The Pittsburgh Experience

Made by Shruti Srikar · UNLISTED (SHOWN IN POOLS)

"Can social media help predict real estate trends?" A study conducted by MIT claims that analyzing social networks might be superior to cartographic tools to study urban networks. This might be truer than we think. How do we find out where the 'it' hangout locations are? How do we now which new club has opened? Before the advent of social media, this information was known and shared via word of mouth or newspaper adverts. Today, they are received via 'Check-ins' and 'Hashtags'. So the question is: Can we analyse social media content to predict the real estate quality of locations? Preliminary logic would point towards check-ins and photograph posting being the most popular way of sharing information about interesting locations. If we take this assumption forward, we can try and analyse these two streams of data by contrasting them against geographic locations and see if they form clusters around specific areas. City planning and design has come a long way from urbanist theories like 'Garden City' with their isolationist ideologies. The built environment is mimicking the internet in its search for interconnected-ness. The advent of new-age spaces like 'Live-Work' and 'Couch Surfing' have spawned entire industries. These spaces have been discovered in the intersection of non-traditional and yet surprisingly sequential information. Hence the potential of this project is to form the basis for a corollary: if we study the nature of locations, can we predict their use? In essence: Can we identify the potential of real estate using social media data?

Created: October 30th, 2017

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"Can social media help predict real estate trends?"

A study conducted by MIT claims that analyzing social networks might be superior to cartographic tools to study urban networks. This might be truer than we think. How do we find out where the 'it' hangout locations are? How do we now which new club has opened? Before the advent of social media, this information was known and shared via word of mouth or newspaper adverts. Today, they are received via 'Check-ins' and 'Hashtags'. So the question is: Can we analyse social media content to predict the real estate quality of locations?

Preliminary logic would point towards check-ins and photograph posting being the most popular way of sharing information about interesting locations. If we take this assumption forward, we can try and analyse these two streams of data by contrasting them against geographic locations and see if they form clusters around specific areas.

City planning and design has come a long way from urbanist theories like 'Garden City' with their isolationist ideologies. The built environment is mimicking the internet in its search for interconnected-ness. The advent of new-age spaces like 'Live-Work' and 'Couch Surfing' have spawned entire industries. These spaces have been discovered in the intersection of non-traditional and yet surprisingly sequential information. Hence the potential of this project is to form the basis for a corollary: if we study the nature of locations, can we predict their use? In essence: Can we identify the potential of real estate using social media data?