Using Yelp to Find Romance in the City: A Case of Restaurants in Four Cities

Findings: There’s a certifiable difference in urban hot spots and demand depending on couples’ relationship stage. Key factors for selecting a romantic date spot include ambiance (cozy & classy atmosphere), high prices, and downtown locations. Couples with families (children) tend to prefer less expensive restaurants, with great service and (probably) accessible parking. Special occasion locations are concentrated in downtown areas, especially for Las Vegas and Pittsburgh, but are more distributed for sprawling cities like Phoenix and Charlotte.

Method: Natural Language Processing of Yelp reviews to scan for correlations of certain keywords, cross-referenced with locations of restaurants.

Good For: If you are opening a bar or restaurant and would like to influence the potential clientele, or if you would like to glean insight into the romantic life cycle.

Integrating Social Network Data into GISystems

Findings: Considering where people are when we examine social networks can help us decide anything from where to advertise to where to build a hospital.

Methods: Describe why modeling socialization in geographic space is essential for understanding human behavior. Outline best practices and techniques for embedding SN in GISystems. Explore case studies in Bolivia, China, Côte d’Ivoire, Singapore, the United Kingdom, and the United States.

Good For: If you want to understand time importance of adding GIS to social network analysis. Some examples: considering how diseases spread (useful for CEID), how likely a person is to have a place to go in the event of a natural disaster, or If you’re deciding where to open a brick and mortar business that appeals to certain social networks.

Hidden Style in the City: An Analysis of Geolocated Airbnb Rental Images in Ten Major Cities

Findings: Photos in international AirBNB listings are starting to have more in common as globalization homogenizes the wold. However, variation between listings in neighborhoods is rising.

Method: 500,000 images downloaded from AirBNB were rated by Mechanical Turk participants.

Good For: If you want to learn how citizens of different locales decorate their homes differently, or to identify favorable interiors to global customers. Useful for AirBNB hosts or hotel marketers seeking a competitive advantage.

The Rise of Partisanship and Super-Cooperators in the U.S. House of Representatives

Findings: Analysis of voting records show proof that US congresspeople are more partisan than ever. Thankfully, Texan Democrats and Northeastern Republicans  are ‘supercooperators’ who have stepped across party lines.

Methods: Charting frequency distributions of roll call vote data from the U.S. House of Representatives from 1949 to 2012 to display cross-party voting patterns.

Good for: If you are interested in the gradual polarization of American congress people, or would like to learn which congress people cooperate outside of their party.