Geovisualization of Social Media

Figure 1: Map Mashup of Twitter data, where eachdot
represents a tweet, the text corresponds to the selected
 tweet marked with a star

In the recently released "The International Encyclopedia of Geography: People, the Earth, Environment, and Technology" we were asked to write a brief entry entitled "geovisualization of social media". Below is a summary of  our chapter:

The proliferation of social media over the last decade is presenting substantial computational challenges associated with the management, processing, analysis and visualization of the corresponding massive volumes of data. Furthermore, this new form of information also imposes new-found challenges upon the geographical community due to the unique nature of its content, as analyzing such data calls for a hybrid mix of spatial and social analysis. The spatial content of social media comprises primarily coordinates from which the contributions originate, or references to specific locations. At the same time, these data have a strong social component, as they can reveal the underlying social structure of the user community through manifestations of their interactions. Analyzing both the spatial and social content of social media feeds is referred to as geosocial analysis. Within this entry we explore the geovisualization opportunities and challenges that are emerging as social media are becoming the subject of study of the geographical community.

In more detail, we start off discussing how the geographic content of social media feeds represents a new type of geographic information. It transcends the early definitions of crowdsourcing or volunteered geographic information as it is not the product of a process through which citizens explicitly and purposefully contribute geographic information to update or expand geographic databases. Instead, the type of geographic information that can be harvested from social media feeds can be referred to as Ambient Geographic Information; it is embedded in the content of these feeds, often across the content of numerous entries rather than within a single one, and has to be somehow extracted. Nevertheless, it is of great importance as it communicates instantaneously information about emerging issues. At the same time, it provides an unparalleled view of the complex social networking and cultural dynamics within a society, and captures the temporal evolution of the human landscape.

In many cases, the geovisualization of social media feeds predominately take the appearance of web map mashups, in essence portraying the location of social media usage on a map. Such an early attempt to visualize social media is shown Figure 1. We argue that while this approach is informative, it often falls short of capturing the depth, richness, and complexity of the information that can be gleaned from social data. As a result, a need for more advanced geovisualization approaches that are capable of better capturing and communicating the complexity and multidimensionality of social media arises. And this is the focus of our chapter. We discuss briefly the geovisualization of network structures (such as shown in Figure 2), the geovisualization of network structure dynamics, the geovisualization of social media content (such as shown in Figure 3) along with the visualization of social media analysis (Figure 4) and conclude the chapter with a list of emerging research challenges.

Figure 2: Visualizing communities: a social network of an interest group (a), and the geovisualization of the  largest community shown over the contiguous U.S (B).

Figure 3: Visualizing social media content dynamics by coupling a Twitter stream viewer (A), a Twitter activity density map (B), and a ranked list top hash-tags (C) and top authors (E), a time slider (D), and author/hash-tags time series graphs.

Figure 4: Visualizing spatiotemporal clusters of tweets following the 2013 Boston bombing. Red circles indicate the approximate radius of each cluster, and color is used to indicate time.

We hope you enjoy. As always any feedback or comments most welcome. Please note this chapter was written a couple of years ago and more recent work by us has been done, click here to see some.

Full Reference:

Croitoru, A., Crooks, A.T., Radzikowski, J. and Stefanidis, A. (2017), Geovisualization of Social Media, in Richardson, D., Castree, N., Goodchild, M. F., Kobayashi, A. L., Liu, W. and Marston, R. (eds.), The International Encyclopedia of Geography: People, the Earth, Environment, and Technology, Wiley Blackwell. DOI: 10.1002/9781118786352.wbieg0605 (PDF)

Project Geppetto

Project Geppetto from Autodesk attempts to make it it easy, fast, and fun to add crowds to 3ds Max scenes. It is part of Autodesk's  "People Power" concept, where the basic idea is to try to assemble all the components one needs to create, manage, and control large crowds of characters. Specificcally it attempts to create believable motion, allow for cultural influences (Evolver) and to create a framework for thousands of characters to interact in. Below are some examples of the project.

New Paper: Agent Street: An Environment for Exploring Agent-Based Models in Second Life

Our work with agent-based modeling in Second Life has just been published in the Journal of Artificial Societies and Social Simulation (JASSS). The full title of the paper is "Agent Street: An Environment for Exploring Agent-Based Models in Second Life" and the abstract reads as follows:

"Urban models can be seen on a continuum between iconic and symbolic. Generally speaking, iconic models are physical versions of the real world at some scaled down representation, while symbolic models represent the system in terms of the way they function replacing the physical or material system by some logical and/or mathematical formulae. Traditionally iconic and symbolic models were distinct classes of model but due to the rise of digital computing the distinction between the two is becoming blurred, with symbolic models being embedded into iconic models. However, such models tend to be single user. This paper demonstrates how 3D symbolic models in the form of agent-based simulations can be embedded into iconic models using the multi-user virtual world of Second Life. Furthermore, the paper demonstrates Second Life's potential for social science simulation. To demonstrate this, we first introduce Second Life and provide two exemplar models; Conway's Game of Life, and Schelling's Segregation Model which highlight how symbolic models can be viewed in an iconic environment. We then present a simple pedestrian evacuation model which merges the iconic and symbolic together and extends the model to directly incorporate avatars and agents in the same environment illustrating how 'real' participants can influence simulation outcomes. Such examples demonstrate the potential for creating highly visual, immersive, interactive agent-based models for social scientists in multi-user real time virtual worlds. The paper concludes with some final comments on problems with representing models in current virtual worlds and future avenues of research."

Agents reacting to Avatars

Accompanying the paper we have created a dedicated website giving more details about the work including the model source code which can be found here.

Our next steps are to start exploring how such models can be created and extended in OpenSim and carrying out user testing along with online model creation.

The full reference to the paper is:

Crooks, A, Hudson-Smith, A and Dearden, J (2009). 'Agent Street: An Environment for Exploring Agent-Based Models in Second Life'. Journal of Artificial Societies and Social Simulation, 12(4)10: http://jasss.soc.surrey.ac.uk/12/4/10.html.

Visualisation in support of management decisions

Following on from the previous post about SYMAP, its amazing to think that in a short period of time how technologies have developed. For example, take the the 18th World IMACS Congress and MODSIM09 International Congress on Modelling and Simulation. There are a wealth of talks in the visualisation in support of management decisions session, such as the paper presented by Phil Greenwood entitled "Using game engine technology to create real-time interactive environments to assist in planning and visual assessment for infrastructure" part of which I show below:



Further information about this session can be found here. Also for those interested in visualization and game engines, the excellent Digital Urban blog at CASA is worth a look.

SYMAP movie

I recently been exploring visualization techniques for agent-based modeling and GIS and came across this old movie produced by Allan Schmidt showing urban expansion of Lansing, Michigan between 1850 to 1965.

Whats interesting is its based on the synergraphic mapping system (SYMAP) developed by Howard Fisher in the mid 1960s which was one of the first general-purpose mapping packages. The second movie below gives some background on SYMAP:

Treemaps: Hierarchical Layouts to Address Research Questions

Effectively visualising and understanding complex datasets is an extremely difficult task so I thought it worth highlighting the recent work of Aidan Slingsby, Jason Dykes and Jo Wood (who has also written a nice book about Java Programming for Spatial Sciences) , who are all from the giCentre at City University London on treemaps, especially how treemaps can be used for displaying and understanding hierarchical data.

In the paper entitled "Configuring Hierarchical Layouts to Address Research Questions, to quote the authors "explore(s) the effects of selecting alternative layouts in hierarchical displays that show multiple aspects of large multivariate datasets, including spatial and temporal characteristics" For further information (including a paper) about the work, readers are advised to read the site: http://www.gicentre.org/hierarchical_layouts/.

Below is a short movie created by Aidan Slingsby demonstrating their work for the IEEE InfoVis Conference in Atlantic City this coming October:



Thanks to Aidan Slingsby for allowing us to use the movie.

Full reference: 

Slingsby, A., Dykes, J., Wood, J. and Crooks, A.T. (2009), The Role of Layout and Order in Treemaps for Showing Spatial and Temporal Variation in House Prices. GeoViz, Hamburg Germany. (pdf)