Showing posts with label GeoSocial. Show all posts
Showing posts with label GeoSocial. Show all posts

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)

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. 

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)

Friday, March 07, 2014

Comparing the spatial characteristics cyber and physical communities

Readers of the blog know that I have an interest in social media, and how through it we can gain an understanding of society at large. The question is how does the cyber community reflect the corresponding physical community? To this end, papers from 6th ACM SIGSPATIAL International Workshop on Location-Based Social Networks which was held in conjunction with the 21st ACM SIGSPATIAL conference have just come out on the  ACM Digital Library. We presented a paper at the conference entitled "Comparing the Spatial Characteristics of Corresponding Cyber and Physical Communities: A Case Study" The abstract of the paper is as follows:

"The proliferation of social media over the past few years is presenting us with unique opportunities to sample opinions and interests at spatial and temporal resolutions previously unheard of. In order to make best use of this information though, we need a better understanding of the degree to which the cyber community that is observed through them can serve as a proxy for the corresponding physical community. In this paper we are making a contribution towards this issue by presenting a case study in which we compare spatial characteristics of a community both in the physical and cyber spaces. The key findings of our analysis relate to the selection of an appropriate level of spatial aggregation for analyzing social media content, and on the effect in the level of participation of the distance from the point of interest."

We hope you enjoy it.

Full reference: 
  • Lu, X., Croitoru, A., Radzikowski, J, Crooks, A. T. and Stefanidis, A. (2013), Comparing the Spatial Characteristics of Corresponding Cyber and Physical Communities: A Case Study, 6th ACM SIGSPATIAL International Workshop on Location-Based Social Networks, Orlando, FL, pp 11-14. (pdf)

Tuesday, February 25, 2014

Geoinformatics and Social Media: A New Big Data Challenge

We recently contributed a chapter to "Big Data: Techniques and Technologies in Geoinformatics" entitled "Geoinformatics and Social Media: A New Big Data Challenge" where we explore how social media and ambient geographic information is transforming geoinformatics. We discuss the key characteristics of big geosocial data beofre moving onto geosocial complexity.  Specifically how goeosocial data is predominantly linked information; links are established among users to establish a social network and among words to define a storyline that is communicated through pieces of information. Aggregating all these connections (links) provides us with a view of the users as a structured, networked community that can be represented as a graph. We then turn to modeling and analyzing geosocial multimedia before concluding with an outlook pertaining to the grand challenges and opportunities for big geosocial data.

Full reference:
Croitoru, A., Crooks, A.T., Radzikowski, J., Stefanidis, A., Vatsavai, R. R. and Wayant, N. (2014), Geoinformatics and Social Media: A New Big Data Challenge, in Karimi, H. (ed.), Big Data Techniques and Technologies in Geoinformatics. CRC Press, Boca Raton, FL, pp. 207-232. (pdf)

Monday, October 21, 2013

IR: State-Driven and Citizen-Driven Networks

Our work exploring how social media can be used to study events around the world has resulted in a new publication in the  Social Science Computer Review entitled "International Relations: State-Driven and Citizen-Driven Networks." In essence what we are attempting to do is compare traditional international relations (e.g. from the United Nations General Assembly voting patterns) to those arising from the bottom up interactions (i.e from people on the ground). The abstract of the paper is below along with some of the images that accompany the paper.
The international community can be viewed as a set of networks, manifested through various transnational activities. The availability of longitudinal datasets such as international arms trades and United Nations General Assembly (UNGA) allows for the study of state-driven interactions over time. In parallel to this top-down approach, the recent emergence of social media is fostering a bottom-up and citizen driven avenue for international relations (IR). The comparison of these two network types offers a new lens to study the alignment between states and their people. This paper presents a network-driven approach to analyze communities as they are established through different forms of bottom-up (e.g. Twitter) and top-down (e.g. UNGA voting records and international arms trade records) IR. By constructing and comparing different network communities we were able to evaluate the similarities between state-driven and citizen-driven networks. In order to validate our approach we identified communities in UNGA voting records during and after the Cold War. Our approach showed that the similarity between UNGA communities during and after the Cold War was 0.55 and 0.81 respectively (in a 0-1 scale). To explore the state- versus citizen-driven interactions we focused on the recent events within Syria within Twitter over a sample period of one month. The analysis of these data show a clear misalignment (0.25) between citizen-formed international networks and the ones established by the Syrian government (e.g. through its UNGA voting patterns).

Full reference:
Crooks, A.T., Masad, D., Croitoru, A., Cotnoir, A., Stefanidis, A. and Radzikowski, J. (2013), International Relations: State-Driven and Citizen-Driven Networks, Social Science Computer Review. DOI:10.1177/0894439313506851
If you don't have access to Social Science Computer Review, send us an email and we can send you an early version of the paper. This is also only part of our work on using multiple networks to explore international relations. One can of course also explore the networks in more detail. For example in the figure below we plot the actual transfer of arms between states during the 2001 and 2011 period. One can clearly see how different states are connected with Syria however, Russia has connections to many states.

Arms transfers

Or if we explore Twitter hastags and add an edge between any pair of hashtags when they are used in the same tweet we can explore an emergent ontology of topic labels users associate with each other. For example, the #Allepo hashtag is associated with other hashtags which appear to local events, including “#civilian”, “#airstrike”, “#hunger”, “#pictures”, many of which are only connected to the #Aleppo hashtag as shown below.

Thursday, September 19, 2013

Work featured in IQT Quarterly

Two of our recent papers have been  featured in IQT Quarterly. The first looks at completeness and error in VGI and the second features some of our work on social media and polycentric communities. The papers have been significantly shortened and edited and make easy reading (that's not to say the original papers were difficult to read :). For those not familiar with IQT Quarterly, it  is a publication from In-Q-Tel which: 
"was created to bridge the gap between the technology needs of the U.S. Intelligence Community (IC) and emerging commercial innovation".
Full References:
Stefanidis, A., Cotnoir, A., Croitoru, A., Crooks, A.T., Radzikowski, J. and Rice, M. (2013), Demarcating New Boundaries: Mapping Virtual Polycentric Communities through Social Media Content, IQT Quarterly, 5 (2): 12-14. (pdf)

Jackson, S. P., Mullen W., Agouris, P., Crooks, A. T., Croitoru, A. and Stefanidis, A. (2013), Assessing Completeness and Spatial Error of Features in Volunteered Geographic Information, IQT Quarterly, 5 (2): 22-26. (pdf)

Sunday, September 15, 2013

Geosocial Gauge Paper

As regular readers of the blog know, we have been spending a lot of time recently looking at social media and the growth in locational information within such media. To this end we are very happy to see one of our papers appear in the International Journal of Geographical Information Science. The paper is entitled "GeoSocial Gauge: A System Prototype for Knowledge Discovery from Social Media" which in essence discusses the challenge of merging diverse social media datasets into a single database which can then be used to generate geosocial knowledge. Below is the abstract:
"The remarkable success of online social media sites marks a shift in the way people connect and share information. Much of this information now contains some form of geographical content because of the proliferation of location-aware devices, thus fostering the emergence of geosocial media – a new type of user-generated geospatial information. Through geosocial media we are able, for the first time, to observe human activities in scales and resolutions that were so far unavailable. Furthermore, the wide spectrum of social media data and service types provides a multitude of perspectives on real-world activities and happenings, thus opening new frontiers in geosocial knowledge discovery. However, gleaning knowledge from geosocial media is a challenging task, as they tend to be unstructured and thematically diverse. To address these challenges, this article presents a system prototype for harvesting, processing, modeling, and integrating heterogeneous social media feeds towards the generation of geosocial knowledge. Our article addresses primarily two key components of this system prototype: a novel data model for heterogeneous social media feeds and a corresponding general system architecture. We present these key components and demonstrate their implementation in our system prototype, GeoSocial Gauge."

Full reference:
Croitoru, A., Crooks, A.T., Radzikowski, J. and Stefanidis, A. (in press), GeoSocial Gauge: A System Prototype for Knowledge Discovery from Social Media, International Journal of Geographical Information Science. DOI: 10.1080/13658816.2013.825724

If you don't have access to IGIS, send us an email and we can send you an early version of the paper.

Friday, May 10, 2013

Tweets from President Obama's inauguration 2013-01-21

Following on from a previous post on agent-based modeling and elections. Here we show geo-located tweets during the day of President Obama's inauguration 2013-01-21.

If you want to explore what people are currently saying about President Obama check out our Geosocial Gauge Website.

Screen shot of Geo social Gauge. Clockwise from top left: Location of tweets, basic sentiment of tweets (green positive, red: negative and gray: neutral), most active countries tweeting and a word cloud of the most popular words in the tweets.

Monday, April 08, 2013

GeoSocial Gauge

Over the last couple of months we have been working on getting our GeoSocial Gauge system up and running. The idea behind the website is to bring together social media and geographical analysis to monitor and explore people’s views, reactions, and interactions through space and time. It takes advantage of the emergence of social media to observe the human landscape as the living, breathing organism that it is: we can witness the explosion-like dissemination of information within a society, or the clusters of individuals who share common opinions or attitudes, and map the locations of these clusters. This is an unprecedented development that broadens drastically our understanding of the way that people act, react to events, and interact with each other and with their environment. We refer to this novel approach to study the integration of geography and society as GeoSocial Analysis.

The GeoSocial Gauge has several live streams ranging from exploring the political issues (e.g. Sequester) to to see what people are tweeting about TV (The Walking Dead).

Screen shot of GeoSocial Gauge of the Sequester. Showing the location of tweets, the most frequent words and whether or not the messages are positive (green) or negative (red).
Screen shot of GeoSocial Gauge of The Walking Dead.
Some of our initial work on this type of analyis can be found at:
  • Stefanidis, T., Crooks, A.T. and Radzikowski, J. (2013), Harvesting Ambient Geospatial Information from Social Media Feeds, GeoJournal, 78, (2): 319-338.
  • Crooks, A.T., Croitoru, A., Stefanidis, A. and Radzikowski, J. (2013), #Earthquake: Twitter as a Distributed Sensor System, Transactions in GIS, 17(1): 124-147.

Tuesday, January 29, 2013

New Paper: Demarcating New Boundaries

We have just been informed that our paper entitled "Demarcating New Boundaries: Mapping Virtual Polycentric Communities through Social Media Content" has been accepted in Cartography and Geographic Information Science (CaGIS).

A point density analysis revealing hotspots in geolocated tweets.

The abstract for the paper is:
The proliferation of social media has led to the emergence of a new type of geospatial information that defies the conventions of authoritative or volunteered geographic information, yet can be harvested to reveal unique and dynamic information about people and their activities. In this paper we address the identification and mapping of global virtual communities formed around issues of specific national interest. We refer to these connected virtual communities formed around issues related to a specific state as the polycentric virtual equivalent of that state. Identifying, mapping, and analyzing these virtual communities is a novel challenge for our community, and this is the subject we pursue in this paper. We present these communities relative to established conventions of statehood, address the harvesting of relevant geographical information from social media feeds, and discuss the challenge of visualizing such information. In order to do so we use the current geopolitical situation in Syria as a demonstrative example. 
Below are some additional images from the paper.

The user interface of our system prototype to harvest, map, and analyze streaming Twitter feeds. 

A network representation of the polycentric virtual Syria as it is captured using Twitter feeds for the period July 10-17, 2012 using a population-normalized participation indices. The size of the nodes indicates level of participation in the corresponding model.

Update 10th of May, 2013: Our paper is now out and made the front cover of Cartography and Geographic Information Science.

Full reference: Stefanidis, A., Cotnoir, A., Croitoru, A., Crooks, A.T., Radzikowski, J. and Rice, M. (2013), Demarcating New Boundaries: Mapping Virtual Polycentric Communities through Social Media Content, Cartography and Geographic Information Science, 40(2): 116-129. (pdf)