The TourismWebsitesReport files contain the full report that demonstrates the solution approach, design, implementation of the work completed, brief manual page to aid the use of the application, lessons learned, and possible future work. The TourismWebsitesReport files have been uploaded in both .docx and .pdf versions. The TourismWebsitesPresentation file contains the slides that give a brief overview of the project including the timeline and the implementation details. They explain the collaborative approach taken by our team to produce the desired outcome. The TourismWebsitesPresentation files have been uploaded in both .pptx and .pdf versions. The files relating to the codebase to the application have been uploaded as TourismWebsitesCode.zip; it contains all of our Python scripts used to run the code. The results have been uploaded as TourismWebsitesResults.zip which contains all of the final JSON files and the graphs for each of the states.	en
dc.identifier.uri	http://hdl.handle.net/10919/107069	en
dc.language.iso	en_US	en
dc.publisher	Virginia Tech	en
dc.rights	Attribution-NoDerivatives 4.0 International	en
dc.rights.uri	http://creativecommons.org/licenses/by-nd/4.0/	en
dc.subject	tourism	en
dc.subject	tourism websites	en
dc.subject	Virginia tourism	en
dc.subject	Colorado tourism	en
dc.subject	California tourism	en
dc.subject	keyword analysis	en
dc.subject	meta tags	en
dc.subject	plotly.dash	en
dc.title	Tourism Websites	en
dc.type	Presentation	en
dc.type	Report	en
dc.type	Other	en