Social Spatial Network Tools in R

Introduction to Social Spatial Networks (SSNs):

Researchers in the social sciences have used social networks/sociograms to visualize the connections and relationships of people in a community since the 1930s (Andris & Sarkar, 2022). However, these networks are aspatial and do not integrate geospatial information about individuals to analyze and explain these relationships (and lack of relationships). Based on Tobler's First Law (Tobler, 1970) "everything is related to everything else, but near things are more related than distant things", it could be theorized that people who live/work near one another are more likely to have similar characteristics and to interact more frequently, but this cannot be confirmed using sociograms alone as they lack a spatial component. Networking and graph theory from the field of Computer Science is also tangentially related to social-spatial networking, but is generally focused on the abstract or theoretical connections between nodes, rather than simulations of real world phenomena (Bondy, 1982). Finally, network analysis also exists within traditional GIS fields and discussions, though this generally based on the distribution of goods and services along pre-defined road/stream networks, rather than a focus on the relationship/connection outside of pre-defined networks (Andris & Sarkar, 2022). Social-Spatial Networks are an integration of the ideas found in these different fields to analyze and document social relationships/connections between individuals situated within their geospatial locations to better understand how connections are formed and maintained.

Term Definitions

In Social-Spatial Network analysis, Nodes are specific geolocated points representing people, businesses, or other points of interest. All nodes need at minimum two datapoints, a unique name/ID to reference the node and some form of location information that can be converted into a (lat, long) pair. Nodes may also contain auxiliary information about the point being represented, such as demographic information on a participant, or classifications of a business type.

Edges represent a social connection between two nodes and are at minimum composed of a pair of names/IDs that are found in the node list, all names within the edge list must be found exactly in the node list, or the program may crash. Similarly to nodes, edges can also contain additional information about a connection, such as a strength value or a type classification that may be used to weight the algorithms.

Buidling a Dataset for a Social-Spatial Network:

Data must be composed of at minimum one .csv file with a list of names for each node as well as their locations, as well as one .csv file that holds pairs of node names indicating connections/edges between the two of them. Either the node or the edge file may also include additional data collected such as demographic or organizational information about the nodes, or information on the type of relationship for each node.

- Essential & Additional Information - Define Your Study Participants - Geolocation of Written Descriptions - Relationship Definitions & Mapping

References

Andris, C., & Sarkar, D. (2022). Social networks in space. Chapters, 400-415.

Bondy, J. A. (1982). Graph theory with applications.

Tobler, Waldo R. 1970. “A Computer Movie Simulating Urban Growth in the Detroit Region.” Economic Geography (Supplement: Proceedings, International Geographical Union. Commission on Quantitative Methods), 46: 234–240. DOI:10.2307/143141.