The latest outputs from researchers, alumni and friends at the UCL Centre for Advanced Spatial Analysis (CASA).
Following on with our GeoSocial Analysis work, we recently had a paper published in PLOS ONE entitled “Crowdsourcing A Collective Sense of Place.” In the paper we discuss and showcase how one can take a quantitative approach to derive a collectiv…
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We recently received word that we had a paper accepted for the upcoming 2016 International Conference on Social Media and Society entitled “Accuracy Of User-Contributed Image Tagging In Flickr: A Natural Disaster Case Study.” In the paper w…
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We recently received word that we had a paper accepted for the upcoming 2016 International Conference on Social Media and Society entitled “Accuracy Of User-Contributed Image Tagging In Flickr: A Natural Disaster Case Study.” In the paper w…
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In the past I have written several pieces about Google, Google Maps and how its been pushing the boundaries of geography. The other day I was fortunate enough to attend a talk by John Bailey from Google’s Geo Education team when he was visiting Masons …
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In the past I have written several pieces about Google, Google Maps and how its been pushing the boundaries of geography. The other day I was fortunate enough to attend a talk by John Bailey from Google’s Geo Education team when he was visiting Masons …
Continue reading »
Special Issue on Smart Buildings and Cities for IEEE Pervasive Computing
Submission deadline: 1 July 2016 Extended to July 18th, 2016
Publication date: April–June 2017
One of Mark Weiser’s first envisionments of ubiquitous and pervasive computing had the smart home as its central core. Since then, researchers focused on realizing this vision have built out from the smart home to the smart city. Such environments aim to improve the transparency of information and the quality of life through access to smarter and more appropriate services.
Despite efforts to build these environments, there are still many unanswered questions: What does it mean to make a building or a city “smart”? What infrastructure is necessary to support smart environments? What is the return on investment of a smart environment?
The key to building smart environments is the fusion of multiple technologies including sensing, advanced networks, the Internet of Things, cloud computing, big data analytics, and mobile devices. This special issue aims to explore new technologies, methodologies, case studies, and applications related to smart buildings and cities. Contributions may come from diverse fields such as distributed systems, HCI, ambient intelligence, architecture, transportation and urban planning, policy development, and cyber-physical systems. Relevant topics for issue include
The guest editors invite original and high-quality submissions addressing all aspects of this field, as long as the connection to the focus topic is clear and emphasized.
Guest Editors
Submission Information
Special Issue on Smart Buildings and Cities for IEEE Pervasive Computing
Submission deadline: 1 July 2016 Extended to July 18th, 2016
Publication date: April–June 2017
One of Mark Weiser’s first envisionments of ubiquitous and pervasive computing had the smart home as its central core. Since then, researchers focused on realizing this vision have built out from the smart home to the smart city. Such environments aim to improve the transparency of information and the quality of life through access to smarter and more appropriate services.
Despite efforts to build these environments, there are still many unanswered questions: What does it mean to make a building or a city “smart”? What infrastructure is necessary to support smart environments? What is the return on investment of a smart environment?
The key to building smart environments is the fusion of multiple technologies including sensing, advanced networks, the Internet of Things, cloud computing, big data analytics, and mobile devices. This special issue aims to explore new technologies, methodologies, case studies, and applications related to smart buildings and cities. Contributions may come from diverse fields such as distributed systems, HCI, ambient intelligence, architecture, transportation and urban planning, policy development, and cyber-physical systems. Relevant topics for issue include
The guest editors invite original and high-quality submissions addressing all aspects of this field, as long as the connection to the focus topic is clear and emphasized.
Guest Editors
Submission Information
Megacities, which can be roughly defined as cities with a population of over 10 million people are on the increase due to ongoing urbanization trends. The United Nations notes that since the 1970’s the number of megacities has more than tripled (from 8 to 34), and is expected to further double until 2050 (to exceed 60).
The question we are wondering is how can GeoSocial analysis help understand such cities. To this end, we have recently had a paper published entitled: “Megacities: Through the Lens of Social Media” in the Journal of the Homeland Defense and Security Information Analysis Center (HDIAC). In the paper we discuss opportunities and challenges that social media brings with respect to understanding the physical and cyber spaces within megacities. Below you can see the synopsis to our paper.
Due to ongoing urbanization trends the worldwide urban population is projected to grow from half of the global population (today) to two thirds of it by 2030. Almost all the new megacities that will emerge through this process are in geopolitical hotspots of southeast Asia and sub-Saharan Africa. Therefore, the U.S. Department of Defense must consider the challenges presented by engagement in such environments when planning for the future. The physical challenge of operating in such dense, highly three-dimensional, environments is only compounded by the added challenge presented by the advanced functional complexity of these environments: megacities function at the intersection of the physical, social, and cyber spaces. Accordingly, military operations in these locations must prepare to engage in environments where news, ideas, and opinions are shaped in cyberspace and propagated across the physical urban landscape. As social networks connect (or, often, divide) populations they form communities and facilitate their mobilization.
We have observed these processes time and again, from the streets of Cairo during the Arab Spring, to the streets of Tokyo during the Fukushima nuclear disaster, and the streets of Paris during the recent ISIL terrorist attacks. Advancing our capability to analyze crowd-generated content in the form of social media feeds is a substantial scientific challenge with considerable implications for future DoD operations. In this publication, we use representative examples to demonstrate the opportunities and challenges associated with such information, especially as they relate to large urban areas.
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| An emerging framework to study urban systems. |
 |
| Social networks embedded within a geographical content, leading to connected, non-contiguous areas. |
Full Reference:
Continue reading »Stefanidis, A., Jenkins A., Croitoru, A. and Crooks, A. (2016). “Megacities Through the Lens of Social Media”, Journal of the Homeland Defense & Security Information Analysis Center (HDIAC), 3(1): 24-29. (pdf)
Megacities, which can be roughly defined as cities with a population of over 10 million people are on the increase due to ongoing urbanization trends. The United Nations notes that since the 1970’s the number of megacities has more than tripled (from 8 to 34), and is expected to further double until 2050 (to exceed 60).
The question we are wondering is how can GeoSocial analysis help understand such cities. To this end, we have recently had a paper published entitled: “Megacities: Through the Lens of Social Media” in the Journal of the Homeland Defense and Security Information Analysis Center (HDIAC). In the paper we discuss opportunities and challenges that social media brings with respect to understanding the physical and cyber spaces within megacities. Below you can see the synopsis to our paper.
Due to ongoing urbanization trends the worldwide urban population is projected to grow from half of the global population (today) to two thirds of it by 2030. Almost all the new megacities that will emerge through this process are in geopolitical hotspots of southeast Asia and sub-Saharan Africa. Therefore, the U.S. Department of Defense must consider the challenges presented by engagement in such environments when planning for the future. The physical challenge of operating in such dense, highly three-dimensional, environments is only compounded by the added challenge presented by the advanced functional complexity of these environments: megacities function at the intersection of the physical, social, and cyber spaces. Accordingly, military operations in these locations must prepare to engage in environments where news, ideas, and opinions are shaped in cyberspace and propagated across the physical urban landscape. As social networks connect (or, often, divide) populations they form communities and facilitate their mobilization.
We have observed these processes time and again, from the streets of Cairo during the Arab Spring, to the streets of Tokyo during the Fukushima nuclear disaster, and the streets of Paris during the recent ISIL terrorist attacks. Advancing our capability to analyze crowd-generated content in the form of social media feeds is a substantial scientific challenge with considerable implications for future DoD operations. In this publication, we use representative examples to demonstrate the opportunities and challenges associated with such information, especially as they relate to large urban areas.
|
| An emerging framework to study urban systems. |
|
| Social networks embedded within a geographical content, leading to connected, non-contiguous areas. |
Full Reference:
Continue reading »Stefanidis, A., Jenkins A., Croitoru, A. and Crooks, A. (2016). “Megacities Through the Lens of Social Media”, Journal of the Homeland Defense & Security Information Analysis Center (HDIAC), 3(1): 24-29. (pdf)
Organizers:
3445 Symposium on Human Dynamics Research: Urban Analytics (I)
Thursday, 3/31/2016, from 1:20 PM – 3:00 PM in Union Square 18, Hilton Hotel, 4th Floor
Chair:Nick Malleson
Talks:
Discussant: Mark Birkin
3545 Symposium on Human Dynamics Research: Urban Analytics (II)
Thursday, 3/31/2016, from 3:20 PM – 5:00 PM in Union Square 18, Hilton Hotel, 4th Floor
Chair: Paul Longley
Talks:
3645 Symposium on Human Dynamics Research: Urban Analytics (III)
Thursday, 3/31/2016, from 5:20 PM – 7:00 PM in Union Square 18, Hilton Hotel, 4th Floor
Chair: Andrew Crooks
Talks:
Discussant: Andrew Crooks
Continue reading »Organizers:
3445 Symposium on Human Dynamics Research: Urban Analytics (I)
Thursday, 3/31/2016, from 1:20 PM – 3:00 PM in Union Square 18, Hilton Hotel, 4th Floor
Chair:Nick Malleson
Talks:
Discussant: Mark Birkin
3545 Symposium on Human Dynamics Research: Urban Analytics (II)
Thursday, 3/31/2016, from 3:20 PM – 5:00 PM in Union Square 18, Hilton Hotel, 4th Floor
Chair: Paul Longley
Talks:
3645 Symposium on Human Dynamics Research: Urban Analytics (III)
Thursday, 3/31/2016, from 5:20 PM – 7:00 PM in Union Square 18, Hilton Hotel, 4th Floor
Chair: Andrew Crooks
Talks:
Discussant: Andrew Crooks
Continue reading »
We recently co-authored a paper entitled “Lessons from the Ebola Outbreak: Action Items for Emerging Infectious Disease Preparedness and Response” in EcoHealth” with several other researchers from George Mason University. In the paper we discuss t…
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We recently co-authored a paper entitled “Lessons from the Ebola Outbreak: Action Items for Emerging Infectious Disease Preparedness and Response” in EcoHealth” with several other researchers from George Mason University. In the paper we discuss t…
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This day-long workshop aims to serve as a platform to discuss and showcase the complex issues associated with the analysis of social media contributions in the context of GIScience.
Spanning spatial footprints, social networks, and sociocultural themes, such data can support a variety of applications, ranging from disaster response and environmental monitoring to health informatics and digital citizenship. Given their variations in accuracy, the complex patterns of participation, and the constantly increasing data volumes, analyzing such data in a meaningful, reliable, and timely manner is a substantial challenge. The objective of this workshop is to showcase on-going research in the GIScience community on the analysis of social media content and thus support the emergence of a cohesive research agenda in our community.
We invite submissions of short papers (1,500-2,000 words) that present research related to the workshop theme. Examples of topics of particular interest include:
Workshop Format:
Organizers:
Website: http://geosocialanalysis.blogspot.com/p/about.html
This day-long workshop aims to serve as a platform to discuss and showcase the complex issues associated with the analysis of social media contributions in the context of GIScience.
Spanning spatial footprints, social networks, and sociocultural themes, such data can support a variety of applications, ranging from disaster response and environmental monitoring to health informatics and digital citizenship. Given their variations in accuracy, the complex patterns of participation, and the constantly increasing data volumes, analyzing such data in a meaningful, reliable, and timely manner is a substantial challenge. The objective of this workshop is to showcase on-going research in the GIScience community on the analysis of social media content and thus support the emergence of a cohesive research agenda in our community.
We invite submissions of short papers (1,500-2,000 words) that present research related to the workshop theme. Examples of topics of particular interest include:
Workshop Format:
Organizers:
Website: http://geosocialanalysis.blogspot.com/p/about.html
Readers might know that we like pedestrian models here. So in keeping with the theme of NetLogo models and the use of GIS below are two simple pedestrian models. In the first model (shown in the movie below), agents just exit the room, taking the short…
Continue reading »
Readers might know that we like pedestrian models here. So in keeping with the theme of NetLogo models and the use of GIS below are two simple pedestrian models. In the first model (shown in the movie below), agents just exit the room, taking the short…
Continue reading »Readers of the blog might be interested in a workshop being organized by Daniel Brown, Eun-Kyeong Kim, Liliana Perez, and Raja Sengupta entitled:
To quote from the call:
“A broad scope of concepts and methodologies from complexity science – including Agent-Based Models, Cellular Automata, network theory, chaos theory, and scaling relations – has contributed to a better understanding of spatial/temporal dynamics of complex geographic patterns and process.
Recent advances in computational technologies such as Big Data, Cloud Computing and CyberGIS platforms, and Sensor Networks (i.e. the Internet of Things) provides both new opportunities and raises new challenges for ABM and complexity theory research within GIScience. Challenges include parameterization of complex models with volumes of georeferenced data being generated, scale model applications to realistic simulations over broader geographic extents, explore the challenges in their deployment across large networks to take advantage of increased computational power, and validate their output using real-time data, as well as measure the impact of the simulation on knowledge, information and decision-making both locally and globally via the world wide web.
The scope of this workshop is to explore novel complexity science approaches to dynamic geographic phenomena and their applications, addressing challenges and enriching research methodologies in geography in a Big Data Era.”
More information about the workshop can be found at https://sites.psu.edu/bigcomplexitygisci/
Continue reading »Readers of the blog might be interested in a workshop being organized by Daniel Brown, Eun-Kyeong Kim, Liliana Perez, and Raja Sengupta entitled:
To quote from the call:
“A broad scope of concepts and methodologies from complexity science – including Agent-Based Models, Cellular Automata, network theory, chaos theory, and scaling relations – has contributed to a better understanding of spatial/temporal dynamics of complex geographic patterns and process.
Recent advances in computational technologies such as Big Data, Cloud Computing and CyberGIS platforms, and Sensor Networks (i.e. the Internet of Things) provides both new opportunities and raises new challenges for ABM and complexity theory research within GIScience. Challenges include parameterization of complex models with volumes of georeferenced data being generated, scale model applications to realistic simulations over broader geographic extents, explore the challenges in their deployment across large networks to take advantage of increased computational power, and validate their output using real-time data, as well as measure the impact of the simulation on knowledge, information and decision-making both locally and globally via the world wide web.
The scope of this workshop is to explore novel complexity science approaches to dynamic geographic phenomena and their applications, addressing challenges and enriching research methodologies in geography in a Big Data Era.”
More information about the workshop can be found at https://sites.psu.edu/bigcomplexitygisci/
Continue reading »In the past I have blogged on how one can use Repast Simphony to get agents to move around a network, which also inspired a similar model in GeoMason (see here for the movie). Keeping with this theme Yang has recently finished a NetLogo model whe…
Continue reading »In the past I have blogged on how one can use Repast Simphony to get agents to move around a network, which also inspired a similar model in GeoMason (see here for the movie). Keeping with this theme Yang has recently finished a NetLogo model whe…
Continue reading »
Recently, Alison Heppenstall, Nick Malleson and myself have just had a paper accepted in Systems entitled: “Space, the Final Frontier”: How Good are Agent-Based Models at Simulating Individuals and Space in Cities?” In the paper we critically examine how well agent-based models have simulated a variety of urban processes. We discus what considerations are needed when choosing the appropriate level of spatial analysis and time frame to model urban phenomena and what role Big Data can play in agent-based modeling. Below you can read the abstract of the paper and see a number of example applications discussed.
Abstract: Cities are complex systems, comprising of many interacting parts. How we simulate and understand causality in urban systems is continually evolving. Over the last decade the agent-based modeling (ABM) paradigm has provided a new lens for understanding the effects of interactions of individuals and how through such interactions macro structures emerge, both in the social and physical environment of cities. However, such a paradigm has been hindered due to computational power and a lack of large fine scale datasets. Within the last few years we have witnessed a massive increase in computational processing power and storage, combined with the onset of Big Data. Today geographers find themselves in a data rich era. We now have access to a variety of data sources (e.g., social media, mobile phone data, etc.) that tells us how, and when, individuals are using urban spaces. These data raise several questions: can we effectively use them to understand and model cities as complex entities? How well have ABM approaches lent themselves to simulating the dynamics of urban processes? What has been, or will be, the influence of Big Data on increasing our ability to understand and simulate cities? What is the appropriate level of spatial analysis and time frame to model urban phenomena? Within this paper we discuss these questions using several examples of ABM applied to urban geography to begin a dialogue about the utility of ABM for urban modeling. The arguments that the paper raises are applicable across the wider research environment where researchers are considering using this approach.
Keywords: cities; agent-based modeling; big data; crime; retail; space; simulation
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| Figure 1. (A) System structure; (B) System hierarchy; and (C) Related subsystems/processes (adapted from Batty, 2013). |
Reference cited:
Batty, M. (2013). The New Science of Cities; MIT Press: Cambridge, MA, USA.
Full reference to the open access paper:
Heppenstall, A., Malleson, N. and Crooks A.T. (2016). “Space, the Final Frontier”: How Good are Agent-based Models at Simulating Individuals and Space in Cities?, Systems, 4(1), 9; doi: 10.3390/systems4010009 (pdf)
Continue reading »
Recently, Alison Heppenstall, Nick Malleson and myself have just had a paper accepted in Systems entitled: “Space, the Final Frontier”: How Good are Agent-Based Models at Simulating Individuals and Space in Cities?” In the paper we critically examine how well agent-based models have simulated a variety of urban processes. We discus what considerations are needed when choosing the appropriate level of spatial analysis and time frame to model urban phenomena and what role Big Data can play in agent-based modeling. Below you can read the abstract of the paper and see a number of example applications discussed.
Abstract: Cities are complex systems, comprising of many interacting parts. How we simulate and understand causality in urban systems is continually evolving. Over the last decade the agent-based modeling (ABM) paradigm has provided a new lens for understanding the effects of interactions of individuals and how through such interactions macro structures emerge, both in the social and physical environment of cities. However, such a paradigm has been hindered due to computational power and a lack of large fine scale datasets. Within the last few years we have witnessed a massive increase in computational processing power and storage, combined with the onset of Big Data. Today geographers find themselves in a data rich era. We now have access to a variety of data sources (e.g., social media, mobile phone data, etc.) that tells us how, and when, individuals are using urban spaces. These data raise several questions: can we effectively use them to understand and model cities as complex entities? How well have ABM approaches lent themselves to simulating the dynamics of urban processes? What has been, or will be, the influence of Big Data on increasing our ability to understand and simulate cities? What is the appropriate level of spatial analysis and time frame to model urban phenomena? Within this paper we discuss these questions using several examples of ABM applied to urban geography to begin a dialogue about the utility of ABM for urban modeling. The arguments that the paper raises are applicable across the wider research environment where researchers are considering using this approach.
Keywords: cities; agent-based modeling; big data; crime; retail; space; simulation
|
| Figure 1. (A) System structure; (B) System hierarchy; and (C) Related subsystems/processes (adapted from Batty, 2013). |
Reference cited:
Batty, M. (2013). The New Science of Cities; MIT Press: Cambridge, MA, USA.
Full reference to the open access paper:
Heppenstall, A., Malleson, N. and Crooks A.T. (2016). “Space, the Final Frontier”: How Good are Agent-based Models at Simulating Individuals and Space in Cities?, Systems, 4(1), 9; doi: 10.3390/systems4010009 (pdf)
Continue reading »
 |
| A summary of our approach |
Background: The emergence of social media is providing an alternative avenue for information exchange and opinion formation on health-related issues. Collective discourse in such media leads to the formation of a complex narrative, conveying public views and perceptions.
Objective: This paper presents a study of Twitter narrative regarding vaccination in the aftermath of the 2015 measles outbreak, both in terms of its cyber and physical characteristics. The contributions of this work are the analysis of the data for this particular study, as well as presenting a quantitative interdisciplinary approach to analyze such open-source data in the context of health narratives.
Methods: 669,136 tweets were collected in the period February 1 through March 9, 2015 referring to vaccination. These tweets were analyzed to identify key terms, connections among such terms, retweet patterns, the structure of the narrative, and connections to the geographical space.
Results: The data analysis captures the anatomy of the themes and relations that make up the discussion about vaccination in Twitter. The results highlight the higher impact of stories contributed by news organizations compared to direct tweets by health organizations in communicating health-related information. They also capture the structure of the anti-vaccination narrative and its terms of reference. Analysis also revealed the relationship between community engagement in Twitter and state policies regarding child vaccination. Residents of Vermont and Oregon, the two states with the highest rates of non-medical exemption from school-entry vaccines nationwide, are leading the social media discussion in terms of participation.
Conclusions: The interdisciplinary study of health-related debates in social media across the cyber-physical debate nexus leads to a greater understanding of public concerns, views, and responses to health-related issues. Further coalescing such capabilities shows promise towards advancing health communication, supporting the design of more effective strategies that take into account the complex and evolving public views of health issues.
 |
| Global distribution of tweets in our data corpus |
Radzikowski, J., Stefanidis, A., Jacobsen K.H., Croitoru, A., Crooks, A.T. and Delamater, P.L. (2016). “The Measles Vaccination Narrative in Twitter: A Quantitative Analysis”, JMIR Public Health and Surveillance, 2(1):e1.
 |
| Hashtag associations: clustering based on co-occurrences of hashtags in individual tweets |
|
| A summary of our approach |
Background: The emergence of social media is providing an alternative avenue for information exchange and opinion formation on health-related issues. Collective discourse in such media leads to the formation of a complex narrative, conveying public views and perceptions.
Objective: This paper presents a study of Twitter narrative regarding vaccination in the aftermath of the 2015 measles outbreak, both in terms of its cyber and physical characteristics. The contributions of this work are the analysis of the data for this particular study, as well as presenting a quantitative interdisciplinary approach to analyze such open-source data in the context of health narratives.
Methods: 669,136 tweets were collected in the period February 1 through March 9, 2015 referring to vaccination. These tweets were analyzed to identify key terms, connections among such terms, retweet patterns, the structure of the narrative, and connections to the geographical space.
Results: The data analysis captures the anatomy of the themes and relations that make up the discussion about vaccination in Twitter. The results highlight the higher impact of stories contributed by news organizations compared to direct tweets by health organizations in communicating health-related information. They also capture the structure of the anti-vaccination narrative and its terms of reference. Analysis also revealed the relationship between community engagement in Twitter and state policies regarding child vaccination. Residents of Vermont and Oregon, the two states with the highest rates of non-medical exemption from school-entry vaccines nationwide, are leading the social media discussion in terms of participation.
Conclusions: The interdisciplinary study of health-related debates in social media across the cyber-physical debate nexus leads to a greater understanding of public concerns, views, and responses to health-related issues. Further coalescing such capabilities shows promise towards advancing health communication, supporting the design of more effective strategies that take into account the complex and evolving public views of health issues.
|
| Global distribution of tweets in our data corpus |
Radzikowski, J., Stefanidis, A., Jacobsen K.H., Croitoru, A., Crooks, A.T. and Delamater, P.L. (2016). “The Measles Vaccination Narrative in Twitter: A Quantitative Analysis”, JMIR Public Health and Surveillance, 2(1):e1.
|
| Hashtag associations: clustering based on co-occurrences of hashtags in individual tweets |
For the last few years one of the classes that I have given is the Introduction to Computational Social Science (CSS). This is often the first class many students take within our program and as such its objectives are:To understand the motivation for t…
Continue reading »For the last few years one of the classes that I have given is the Introduction to Computational Social Science (CSS). This is often the first class many students take within our program and as such its objectives are:To understand the motivation for t…
Continue reading »Carrying on with the theme of linking GIS to NetLogo for creating agent-based models. We would like to showcase two simple models. Both are based on using a shapefile to create Schelling-inspired segregation model.In the first model (as shown in the mo…
Continue reading »Carrying on with the theme of linking GIS to NetLogo for creating agent-based models. We would like to showcase two simple models. Both are based on using a shapefile to create Schelling-inspired segregation model.In the first model (as shown in the mo…
Continue reading »
Now whats seems like a long time ago, we where inspired to by the NetLogo Grand Canyon Model and created a similar model in GeoMason. Now we have returned to NetLogo to test its ability to handle GIS data. Below you can see our attempt. The mode…
Continue reading »
Now whats seems like a long time ago, we where inspired to by the NetLogo Grand Canyon Model and created a similar model in GeoMason. Now we have returned to NetLogo to test its ability to handle GIS data. Below you can see our attempt. The mode…
Continue reading »
Readers of this blog might be interested in the following position.
Tenure-Track Assistant Professor, Computational Social Science
The George Mason University Computational and Data Sciences (CDS) Department in the College of Science invites applicants for a full-time, tenure-track faculty position at the Assistant Professor level.
Responsibilities:
Beginning Fall 2016, this position is intended to primarily support the Computational Social Science (CSS) Program within CDS, including support of the Ph.D. degree in CSS, a master’s degree in interdisciplinary studies, and a CSS certificate. This position will also support undergraduate programs that are currently under development.
Qualifications:
Potential for success in both research and teaching are the primary criteria for this position. Applicants should have a promising research record, with a deep knowledge of and interest in computation as applied to one or more of the social sciences. While we are open to expertise in all areas of computational social science, we are particularly interested in social network specialists interested in both theory and data. Applicants must have a Ph.D. (expected completion by August 2016 is acceptable) from an accredited institution.
About the Program:
Methodologically, the CSS Program focuses on data-driven social science models using social network and agent-based computational approaches from a complexity perspective. Current faculty members have domain expertise in economics and finance, political science and international relations, geography and geographic information systems, land use and cover change, and public policy. As one of the first programs of its type in the world, CSS has had significant success in both research and professional placement. Our students come from all over the world (the Americas, Europe, Africa, Asia and Australia) and have been placed at a variety of top universities (e.g., University of Oxford, University College London), at government agencies, as well as in the private sector, including start-up companies.
More Information:
Continue reading »
Readers of this blog might be interested in the following position.
Tenure-Track Assistant Professor, Computational Social Science
The George Mason University Computational and Data Sciences (CDS) Department in the College of Science invites applicants for a full-time, tenure-track faculty position at the Assistant Professor level.
Responsibilities:
Beginning Fall 2016, this position is intended to primarily support the Computational Social Science (CSS) Program within CDS, including support of the Ph.D. degree in CSS, a master’s degree in interdisciplinary studies, and a CSS certificate. This position will also support undergraduate programs that are currently under development.
Qualifications:
Potential for success in both research and teaching are the primary criteria for this position. Applicants should have a promising research record, with a deep knowledge of and interest in computation as applied to one or more of the social sciences. While we are open to expertise in all areas of computational social science, we are particularly interested in social network specialists interested in both theory and data. Applicants must have a Ph.D. (expected completion by August 2016 is acceptable) from an accredited institution.
About the Program:
Methodologically, the CSS Program focuses on data-driven social science models using social network and agent-based computational approaches from a complexity perspective. Current faculty members have domain expertise in economics and finance, political science and international relations, geography and geographic information systems, land use and cover change, and public policy. As one of the first programs of its type in the world, CSS has had significant success in both research and professional placement. Our students come from all over the world (the Americas, Europe, Africa, Asia and Australia) and have been placed at a variety of top universities (e.g., University of Oxford, University College London), at government agencies, as well as in the private sector, including start-up companies.
More Information:
Continue reading »
Recently Yang Zhou, a PhD student in the Computational Social Program carried out a partial re-implementation of the SLEUTH urban growth model (without Self Modification). The region of study is Santa Fe, New Mexico. The data was obtained from T…
Continue reading »
Recently Yang Zhou, a PhD student in the Computational Social Program carried out a partial re-implementation of the SLEUTH urban growth model (without Self Modification). The region of study is Santa Fe, New Mexico. The data was obtained from T…
Continue reading »
“Agent-based modeling is currently a hole in in Python’s robust and growing scientific ecosystem. Mesa is a new open-source package meant to fill that gap. It allows users to quickly create agent-based models using built-in core components (such as agent schedulers and spatial grids) or customized implementations; visualize them using an innovative browser-based interface; and analyze their results using Python’s robust data analysis tools. Its goal is to be a Python 3-based alternative to other popular frameworks based in other languages such as NetLogo, Repast, or MASON.”
Below is short presentation outlining Mesa from SciPy 2015:
Continue reading »
“Agent-based modeling is currently a hole in in Python’s robust and growing scientific ecosystem. Mesa is a new open-source package meant to fill that gap. It allows users to quickly create agent-based models using built-in core components (such as agent schedulers and spatial grids) or customized implementations; visualize them using an innovative browser-based interface; and analyze their results using Python’s robust data analysis tools. Its goal is to be a Python 3-based alternative to other popular frameworks based in other languages such as NetLogo, Repast, or MASON.”
Below is short presentation outlining Mesa from SciPy 2015:
Continue reading »
A deluge of new data created by people and machines is changing the way that we understand, organise and model urban spaces. New analytics are required to make sense of these data and to usefully apply findings to real systems. This session seeks to bring together quantitative or mixed methods papers that develop or use new analytics in order to better understand the form, function and future of urban systems. We invite methodological, theoretical and empirical papers that engage with any aspect of urban analytics. Topics include, but are not limited to:
Please e-mail the abstract and key words with your expression of intent to Nick Malleson (n.s.malleson@leeds.ac.uk) by 22nd October, 2015 (one week before the AAG session deadline). Please make sure that your abstract conforms to the AAG guidelines in relation to title, word limit and key words and as specified at:
http://www.aag.org/cs/annualmeeting/call_for_papers
An abstract should be no more than 250 words that describe the presentation’s purpose, methods, and conclusions.
A deluge of new data created by people and machines is changing the way that we understand, organise and model urban spaces. New analytics are required to make sense of these data and to usefully apply findings to real systems. This session seeks to bring together quantitative or mixed methods papers that develop or use new analytics in order to better understand the form, function and future of urban systems. We invite methodological, theoretical and empirical papers that engage with any aspect of urban analytics. Topics include, but are not limited to:
Please e-mail the abstract and key words with your expression of intent to Nick Malleson (n.s.malleson@leeds.ac.uk) by 22nd October, 2015 (one week before the AAG session deadline). Please make sure that your abstract conforms to the AAG guidelines in relation to title, word limit and key words and as specified at:
http://www.aag.org/cs/annualmeeting/call_for_papers
An abstract should be no more than 250 words that describe the presentation’s purpose, methods, and conclusions.
We recently had published in ISPRS International Journal of Geo-Information a paper entitled “Walk this Way: Improving Pedestrian Agent-Based Models through Scene Activity Analysis”. In the paper we explore how new data can help inform our agent-based…
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