A Review of High and Very High Resolution Remote Sensing Approaches for Detecting and Mapping Slums

Regular readers of this site might of noticed that we have an interest in slums. In the past this has focused on modeling them from an agent-based perspective, comparing volunteered geographical information to more authoritative data on slums, to that …

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A Review of High and Very High Resolution Remote Sensing Approaches for Detecting and Mapping Slums

Regular readers of this site might of noticed that we have an interest in slums. In the past this has focused on modeling them from an agent-based perspective, comparing volunteered geographical information to more authoritative data on slums, to that …

Continue reading »

New Paper: Cancer and Social Media

Continuing our work on geosocial analysis we recently had a paper entitled “Cancer and Social Media: A Comparison of Traffic about Breast Cancer, Prostate Cancer, and Other Reproductive Cancers on Twitter and Instagram” published in the Journal of Health Communication. In the paper we  present a comparative study of differences in messaging for women’s and men’s cancer campaigns on social media through three discrete approaches. 
  1. we directly compare the incident rates of women’s and men’s cancers in the United States to the corresponding levels of traffic that these cancers elicited during World Cancer Day across two social media platforms, Twitter and Instagram. 
  2. we examine social media activity for breast cancer versus prostate cancer on both Twitter and Instagram during the dedicated month-long campaigns (October and November, respectively). 
  3. we compare the top terms associated with each campaign on these two social media platforms to discover whether there are differences in the terms associated with these online discussions.
Below you can read the abstract to our paper, see some of our results and at the bottom of the post have the full citation and link to the paper.

Abstract: 

Social media are often heralded as offering cancer campaigns new opportunities to reach the public. However, these campaigns may not be equally successful, depending on the nature of the campaign itself, the type of cancer being addressed, and the social media platform being examined. This study is the first to compare social media activity on Twitter and Instagram across three time periods: #WorldCancerDay in February, the annual month-long campaigns of National Breast Cancer Awareness Month (NBCAM) in October and Movember in November, and during the full year outside of these campaigns. Our results suggest that women’s reproductive cancers – especially breast cancer – tend to outperform men’s reproductive cancer – especially prostate cancer – across campaigns and social media platforms. Twitter overall generates substantially more activity than Instagram for both cancer campaigns, suggesting Instagram may be an untapped resource. However, the messaging for both campaigns tends to focus on awareness and support rather than on concrete actions and behaviors. We suggest health communication efforts need to focus on effective messaging and building engaged communities for cancer communication across social media platforms.

A comparison of percentages of cancer cases (green bars) and references to corresponding cancers in Twitter (blue bar) and Instagram (orange bar) during World Cancer Day 2016.

 References to breast cancer (green line), prostate cancer (orange line), and Movember (blue line) over the full year 2015 in Instagram.

Full Reference: 

Vraga, E., Stefanidis, A., Lamprianidis, G., Croitoru, A., Crooks, A.T. Delamater, P.L., Pfoser, D., Radzikowski, J. and Jacobsen, K.H. (2018), Cancer and Social Media: A Comparison of Traffic about Breast Cancer, Prostate Cancer, and Other Reproductive Cancers on Twitter and Instagram, Journal of Health Communication. 3(2), 181-189. (pdf)

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New Paper: Cancer and Social Media

Continuing our work on geosocial analysis we recently had a paper entitled “Cancer and Social Media: A Comparison of Traffic about Breast Cancer, Prostate Cancer, and Other Reproductive Cancers on Twitter and Instagram” published in the Journal of Health Communication. In the paper we  present a comparative study of differences in messaging for women’s and men’s cancer campaigns on social media through three discrete approaches. 
  1. we directly compare the incident rates of women’s and men’s cancers in the United States to the corresponding levels of traffic that these cancers elicited during World Cancer Day across two social media platforms, Twitter and Instagram. 
  2. we examine social media activity for breast cancer versus prostate cancer on both Twitter and Instagram during the dedicated month-long campaigns (October and November, respectively). 
  3. we compare the top terms associated with each campaign on these two social media platforms to discover whether there are differences in the terms associated with these online discussions.
Below you can read the abstract to our paper, see some of our results and at the bottom of the post have the full citation and link to the paper.

Abstract: 

Social media are often heralded as offering cancer campaigns new opportunities to reach the public. However, these campaigns may not be equally successful, depending on the nature of the campaign itself, the type of cancer being addressed, and the social media platform being examined. This study is the first to compare social media activity on Twitter and Instagram across three time periods: #WorldCancerDay in February, the annual month-long campaigns of National Breast Cancer Awareness Month (NBCAM) in October and Movember in November, and during the full year outside of these campaigns. Our results suggest that women’s reproductive cancers – especially breast cancer – tend to outperform men’s reproductive cancer – especially prostate cancer – across campaigns and social media platforms. Twitter overall generates substantially more activity than Instagram for both cancer campaigns, suggesting Instagram may be an untapped resource. However, the messaging for both campaigns tends to focus on awareness and support rather than on concrete actions and behaviors. We suggest health communication efforts need to focus on effective messaging and building engaged communities for cancer communication across social media platforms.

A comparison of percentages of cancer cases (green bars) and references to corresponding cancers in Twitter (blue bar) and Instagram (orange bar) during World Cancer Day 2016.

 References to breast cancer (green line), prostate cancer (orange line), and Movember (blue line) over the full year 2015 in Instagram.

Full Reference: 

Vraga, E., Stefanidis, A., Lamprianidis, G., Croitoru, A., Crooks, A.T. Delamater, P.L., Pfoser, D., Radzikowski, J. and Jacobsen, K.H. (2018), Cancer and Social Media: A Comparison of Traffic about Breast Cancer, Prostate Cancer, and Other Reproductive Cancers on Twitter and Instagram, Journal of Health Communication. 3(2), 181-189. (pdf)

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Come Work with Us: 2 Postdocs in Urban Simulation

The George Mason University Department of Geography and Geoinformation Science within the College of Science, has an immediate opening for two postdoctoral fellows (up to 2-years), subject to budgetary approval. These positions will be part of the “Urban simulation” project team conducting research as part of the DARPA’s “Ground Truth” program, a network of DARPA-funded teams across the USA. The GMU team is directed by Andreas Züfle, Dieter Pfoser, and Andrew Crooks and supported by Carola Wenk at Tulane University. George Mason University has a strong institutional commitment to the achievement of excellence and diversity among its faculty and staff, and strongly encourages candidates to apply who will enrich Mason’s academic and culturally inclusive environment.

Postdoc 1

Responsibilities:
The primary job responsibilities of this position consist of the design, development and refinement of an agent-based simulation framework for urban areas. Using the existing Multiagent Simulation Toolkit (MASON) platform (written in Java), new agent logic will have to be implemented, thus creating agents that use socially plausible rules for mobility and interaction with other agents. A main goal is to create computationally efficient agent logic, thus allowing millions of agents to make decisions, find shortest paths between locations, and interact with their simulated world at the same time. For this purpose, implemented algorithms will need to be highly parallelizable, thus allowing to scale simulation via distribution among computing clusters located at GMU and Tulane. The successful candidate will also supervise graduate-level research assistants, collaborate with fellow scholars, and promote the department’s accomplishments through publications, presentations, and other public events.

Required Qualifications:

  • Ph.D. in computer science, data science, or closely related field;
  • Strong programming skills in Java;
  • Excellent written communication skills demonstrated by prior publications;
  • A track record that demonstrates the ability to work well with interdisciplinary research teams.
Preferred Qualifications:
  • Solid knowledge of graph algorithms;
  • Experience with Agent-Based Modeling and social science simulation;
  • Experience in design and implementation of software systems.
Postdoc 2
Responsibilities:
The primary job responsibilities of this position will be the design of an agent-based model based on the first principles underlying human needs, social interactions, and mobility to define socially plausible causalities. This model will contribute towards the design, development and refinement of an agent-based simulation framework for urban areas. Using the existing Multiagent Simulation Toolkit (MASON) platform (written in Java), new agent logic will have to be implemented, thus creating agents that use socially plausible rules for mobility and interaction with other agents. The successful candidate will also supervise graduate-level research assistants, collaborate with fellow scholars, and promote the department’s accomplishments through publications, presentations, and other public events.

Required Qualifications:

  • Ph.D. in computer science, data science, or closely related field; 
  • Experience with Agent-Based Modeling and social science simulation; 
  • Excellent written communication skills demonstrated by prior publications; 
  • A track record that demonstrates the ability to work well with interdisciplinary research teams.
Preferred Qualifications:
  • Strong programming skills in Java;

More Information: https://jobs.gmu.edu/postings/42109

    Continue reading »

    Come Work with Us: 2 Postdocs in Urban Simulation

    The George Mason University Department of Geography and Geoinformation Science within the College of Science, has an immediate opening for two postdoctoral fellows (up to 2-years), subject to budgetary approval. These positions will be part of the “Urban simulation” project team conducting research as part of the DARPA’s “Ground Truth” program, a network of DARPA-funded teams across the USA. The GMU team is directed by Andreas Züfle, Dieter Pfoser, and Andrew Crooks and supported by Carola Wenk at Tulane University. George Mason University has a strong institutional commitment to the achievement of excellence and diversity among its faculty and staff, and strongly encourages candidates to apply who will enrich Mason’s academic and culturally inclusive environment.

    Postdoc 1

    Responsibilities:
    The primary job responsibilities of this position consist of the design, development and refinement of an agent-based simulation framework for urban areas. Using the existing Multiagent Simulation Toolkit (MASON) platform (written in Java), new agent logic will have to be implemented, thus creating agents that use socially plausible rules for mobility and interaction with other agents. A main goal is to create computationally efficient agent logic, thus allowing millions of agents to make decisions, find shortest paths between locations, and interact with their simulated world at the same time. For this purpose, implemented algorithms will need to be highly parallelizable, thus allowing to scale simulation via distribution among computing clusters located at GMU and Tulane. The successful candidate will also supervise graduate-level research assistants, collaborate with fellow scholars, and promote the department’s accomplishments through publications, presentations, and other public events.

    Required Qualifications:

    • Ph.D. in computer science, data science, or closely related field;
    • Strong programming skills in Java;
    • Excellent written communication skills demonstrated by prior publications;
    • A track record that demonstrates the ability to work well with interdisciplinary research teams.
    Preferred Qualifications:
    • Solid knowledge of graph algorithms;
    • Experience with Agent-Based Modeling and social science simulation;
    • Experience in design and implementation of software systems.
    Postdoc 2
    Responsibilities:
    The primary job responsibilities of this position will be the design of an agent-based model based on the first principles underlying human needs, social interactions, and mobility to define socially plausible causalities. This model will contribute towards the design, development and refinement of an agent-based simulation framework for urban areas. Using the existing Multiagent Simulation Toolkit (MASON) platform (written in Java), new agent logic will have to be implemented, thus creating agents that use socially plausible rules for mobility and interaction with other agents. The successful candidate will also supervise graduate-level research assistants, collaborate with fellow scholars, and promote the department’s accomplishments through publications, presentations, and other public events.

    Required Qualifications:

    • Ph.D. in computer science, data science, or closely related field; 
    • Experience with Agent-Based Modeling and social science simulation; 
    • Excellent written communication skills demonstrated by prior publications; 
    • A track record that demonstrates the ability to work well with interdisciplinary research teams.
    Preferred Qualifications:
    • Strong programming skills in Java;

    More Information: https://jobs.gmu.edu/postings/42109

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      AAG2018: Innovations in Urban Analytics

      Call for Papers, AAG2018: Innovations in Urban Analytics

      We welcome paper submissions for our session at the Association of American Geographers Annual Meeting on 10-14 April, 2018, in New Orleans.

      Session Description

      New forms of data about people and cities, often termed ‘Big’, are fostering research that is disrupting many traditional fields. This is true in geography, and especially in those more technical branches of the discipline such as computational geography / geocomputation, spatial analytics and statistics, geographical data science, etc. These new forms of micro-level data have lead to new methodological approaches in order to better understand how urban systems behave. Increasingly, these approaches and data are being used to ask questions about how cities can be made more sustainable and efficient in the future.

      This session will bring together the latest research in urban analytics. We are particularly interested in papers that engage with the following domains:

      • Agent-based modelling (ABM) and individual-based modelling;
      • Machine learning for urban analytics;
      • Innovations in consumer data analytics for understanding urban systems;
      • Real-time model calibration and data assimilation;
      • Spatio-temporal data analysis;
      • New data, case studies, demonstrators, and tools for the study of urban systems;
      • Complex systems analysis;
      • Geographic data mining and visualization;
      • Frequentist and Bayesian approaches to modelling cities.

      Please e-mail the abstract and key words with your expression of intent to Nick Malleson (n.s.malleson@leeds.ac.uk) by 18 October, 2017 (one week before the AAG abstract 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://annualmeeting.aag.org/submit_an_abstract. An abstract should be no more than 250 words that describe the presentation’s purpose, methods, and conclusions.

      For those interested specifically in the interface between research and policy, they might consider submitting their paper to the session “Computation for Public Engagement in Complex Problems” (http://www.gisagents.org/2017/10/call-for-papers-computation-for-public.html).

      Key Dates
      • 18 October, 2017: 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.
      • 23 October, 2017: Session finalization and author notification.
      • 25 October, 2017: Final abstract submission to AAG, via the link above. 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 (n.s.malleson@leeds.ac.uk). Neither the organizers nor the AAG will edit the abstracts.
      • 8 November, 2017: AAG session organization deadline. Sessions submitted to AAG for approval.
      • 9-14 April, 2018: AAG Annual Meeting.
      Session Organizers
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