The Digital Footprint of Urban Tourism

Inspiration

Wanted to create a better way to understand the cultural aspect of a location.

What it does

Our project aims to analyze tourist preferences across eight major cities by performing sentiment analysis on reviewing platforms. Using NLP, we explored how much tourists enjoyed their visits at their destinations’ points of interest, restaurants, attractions, and accommodations, and learn what experiences helped form their opinions location-to-location.

How we built it

Using R, JMP, google spreadsheets, and Canva

Challenges we ran into

Processing took to long and API didn't have all data available as was on their website.

1. Language translation took too long
2. API data was messed up and had to change directions ## Accomplishments that we're proud of
3. Our first NLP
4. My first time using an API ## What we learned
5. API data retrieval
6. Lots of NLP information
7. Lots of helpful R functions ## What's next for The Digital Footprint of Urban Tourism
8. Consider how translation affects accuracy
9. More preprocessing of data including adding languages

Built With

• canva
• google-spreadsheets
• jmp
• r
• tourpedia