Wednesday, December 17, 2014

Example Models from CSS600

Even after several years of teaching it is always amazing how quickly a semester passes. One of the courses I taught this semester was CSS 600: Introduction to Computational Social Science. This is often the first CSS class many students take here at George Mason University. We discuss a number of computational approaches which are used for social science research, coupled to  complexity theory. As an introduction to the subject, the course has the following objectives:
  1. To understand the motivation for the use of computational models in social science theory and research, including some historical aspects (Why conduct computational research in the social sciences?).
  2. To learn about the variety of CSS research programs across the social science disciplines, through a survey of social simulation models (What has CSS accomplished thus far?).
  3. To understand the distinct contribution that CSS can make by providing specific insights about society, social phenomena at multiple scales, and the nature of social complexity (What is the relation between computational social science.
  4. To provide foundations for more advanced work in subsequent courses or projects for those students who already have or will develop a long-term interest in CSS.
Part of the students final grade comes from the development of a computational model in an area of their interest (e.g., microeconomics, international relations, environmental policy, economic development, historical dynamics, finance etc..). Often, this is the first compuational model that the students have ever developed. Below you can see a number of models developed using NetLogo as part of the class.

To find out more about our program see:

Friday, November 28, 2014

Linking Cyber and Physical Spaces

We have just published a new paper in  Computers, Environment and Urban Systems entitled "Linking Cyber and Physical Spaces Through Community Detection And Clustering in Social Media Feeds". In the paper we explore how geosocial media is providing us with  a new social communication avenue and a novel source of geosocial information. 

In particular, we discuss the notion of physical presence within social media and its importance for exploring the relation between the cyber and the physical domains. We discuss how communities and groups can be detected in both the cyber and physical space, and how they can be processed to form a ‘hybrid’ geosocial view of communities using social network analysis, community detection (the Louvain method) and DenStream. To showcase these concepts and their benefits, we present the analysis of two case studies that make use of Twitter data associated with two different types of events: a planned activity during the Occupy Wall Street (OWS) Day of Action (November 17th, 2011), and the response to the Boston Marathon Bombing (April 15, 2013). We conclude with a summary and outlook. Below is the abstract of the paper:
Over the last decade we have witnessed a significant growth in the use of social media. Interactions within their context lead to the establishment of groups that function at the intersection of the physical and cyber spaces, and as such represent hybrid communities. Gaining a better understanding of how information flows in these hybrid communities is a substantial scientific challenge with significant implications on our ability to better harness crowd-contributed content. This paper addresses this challenge by studying how information propagates and evolves over time at the intersection of the physical and cyber spaces. By analyzing the spatial footprint, social network structure, and content in both physical and cyber spaces we advance our understanding of the information propagation mechanisms in social media. The utility of this approach is demonstrated in two real-world case studies, the first reflecting a planned event (the Occupy Wall Street – OWS – movement’s Day of Action in November 2011), and the second reflecting an unexpected disaster (the Boston Marathon bombing in April 2013). Our findings highlight the intricate nature of the propagation and evolution of information both within and across cyber and physical spaces, as well as the role of hybrid networks in the exchange of information between these spaces.

Research highlights include:
    • Our analysis includes two major events as captured in Twitter.
    • The themes in cyber and physical communities tend to converge over time.
    • Messages among physical space users are more consistent at the onset of the event.
    • Geolocated users are consuming information more than they produce.

      Below are some of the images from the paper. Specifically the first image is how one can think of the relationships between physical and cyber spaces.  The next image provides an overview Our geosocial analysis framework for examining cyber and physical communities.

      Our Geosocial analysis framework

      In the figure below we show an example of using DenStream for spatiotemporal clustering and how the process can capture the protest activities that were planned for the Occupy Wall Street movement’s Day of Action. Each dot corresponds to the originating location of a geolocated tweet; The color of each point indicates the time of the corresponding tweet, ranging from dark blue (early morning, 0) to dark red (late night, 1). While the circles represent a specific spatiotemporal cluster. For example the circle labeled A marked the start of the day where people congregated around Wall Street while circle labeled C shows a cluster at Foley Square.
      Physical space groups identified in the lower Manhattan area. Each dot corresponds to the originating location of a geolocated tweet; The color of each point indicates the time of the corresponding tweet, ranging from dark blue (early morning, 0) to dark red (late night, 1).

      While in the figure below we show one example of linking the cyber and physical communities. Specifically in (a), the top five communities (node degree > 100) in the cyber space retweet network (each community is designated by one color) are shown; (b) shows the physical space groups; and (c) shows the resulting  hybrid meta-network where the connections between physical groups (P nodes), and cyber space communities (C nodes) are shown.

      We hope you enjoy the paper.

      Full Reference:
      Croitoru, A., Wayant, N., Crooks, A.T., Radzikowski, J. and Stefanidis, A. (2014), Linking Cyber and Physical Spaces Through Community Detection And Clustering in Social Media Feeds, Computers, Environment and Urban Systemsdoi:10.1016/j.compenvurbsys.2014.11.002. (pdf)

      Wednesday, October 29, 2014

      Happy Halloween: Zombie Agent-Based model

      In preparation for Halloween,  last night in class we explored a simple agent-based model of zombie attack. At each time step, a human moves to a nearby unoccupied space, and a zombie moves to the nearest human. If a zombie and an uninoculated human occupy the same space, a fierce battle ensues, in which the probability that the human will kill the zombie is pkH-z, and the probability that the zombie kills the human and converts them to their horrific undead form is pkZ-h. 

      Zombies, however, are not attracted to inoculated humans and ignore them. If recovery? is enabled, then there is a chance (given by recoveryRate) that a zombified person will see the errors of their cannibalistic ways and return to human form. All these factors working together provide some interesting population dynamics, illustrated by the “Totals” population count plot on the screen. 

      The model is programed in NetLogo and also demonstrates how a simple as .asc file can be used for the spatial envirment for the zombies and humans to interact within.

      You can download the code from here.

      Tuesday, September 23, 2014

      Geosimulation and Big Data: A Marriage made in Heaven or Hell?
      Call for papers: AAG 2015 – Geosimulation and Big Data: A Marriage made in Heaven or Hell?

      In recent years, human emotions, intentions, moods and behaviors have been digitized to an extent previously unimagined in the social sciences. This has been in the main due to the rise of a vast array of new data, termed ‘Big Data’. These new forms of data have the potential to reshape the future directions of social science research, in particular the methods that scientists use to model and simulate spatially explicit social systems. Given the novelty of this potential “revolution” and the surprising lack of reliable behavioural insight to arise from Big Data research, it is an opportune time to assess the progress that has been made and consider the future directions of socio-spatial modelling in a world that is becoming increasingly well described by Big Data sources.

      We invite methodological, theoretical and empirical papers that that engage with any aspect of geospatial modelling and the use of Big Data. We are particularly interested in the ways that insight into individual or group behavior can be elucidated from new data sources – including social media contributions, volunteered geographical information, mobile telephone transactions, individually-sensed data, crowd-sourced information, etc. – and used to improve models or simulations. Topics include, but are not limited to:
      • Using Big Data to inform individual–based models of geographical systems;
      • Translating Big Data into agent rules;
      • Elucidating behavioral information from diverse data;
      • Improving simulated agent behavior;
      • Validating agent-based models (ABM) with Big Data;
      • Ethics of data collected en masse and their use in simulation.
      Please e-mail the abstract and key words with your expression of intent to Nick Malleson by 28th October, 2014. Please make sure that your abstract conforms to the AAG guidelines in relation to title, word limit and key words and as specified at An abstract should be no more than 250 words that describe the presentation’s purpose, methods, and conclusions as well as to include keywords.

      • Alison Heppenstall, School of Geography, University of Leeds
      • Nick Malleson, School of Geography, University of Leeds
      • Andrew Crooks, Department of Computational Social Science, George Mason University
      • Paul Torrens, Department of Geographical Sciences, University of Maryland
      • Ed Manley, Centre for Advanced Spatial Analysis, University College London
      • 28th October, 2014: Abstract submission deadline. E-mail Nick Malleson by this date if you are interested in being in this session. Please submit an abstract and key words with your expression of intent.
      • 31st October, 2014: Session finalization and author notification
      • 3rd November, 2014: Final abstract submission to AAG, via All participants must register individually via this site. Upon registration you will be given a participant number (PIN). Send the PIN and a copy of your final abstract to Nick Malleson. Neither the organizers nor the AAG will edit the abstracts.
      • 5th November, 2014: AAG registration deadline. Sessions submitted to AAG for approval.

      Thursday, September 18, 2014

      New Paper: ABM Applied to the Spread of Cholera

      Cholera transmission through the interaction
      of host and the environment
      We are pleased to announce we have just had a paper published in Environmental Modelling and Software entitled "An Agent-based Modeling Approach Applied to the Spread of Cholera"

      Research highlights include:
      • An agent-based model was developed to explore the spread of cholera.
      • The progress of cholera transmission is represented through a Susceptible-Exposed-Infected-Recovered (SEIR) model. 
      • The model integrates geographical data with agents’ daily activities within a refugee camp.
      • Results show cholera infections are impacted by agents’ movement and source of contamination. 
      • The model has the potential for aiding humanitarian response with respect to disease outbreaks.
      Cholera dynamics when rainfall is introduced.

      Spatial spread of cholera over the course of a year.

      Study area
      If the research highlights have not turned you off, the abstract to the paper is below:
      "Cholera is an intestinal disease and is characterized by diarrhea and severe dehydration. While cholera has mainly been eliminated in regions that can provide clean water, adequate hygiene and proper sanitation; it remains a constant threat in many parts of Africa and Asia. Within this paper, we develop an agent-based model that explores the spread of cholera in the Dadaab refugee camp in Kenya. Poor sanitation and housing conditions contribute to frequent incidents of cholera outbreaks within this camp. We model the spread of cholera by explicitly representing the interaction between humans and their environment, and the spread of the epidemic using a Susceptible-Exposed-Infected-Recovered model. Results from the model show that the spread of cholera grows radially from contaminated water sources and seasonal rains can cause the emergence of cholera outbreaks. This modeling effort highlights the potential of agent-based modeling to explore the spread of cholera in a humanitarian context."
      Finally to aide replication, experimentation or just explore how you can link raster and vector data in GeoMason, we have a dedicated website where you can download executables of the model along with the source code and associated data. Moreover we have provide a really detailed Overview, Design concepts, and Details (ODD) Protocol document of the model here.

      Full Reference:
      Crooks, A.T. and Hailegiorgis, A.B. (2014), An Agent-based Modeling Approach Applied to the Spread of Cholera, Environmental Modelling and Software, 62: 164-177
      DOI: 10.1016/j.envsoft.2014.08.027 (pdf)

      Wednesday, September 17, 2014

      Triangulating Social Multimedia Content for Event Localization

      As regular visitors will know, we have been developing our ability to collect and analyze social media. To this end we have just received word from Transactions in GIS that our paper entitled "Triangulating Social Multimedia Content for Event Localization using Flickr and Twitter" has just been accepted. Below is the abstract from the paper:
      The analysis of social media content for the extraction geospatial information and event-related knowledge has recently received substantial attention. In this paper we present an approach that leverages the complementary nature of social multimedia content by utilizing heterogeneous sources of social media feeds to assess the impact area of a natural disaster. More specifically, we introduce a novel social multimedia triangulation process that uses jointly Twitter and Flickr content in an integrated two-step process: Twitter content is used to identify toponym references associated with a disaster; this information is then used to provide approximate orientation for the associated Flickr imagery, allowing us to delineate the impact area as the overlap of multiple view footprints. In this approach, we practically crowdsource approximate orientations from Twitter content and use this information to orient accordingly Flickr imagery and identify the impact area through viewshed analysis and viewpoint integration. This approach enables us to avoid computationally intensive image analysis tasks associated with traditional image orientation, while allowing us to triangulate numerous images by having them pointed towards the crowdsourced toponym location. The paper presents our approach and demonstrates its performance using a real-world wildfire event as a representative application case study.
       Our cross-source triangulation framework is outlined in the figure below:

      The cross-source triangulation framework.
      To demonstrate the benefit of using cross-sourced social media in the triangulation process we applied three modes of the analysis:
      • Mode 1: the impact area was estimated as the overlap of all viewsheds that were generated from all Flickr contribution locations without calculating a reference point or evaluating the Angle Of View (AOV) for each image. Accordingly, in this mode, we use only Flickr data, without constraining the viewshed analysis with any AOV information. 
      • Mode 2: the impact area was estimated by using the centroid of the locations of all Flickr contributions as the reference point for the AOV calculation, followed by a viewshed analysis of each image. Accordingly, in this mode we use only Flickr data, ignoring any toponym information from Twitter. 
      • Mode 3: the impact area was estimated by using the toponym reference, as derived from Twitter, as the reference point for the AOV calculation, followed by a viewshed analysis of each image. Accordingly, in this mode we use Twitter content to orient Flickr data and guide the viewshed analysis.
      The figure below shows the result from Mode 3:

      A three-dimensional perspective of wildfire location assessment as derived by analysis mode 3.

      Full Reference: 
      Panteras, G., Wise, S., Lu, X., Croitoru, A., Crooks, A.T. and Stefanidis, A. (2014), Triangulating Social Multimedia Content for Event Localization using Flickr and Twitter, Transactions in GIS. (pdf)

      Friday, September 12, 2014

      Scottish Referendum conversation as seen on Twitter

      There is a lot of talk about Scotland's up and coming referendum for independence. If you are interested in what people are saying live on Twitter you can take a look at our GeoSocial Gauge website.

      What you will see is a map showing the location of tweets (which you can click on to find more information), along with options for visualizing the intensity of Twitter activity, and whether or not the tweets are negative or positive. You can also see the overall mood of the conversion and the keywords from the tweets. 

      To see more of our GeoSocial projects click here.

      Call for Papers: New Directions in Geospatial Simulation

      New Directions In Geospatial Simulation

      The geospatial simulation community has enjoyed steady growth over the past decade as novel and advanced forms of agent-based and cellular automata modeling continue to facilitate the exploration of complex geographic problems facing the world today. It is now an opportune time to consider the future direction of this community and explore ways to leverage geospatial simulation in professional arenas. The aim of these sessions is to bring together researchers utilizing agent-based and cellular automata techniques and associated methodologies to discuss new directions in geospatial simulation. We invite papers that fall into one of the following four categories:
      • Graduate student geospatial simulation research
      • Methodological advances of agent-based or cellular automata modeling
      • New application frontiers in geospatial simulation
      • Approaches for evaluating the credibility of geospatial simulation models
      Student papers will be presented in an interactive short paper session with presentations no longer than five minutes and no more than ten slides. Following presentations, students will form a panel that will address questions from the audience as directed by the session moderator. Student presentations will be judged as a part of a Best Student Paper award, the winner of which will receive an award of $500.

      All other papers will be placed in one of the following three sessions: (1) Methodological Advances, (2) Novel Applications, or (3) Model Credibility. Each session will be comprised of four speakers followed by a twenty-minute discussion on the session topic.

      Please e-mail the abstract and key words with your expression of intent to Chris Bone by October 28, 2014. Please make sure that your abstract conforms to the AAG guidelines in relation to title, word limit and key words and as specified at An abstract should be no more than 250 words that describe the presentation's purpose, methods, and conclusions as well as to include keywords. Full submissions will be given priority over submissions with just a paper title.

      Chris Bone, Department of Geography, University of Oregon
      Andrew Crooks, Department of Computational Social Science, George Mason University
      Alison Heppenstall, School of Geography, University of Leeds
      Arika Ligmann-Zielinska, Department of Geography, Michigan State University
      David O’Sullivan, Department of Geography, University of California, Berkeley


      October 14th, 2014: Second call for papers

      October 28th, 2014: Abstract submission and expression of intent to session organizers. E-mail Chris Bone by this date if you are interested in being in this session. Please submit an abstract and key words with your expression of intent. Full submissions will be given priority over submissions with just a paper title.

      October 31st, 2014: Session finalization. Session organizers determine session order and content and notify authors.

      November 3rd, 2014: Final abstract submission to AAG, via All participants must register individually via this site. Upon registration you will be given a participant number (PIN). Send the PIN and a copy of your final abstract to Chris Bone. Neither the organizers nor the AAG will edit the abstracts.

      November 5th, 2014: AAG registration deadline. Sessions submitted to AAG for approval.

      April 21-25, 2014: AAG meeting, Chicago, Illinois, USA.

      Friday, August 29, 2014

      Herding Sheep
      Have you ever wondered how a farmer and a single sheep dog can herd sheep? A recent paper in Journal of the Royal Society Interface explains just how. Using GPS data from collars researchers have developed a computational model which  "reproduces key features of empirical data collected from sheep–dog interaction". The model has two simple rules:
      "The first rule: The sheepdog learns how to make the sheep come together in a flock. The second rule: Whenever the sheep are in a tightly knit group, the dog pushes them forwards." (BBC)
      The movie below (which accompanies the paper) shows some simulation runs with different numbers of agents. The shepherd (blue) approaches and rounds up the agents/sheep (black dots) and then proceed to herd the group toward the target.

      Full Reference:
      Strömbom. D. Mann, R. P., Wilson, A. M., Hailes, S., Morton, A. J., Sumpter, D. J. T., King, A. J. (2014) Solving the shepherding problem: Heuristics for herding autonomous, interacting agents. Journal of the Royal Society Interface, 11: 20140719.
      Thanks to @Badnetworker for drawing my attention to this.

      Wednesday, July 09, 2014

      New Paper: Assessing the impact of demographic characteristics on spatial error in VGI features

      LISA analysis of positional accuracy for the OSM  data set
      Building upon our interest in volunteered geographic information (VGI) and extending our previous paper  "Assessing Completeness and Spatial Error of Features in Volunteered Geographic Information" we have just published the paper with the rather long title "Assessing the impact of demographic characteristics on spatial error in volunteered geographic information features" where we explore how demographics impact on the quality of VGI data

      Below is the abstract of the paper: 
      The proliferation of volunteered geographic information (VGI), such as OpenStreetMap (OSM) enabled by technological advancements, has led to large volumes of user-generated geographical content. While this data is becoming widely used, the understanding of the quality characteristics of such data is still largely unexplored. An open research question is the relationship between demographic indicators and VGI quality. While earlier studies have suggested a potential relationship between VGI quality and population density or socio-economic characteristics of an area, such relationships have not been rigorously explored, and mainly remained qualitative in nature. This paper addresses this gap by quantifying the relationship between demographic properties of a given area and the quality of VGI contributions. We study specifically the demographic characteristics of the mapped area and its relation to two dimensions of spatial data quality, namely positional accuracy and completeness of the corresponding VGI contributions with respect to OSM using the Denver (Colorado, US) area as a case study. We use non-spatial and spatial analysis techniques to identify potential associations among demographics data and the distribution of positional and completeness errors found within VGI data. Generally, the results of our study show a lack of statistically significant support for the assumption that demographic properties affect the positional accuracy or completeness of VGI. While this research is focused on a specific area, our results showcase the complex nature of the relationship between VGI quality and demographics, and highlights the need for a better understanding of it. By doing so, we add to the debate of how demographics impact on the quality of VGI data and lays the foundation to further work.

      The analysis workflow
      Full Reference:
      Mullen W., Jackson, S. P., Croitoru, A., Crooks, A. T., Stefanidis, A. and Agouris, P., (2014), Assessing the Impact of Demographic Characteristics on Spatial Error in Volunteered Geographic Information Features, GeoJournal. DOI: 10.1007/s10708-014-9564-8

      Thursday, June 05, 2014

      The Evolving GeoWeb

      We recently contributed a chapter to Geocomputation (2nd edition) entitled "The Evolving GeoWeb". What is interesting is the marked difference between the first edition (which was published in 2000) and the second. For example, in the latest edition, there is a chapter on agent-based modeling (ABM), while in the first, only cellular automata (CA) models were covered and ABMs only briefly discussed. We also see in the second edition new chapters including ours on the GeoWeb which shows how the field of geocomputation has changed with advances in Web 2.0 technology, greater computational power, new devices (such as GPS enabled smart phones) and the rise in new sources of data (volunteered and ambient geographical information, VGI and AGI). The abstract of our chapter is copied below, while examples of early and current web mapping is provided in the figures below.

      "The Internet and its World Wide Web (WWW) have revolutionised many aspects of our daily lives from how we access and retrieve information to how we communicate with friends and peers. Over the past two decades, the Web has evolved from a system aimed primarily towards data access to a medium that fosters information contribution and interaction within large, globally distributed communities. Just as the Web evolved, so too did Web-based GeoComputation (GC), which we refer to here as the Geographic World Wide Web or the GeoWeb for short. Whereas the generation and viewing of geographical information was initially limited to the purview of specialists and dedicated workstations, it has now become of interest to the general public and is accessed using a variety of devices such as GPS-enabled smartphones and tablets. Accordingly, in order to meet the needs of this expanded constituency, the GeoWeb has evolved from displaying static maps to a dynamic environment where diverse datasets can be accessed, exchanged and mashed together. Within this chapter, we trace this evolution and corresponding paradigm shifts within the GeoWeb with a particular focus on Web 2.0 technologies. Furthermore, we explore the role of the crowd in consuming and producing geographical information and how this is influencing GeoWeb developments. Specifically, we are interested in how location provides a means to index and access information over the Internet. Next, we discuss the role of Digital Earth and virtual world paradigms for storing, manipulating and displaying geographical information in an immersive environment. We then discuss how GIS software is changing towards GIS services and the rise in location-based services (LBS) and lightweight software applications (so-called apps). Finally, we conclude with a summary of this chapter and discuss how the GeoWeb might evolve with the rise in massive amounts of locational data being generated."

      PARC Map Viewer (Source: Putz, 1994)

      Google Earth as a base layer for possible trajectories of the radioactive plume from the Fukushima Daiichi nuclear disaster. The different color lines represent different possible paths of the plume (Source:

      A proof of our chapter can be downloaded from here. We hope you enjoy it!

      Full reference:
      Crooks, A.T., Hudson-Smith, A., Croitoru, A. and Stefanidis, A. (2014), The Evolving GeoWeb, in Abrahart R. J. and See, L. M. (eds.), Geocomputation (Second Edition), CRC Press, Boca Raton, FL, pp. 69-96. (pdf)

      Tuesday, May 27, 2014

      A semester with Spatial Agent-based Models

      This last semester, I taught a class entitled "Spatial Agent-based Models of Human-Environment Interactions" which introduces graduate students to the use of agent-based techniques as a means of modelling human-environmental interactions. Within the class we cover a variety of applications in areas such as agriculture, forestry, biodiversity, habitat degradation, interactions between human populations and nonhuman species and urban models. As with many of the courses I teach it combines literature reviews with hands-on modelling. One of the requirements of the class is for students to complete a class project where they develop their own agent-based model in their area of interest. As always there were a range of models and I wanted to share some here.

      The first is an agent-based model of gentrification in part of Washington DC. Within the model, developers create new houses, residents can move in and out and as a result the demographics of the area changes over time. The movie below gives a sense of the model dynamics.

      In another model, a student developed a simple agent-based model which asks the question if random police patrols vs. a concentrated police effort can reduce the number of burglaries in an area. The burglars have a simple routine and commit crimes when their energy reserves fall below a certain threshold. If the police agents see a crime being committed they arrest the burglar. Over time, crime hotspots emerge (detected using DBSCAN) which lead to an increased police presence in an area. The movie below gives a sense of the model dynamics.

      In another model,  a student explored how commuting behaviors of agents might lead to traffic jams and how different transportation options might reduce congestion. The movie below gives a sense of the model dynamics.

      Overall it was a fun class with many interesting models programed in a variety of languages and toolkits (Python, Java, MASON, NetLogo).

      Friday, April 25, 2014

      Special Sessions on GeoComputation @ NARSC

      Second Call for participation

      Special Sessions on GeoComputation

      61st Annual North American Meetings of the Regional Science Association International NARSC - RSAI
      November 12-15, 2014, Washington, DC, USA

      The special sessions on various aspects of GeoComputation are planned for the North American Meetings of the Regional Science Association International (NARSC) to be held in Washington DC, USA, November 12-15, 2014. Suitable topics for the session presentations are theoretical, methodological and applied issues related to GeoComputation – spatial analysis and modeling, and in the context of regional science.

      Please let us know if you are interested to contribute to the special session(s) by sending an email at <> with the title, abstract, name of author(s), affiliations, contact details and the unique ID number at your earliest but not later than June 25th, 2014. The abstract should be 2,000 to 5,500 characters and spaces.

      Please note that in order to have your presentation included to the special session we do need the unique identification number (ID). The ID, or PIN, is a number included at the bottom of the confirmation email received following the submission of an abstract.

      Detailed information about the NARSC conference can be found at . Information about the submission process can be found at . Conference abstract submission deadline is July 1st, 2014.

      Looking forward to seeing you in Washington, DC.

      The organizers:

      Prof. Suzana Dragićević
      Department of Geography
      Simon Fraser University, Canada

      Prof. Andrew Crooks
      Department of Computational Social Science
      George Mason University, USA

      Prof. Jean-Claude Thill
      Department of Geography and Earth Sciences
      University of North Carolina at Charlotte, USA

      Saturday, April 12, 2014

      AAG and Twitter

      After spending a rather enjoyable few days at the Association of American Geographers (AAG) annual meeting in Tampa where there were some great talks on agent-based modeling, GIS and many other topics which I find interesting, along with catching up with some old friends and meeting new ones, its now time to head back up North. 

      However, before jumping on the plane, I thought it would be intersing to look at the twitter traffic of the event (especially how there so many talks on using social media for geographical research). That being said, before showing the Twitter networks associated with the conference, one issue that was common among the conversion outside of the sessions was the lack of wifi access at the conference which accounts for small numbers of tweets durring the events but also one could argue people were more interested in the talks than that of tweeting. With that being said, within this analysis we show below we collected data using the #aag2014 and the @theAAG to explore the Twitter conversation.

      The image below shows the # hashtag network from the conference with the biggest cluster being #aag2014 and associated words (click here to see a high solution image)

      In the next image we removed the #aag2014 to only show the details of the network within this cluster. After removing the #aag2014 we re-ran the clustering on this network. The graph below shows the biggest clusters (with 3 or more nodes) within the #aag2014 group. Nicely outlined are the discussion topics (e.g. gender, sexuality, intimacy, climate, geoweb). Click here to see a higher resolution image.

      Moving away from the hashtags and looking at the retweet network we were surprised to see that the AAG's account wasn't more active (click here to see a higher resolution image).

      Also we are currently working on a spatial-temporal slider to look at the conversion over time. Below is a sneak peak from one moment in time. This will be soon coming to the Geosocial Gauge website. 

      Wednesday, April 09, 2014

      An Agent-based Model for the Spread and Containment of Tuberculosis

      Over the last few months we have been working on developing a agent-based model which explores the spread and containment of tuberculosis. Today is the first time that we show the model to a academic audience at the AAG Annual meeting. To give a sense of our research, below is the abstract:
      Tuberculosis (TB) is a global problem and especially in developing countries. After human immunodeficiency virus (HIV) it is the most common form of death from an infectious disease. However, it is still unknown exactly how it spreads within a population. A geographic explicit agent-based model, with humans as agents, was created and applied to study the TB problem. Specifically the model was developed to see what epidemiological dynamics may occur, and what could be learned about the spreading of the disease. The model was developed in MASON and utilizes the GeoMason GIS extension. A Susceptible-Exposed-Infectious-Recovered (SEIR) submodel was created to model TB progression and linked to daily human activities. The slum of Kibera, Kenya (the largest urban slum in Africa, and an area where TB and HIV is particularly rampant) was chosen as a test-case. Detailed geospatial and demographic information from Kibera was used for the instantiation of the models spatial environment and demographic properties of the agents. Preliminary results obtained from standard model runs show that TB epidemics progress in staircase patterns of emergence and stabilization. Furthermore, it was found that TB was creating hotspots, or pockets of dense disease concentration, from where it was spreading. The results and lessons gleaned from the model can be easily incorporated into current health policies to mitigate TB's negative impact. Furthermore, the research shows the potential of ABMs in investigating infectious diseases.
      Susceptible-Exposed-Infectious-Recovered (SEIR) submodel

      To give a sense of what the model looks like below we show the full model running with 250,000 agents on the slum of Kibera, Kenya.

      In the next movie we show the model running with only 50,000 agents but with a zoomed in section of the Kibera Slum. In this movie, you can see the agents going about their daily activities and how some become infected with TB.

      This work would not of been possible without the work of my co-author Parth Chopra and the Thomas Jefferson High School for Science and Technology Mentorship Program.

      Thursday, April 03, 2014

      Social Media and the Emergence of Open-Source Geospatial Intelligence

      Recently the USGIF published a book entitled "Human Geography: Socio-Cultural Dynamics and Global Security" in which we have a chapter called "Social Media and the Emergence of Open-Source Geospatial Intelligence". This book has been some  time in the making. We blogged about our contribution in  2012. But its finally its out! Below is the abstract for our chapter:

      The emergence of social media has provided the public with an effective and irrepressible real-time mechanism to broadcast information. The great popularity of platforms such as twitter and YouTube, and the substantial amount of content that is communicated through them are making social media an essential component of open-source intelligence. The information communicated through such feeds conveys the interests and opinions of individuals, and reveals links and the complex structure of social networks. However, this information is only partially exploited if one does not consider its geographical aspect. Indeed, social media feeds more often than not have some sort of geographic content, as they may communicate the location from where a particular report is contributed, the geolocation of an image, or they may refer to a specific sociocultural hotspot. By harvesting this geographic content from social media feeds we can transfer the extracted knowledge from the amorphous cyberspace to the geographic space, and gain a unique understanding of the human lansdscape, its structure and organization, and its evolution over time. This newfound opportunity signals the emergence of open-source geospatial intelligence, whereby social media contributions can be analyzed and mined to gain unparalleled situational awareness. In this paper we showcase a number of sample applications that highlight the capabilities of harvesting geospatial intelligence from social media feeds, focusing particularly on twitter as a representative data source. 

      Geolocated pairs of tweeters and retweeters in Tokyo at the time immediately following the Sendai earthquake

      Full Reference: 
      Stefanidis, A., Crooks, A.T., Radzikowski, J., Croitoru, A. and Rice, M. (2014), Social Media and the Emergence of Open-Source Geospatial Intelligence, in Murdock, D.G., Tomes, R. and Tucker, C. (eds.), Human Geography: Socio-Cultural Dynamics and Global Security, US Geospatial Intelligence Foundation (USGIF), Herndon, VA, pp. 109-123. (pdf)

      Multi-Agent Systems for Urban Planning

      Recently we contributed a chapter to "Technologies for Urban and Spatial Planning: Virtual Cities and Territories" which aims to quote from the preference:  
      "(i) to contribute to the dissemination of the recent research and development of the use of information and communication technologies (ICT) in urban and spatial planning, trying to demonstrate their usability in planning processes through the presentation of relevant case studies, framed by their underlying theory; (ii) to give additional evidence to the fact that ICT are the privileged means to produce virtual cities and territories; and (iii) to make available, from a pedagogical standpoint, a group of illustrative reviews of the scientific production made by both academics and practitioners in the field."
      The book has 11 chapters which are grouped in several themes:
      "first group focuses on the discussion over the use of ICT in spatial planning; the second group of contributions deals with urban modelling and simulation; the third group focuses on the use of different sensors to acquire information and model spatial processes; the fourth group focuses on the use of data to create more capable visualization tools; and the fifth group is about the use of virtual models to simulate real environments and plan and manage other aspects of the built environment such as energy."
      Our chapter is entitled "Multi-agent Systems for Urban Planning" fits into the second group with respect to urban modeling and simulation. We present a detailed overview about the theory and the development of multi-agent systems (MAS) in spatial planning, focusing on how MAS can lead to insights into urban problems and aid urban planning fostering a bottom up approach to spatial planning. The abstract is as follows:
      Cities provide homes for over half of the world's population, and this proportion is expected to increase throughout the next century. The growth of cities raises many questions and challenges for urban planning including which cities and regions are most likely to grow, what the pattern of urban growth will be, and how the existing infrastructure will cope with such growth. One way to explore these types of questions is through the use of multi-agent systems (MAS) that are capable of modeling how individuals interact and how structures emerge through such interactions, in terms of both the social and physical environment of cities. Within this chapter, the authors focus on how MAS can lead to insights into urban problems and aid urban planning from the bottom up. They review MAS models that explore the growth of cities and regions, models that explore land-use patterns resulting from such growth along with the rise of slums. Furthermore, the authors demonstrate how MAS models can be used to model transportation and the changing demographics of cities. Through these examples the authors also demonstrate how this style of modeling can give insights into such issues that cannot be gleamed from other modeling methodologies. The chapter concludes with challenges and future research directions of MAS models with respect to capturing the dynamics of human behavior in urban planning.

      Full Reference:
      Crooks, A.T., Patel, A. and Wise, S. (2014), Multi-agent Systems for Urban Planning, in Pinto, N.N., Tenedório, J. Antunes A. P. and Roca, J. (eds.), Technologies for Urban and Spatial Planning: Virtual Cities and Territories, IGI Global, Hershey, PA, pp. 29-56. (pdf)

      Friday, March 21, 2014

      AAG 2014: Geosimulation Models Sessions

      If you going to this years AAG, you might be interested in our Geosimulation Models sessions which will take place on Wednesday the 9th of April from 10am (more details below).

      Session Description: Since the publication of Geosimulation in 2004, the use of Agent-based Modeling (ABM) and Cellular Automata (CA) under the umbrella of Geosimulation models within geographical systems have started to mature as methodologies to explore a wide range of geographical and more broadly social sciences problems facing society. The aim of these sessions is to bring together researchers utilizing geosimulation techniques (and associated methodologies) to discuss topics relating to: theory, technical issues and applications domains of ABM and CA within geographical systems.

      10:00 AM to 11:40,  Room 39, TCC, Fourth Floor , Chair: Suzana Dragicevic

      12.40PM to 2.20PM, Room 39, TCC, Fourth Floor, Chair: Paul Torrens

      2:40 PM to 4:20 PM in Room 39, TCC, Fourth Floor, Chair: Paul Torrens

      Siyu Fan and Yichun Xie

      We would also like to thank the following AAG specialty groups for sponsoring our sessions: Spatial Analysis and Modeling Specialty GroupCyberinfrastructure Specialty Group and the Geographic Information Science and Systems Specialty Group