71 Transportation Research Record: Journal of the Transportation Research Board, No. 2566, Transportation Research Board, Washington, D.C., 2016, pp. 71–82. DOI: 10.3141/2566-08 On the basis of data from online location-based social networks, the spa- tiality of destinations in the context of social networks and the influence of social networks on travelers’ destination choices are explored through check-in behavior. Analysis results show that social relationships play a role in travelers’ destination choices and that distance plays a strong role in social networks and in location choice. Comparison of check-in behavior of travelers in two social networks identified in two metro- politan areas (Chicago, Illinois, and New York City) and examination of interactions in the largest communities in each social network indicate that the denser a social network is, the greater the likelihood that trav- elers will be influenced by their friends in their choice of destination. However, travelers’ own experiences appear to exert greater influence on their decision making than do friendships. Massive technological changes have occurred in human communi- cation in recent years. The effect of social interaction and its influ- ence on travelers’ behavior have attracted researchers’ attention in the transportation field. Travelers learn about transportation-related changes through various information sources, including social com- munication. Not all travelers may be aware of the same information, and they likely perceive it differently depending on the source. The formation of activity (why travelers want to travel) and choice sets (such as destination choice) are influenced not only by external factors but also by personal perceptions, such as attitudes (1) and acceptance. Several studies indicate that opinion or judgment plays an important role in screening relevant alternatives for consideration in one’s choice set (2, 3). Modeling of activity and travel choices used in predicting demand is at the core of travel behavior research. In applying travel choice models to predict demand in practice, the assumption is generally made that the choice set is known and that travelers are aware of the attributes of the available alternatives. However, this is a simplifica- tion of behavioral processes, especially when choices with poten- tially large choice sets and attributes that are perceived differently by different travelers are modeled. Social media are becoming an integral part of life online and are permeating all other aspects of life. In this context, consideration of the opinion formation process (e.g., with regard to new destinations) and the role of information diffusion through social communication become important elements of the dynamics of the adoption pro- cess, such as adoption of new travel modes and new destinations. This process determines how travelers form their choice sets. Con- sideration of this dynamic process is desirable in modeling travel choices to improve the understanding, representation, and forecast- ing of demand. Similarly, awareness of an attribute and the relative weight placed on it are affected by social influences and information received. Research into travelers’ decision making seeks to understand and model social influences. Some studies have shown the potential of considering social network influences and have highlighted the importance of information diffusion in market adoption (for example, electrical cars’ market adoption in transportation). However, the data to capture such processes dynamically have been lacking. With the development of location-based social networking applications, travelers may share their current location information by logging into their online accounts; through the check-in process (check-ins), travelers release a message about their current locations. These appli- cations thus provide a new method for tracking and understanding travelers’ activity and travel behavior over space and time. This paper explores activity and location choice behavior as revealed through data from the online location-based social networking site Brightkite (http://en.wikipedia.org/wiki/Brightkite). This data set contains dynamic user check-in information with time stamps and coordinates, as well as an undirected social network of its users (“travelers,” used in this paper). The premise of this exploratory analysis is that social networks influence people’s resource allocation decisions in planning and executing activities and that the manifesta- tion of such decisions in their travel patterns can be observed in the data set at hand. Two main descriptive topics were investigated: first, the spatiality of the check-in data and locations and the activity behavior repre- sented by check-ins over time; and second, check-in behavior in rela- tion to the social network. Next, those destinations checked into by at least a pair of friends were grouped into 10 categories by using the Foursquare application programming interface (API). These ques- tions are examined in a comparative assessment of data from two large metropolitan areas in the United States: Chicago, Illinois, and New York City. BACKGROUND REVIEW An individual’s opinion about a particular subject can be developed from internal logic or from communication with others. As social creatures, travelers depend not only on their own experience but Use of Social Networking Data to Explore Activity and Destination Choice Behavior in Two Metropolitan Areas Ying Chen and Hani S. Mahmassani Y. Chen, Department of Civil and Environmental Engineering, Robert R. McCormick School of Engineering and Applied Science, and H. S. Mahmassani, Transporta- tion Center, Northwestern University, 600 Foster Street, Evanston, IL 60208. Corresponding author: H. S. Mahmassani, masmah@northwestern.edu.