  Location-sharing services were built upon people's desire to share their
activities and locations with others. By "checking-in" to a place, such as a
restaurant, a park, gym, or train station, people disclose where they are,
thereby providing valuable information about land use and utilization of
services in urban areas. This information may, in turn, be used to design
smarter, happier, more equitable cities. We use data from Foursquare
location-sharing service to identify areas within a major US metropolitan area
with many check-ins, i.e., areas that people like to use. We then use data from
the Twitter microblogging platform to analyze the properties of these areas.
Specifically, we have extracted a large corpus of geo-tagged messages, called
tweets, from a major metropolitan area and linked them US Census data through
their locations. This allows us to measure the sentiment expressed in tweets
that are posted from a specific area, and also use that area's demographic
properties in analysis. Our results reveal that areas with many check-ins are
different from other areas within the metropolitan region. In particular, these
areas have happier tweets, which also encourage people from other areas to
commute longer distances to these places. These findings shed light on human
mobility patterns, as well as how physical environment influences human
emotions.
