Business Mafia Proposal

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PROPOSAL

POSTER

APPLICATION

RESEARCH PAPER

Project Objective

Through our project, we aim to:

1. Derive individual walking distance between various key attractions and Airbnb listings in Downtown Seattle
2. Analyse the spatial relationships between various key locations and Airbnb listings in Downtown Seattle to determine if the listing's location to key places affect its listing price
3. Through the use of Local Geographical Weighted Regression (GWR) Model, we hope to help Airbnb owner(s) determine the better pricing for their listing(s).

Our Datasets

Data	Source	Data Description	Source URL	Data Type
Seattle Open Airbnb Data	Inside Airbnb	Information on all Airbnb listings found within Downtown Seattle, last scrapped on 15 November 2018	http://insideairbnb.com/get-the-data.html	CSV File
Common Place Name (CPN)	City of Seattle Open Data Portal	A point feature class showing common place names and corresponding locations in Seattle.	https://data.seattle.gov/Land-Base/Common-Place-Names-CPN-/599c-9ddc	CSV File
City Clerk Neighbourhoods	Seattle.gov	Displays the 20 Large City Clerk neighborhood boundaries, along with their smaller neighborhood boundaries.	https://data.seattle.gov/dataset/City-Clerk-Neighborhoods/926y-cwh9	SHP File
Zoning (Generalized)	Seattle GIS Open Data	A polygon feature class showing zoning areas. It also provides information on the type of zoning such as Downtown, Major Institutions, Manufacturing/Industrial, Multifamily, Neighbourhood/Commercial, Residential/Commercial and Single Family.	https://data-seattlecitygis.opendata.arcgis.com/datasets/a85e74dac41d43cab5a8b840558c4d77_3?page=15	SHP File

Literature Review

Sources:

1. https://towardsdatascience.com/airbnb-rental-listings-dataset-mining-f972ed08ddec
2. https://www.airbnbcitizen.com/the-airbnb-community-in-seattle/

Project Storyboard