The recent COVID-19 pandemic has brought the debate around vaccinations to the forefront of publi... more The recent COVID-19 pandemic has brought the debate around vaccinations to the forefront of public discussion. In this discussion, various social media platforms have a key role. While this has long been recognized, the way by which the public assigns attention to such topics remains largely unknown. Furthermore, the question of whether there is a discrepancy between people's opinions as expressed online and their actual decision to vaccinate remains open. To shed light on this issue, in this paper we examine the dynamics of online debates among four prominent vaccines (i.e., COVID-19, Influenza, MMR, and HPV) through the lens of public attention as captured on Twitter in the United States from 2015 to 2021. We then compare this to actual vaccination rates from governmental reports, which we argue serve as a proxy for real-world vaccination behaviors. Our results demonstrate that since the outbreak of COVID-19, it has come to dominate the vaccination discussion, which has led to a redistribution of attention from the other three vaccination themes. The results also show an apparent discrepancy between the online debates and the actual vaccination rates. These findings are in line with existing theories, that of agenda-setting and zero-sum theory. Furthermore, our approach could be extended to assess the public's attention toward other health-related issues, and provide a basis for quantifying the effectiveness of health promotion policies.
Proceedings of the 7th 2016 International Conference on Social Media & Society - SMSociety '16, 2016
Social media platforms have become extremely popular during the past few years, presenting an alt... more Social media platforms have become extremely popular during the past few years, presenting an alternate, and often preferred, avenue for information dissemination within massive global communities. Such user-generated multimedia content is emerging as a critical source of information for a variety of applications, and particularly during times of crisis. In order to fully explore this potential, there is a need to better assess, and improve when possible, the accuracy of such information. This paper addresses this issue by focusing in particular on user-contributed image tagging in Flickr. We use as case study a natural disaster event (wildfire), and assess the reliability of user-generated tags. Furthermore, we compare these data to the results of a content-based annotation approach in order to assess the potential performance of an alternative, user-independent, automated approach to annotate such imagery. Our results show that Flickr user annotations can be considered quite reliable (at the level of ~50%), and that using a spatially distributed training dataset for our content-based image retrieval (CBIR) annotation process improves the performance of the content-based image labeling (to the level of ~75%).
As spatial data becomes a central component in a variety of applications, the demand for up-to-da... more As spatial data becomes a central component in a variety of applications, the demand for up-to-date data is on the rise. In order to shorten the updating cycle time local updating is preferred, in which patches of up-to-date data must be incorporated into the existing data set. Although this can be done by using a global transformation model or a rubber-sheeting scheme, it is argued that in the case of patch-based updating the accuracy relations and its spatial variations must be considered. This requires adopting a field ...
International Archives of Photogrammetry and Remote Sensing, 2000
The requirement for maintaining up-to-date spatial data originates both from the end-user and fro... more The requirement for maintaining up-to-date spatial data originates both from the end-user and from the information provider, since inability to do so may result in reluctance to utilize the data. Maintaining up-to-date spatial data may be performed either by completely remapping the area of interest (a global strategy) or by a local updating cycle, in which limited areas (³patches) in the existing data set are updated according to need (a local strategy). When implementing the local strategy, two prerequisites must be fulfilled. The ...
Mass shootings, like other extreme events, have long garnered public curiosity and, in turn, sign... more Mass shootings, like other extreme events, have long garnered public curiosity and, in turn, significant media coverage. The media framing, or topic focus, of mass shooting events typically evolves over time from details of the actual shooting to discussions of potential policy changes (e.g., gun control, mental health). Such media coverage has been historically provided through traditional media sources such as print, television, and radio, but the advent of online social networks (OSNs) has introduced a new platform for accessing, producing, and distributing information about such extreme events. The ease and convenience of OSN usage for information within society’s larger growing reliance upon digital technologies introduces potential unforeseen risks. Social bots, or automated software agents, are one such risk, as they can serve to amplify or distort potential narratives associated with extreme events such as mass shootings. In this paper, we seek to determine the prevalence an...
Location and time are critical to the success of many organizations’ missions. Sensors, software,... more Location and time are critical to the success of many organizations’ missions. Sensors, software, processors, vehicles, and human analysts work together to accomplish these tasks of detecting and identifying specific entities as quickly as possible for these missions. This work aims to make a contribution by providing a team-based detection and identification performance model incorporating the theory of Distributed Situational Awareness (DSA) and its effect on completing a specific task. The task being the ability to detect and identify a specific entity within a complex urban environment. Conditions to accomplish the task is the utilization of two unmanned aerial vehicles mounted with electrooptical sensors, operated by two analysts, creating a team to execute this task. Our results provide an additional resource on the how technology and training might be utilized to find the best performance given these certain conditions and missions. A highly trained team might improve their performance with this technology, or a team with low training could perform at a high level given the appropriate technology in limited time scenarios. More importantly, the model presented in this paper provides an evaluation tool to compare new technologies and their impact on teams. Specifically, it enables answering questions, such as: is an investment in new technology appropriate if investing in additional training produces the same performance results? Future performance can also be evaluated based on the team’s level of training and use of technology for these specific tasks.
Using geolocated tweets to achieve situational awareness is an often researched topic in disaster... more Using geolocated tweets to achieve situational awareness is an often researched topic in disaster and emergency management. However, little has been done in the area of drug cartels, which, as transnational crime organizations, continue to pose great risk to the stability and safety of our communities. This paper made an initial effort in using geolocated social media (specifically Twitter) to achieve situational awareness of drug cartels through temporal and spatial analysis of derived named entity clusters. The results show that detecting peaks in the time series of frequently occurring entity clusters enabled the tracking of important events in public discourse surrounding drug cartels. Correlations between time series also provided valuable insights into the synchronicity between different events. Further examining the spatial distribution of key events for different countries, we identify thematic hotpots of public discourse on cartel activity. Our methodology also addresses issues of language ambiguity when working with noisy social media data in order to achieve situational awareness on drug cartels.
Participants will leave the session with concrete ideas and examples for materials that might be ... more Participants will leave the session with concrete ideas and examples for materials that might be included in their dossiers as part of the reappointment, renewal, promotion, and/or tenure processes.
Abstract: Pedestrian movement is woven into the fabric of urban regions. With more people living ... more Abstract: Pedestrian movement is woven into the fabric of urban regions. With more people living in cities than ever before, there is an increased need to understand and model how pedestrians utilize and move through space for a variety of applications, ranging from urban planning and architecture to security. Pedestrian modeling has been traditionally faced with the challenge of collecting data to calibrate and validate such models of pedestrian movement. With the increased availability of mobility datasets from video surveillance and enhanced geolocation capabilities in consumer mobile devices we are now presented with the opportunity to change the way we build pedestrian models. Within this paper we explore the potential that such information offers for the improvement of agent-based pedestrian models. We introduce a Scene- and Activity-Aware Agent-Based Model (SA2-ABM), a method for harvesting scene activity information in the form of spatiotemporal trajectories, and incorporate...
The emergence of social media has provided the public with an effective and irrepressible real-ti... more 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 cyberspac...
Social media content analysis often focuses on just the words used in documents or by users and o... more Social media content analysis often focuses on just the words used in documents or by users and often overlooks the structural components of document composition and linguistic style. We propose that document structure and emoji use are also important to consider as they are impacted by individual communication style preferences and social norms associated with user role and intent, topic domain, and dissemination platform. In this paper we introduce and demonstrate a novel methodology to conduct structural content analysis and measure user consistency of document structures and emoji use. Document structure is represented as the order of content types and number of features per document and emoji use is characterized by the attributes, position, order, and repetition of emojis within a document. With these structures we identified user signatures of behavior, clustered users based on consistency of structures utilized, and identified users with similar document structures and emoji...
The recent Zika outbreak witnessed the disease evolving from a regional health concern to a globa... more The recent Zika outbreak witnessed the disease evolving from a regional health concern to a global epidemic. During this process, different communities across the globe became involved in Twitter, discussing the disease and key issues associated with it. This paper presents a study of this discussion in Twitter, at the nexus of location, actors, and concepts. Our objective in this study was to demonstrate the significance of 3 types of events: location related, actor related, and concept related, for understanding how a public health emergency of international concern plays out in social media, and Twitter in particular. Accordingly, the study contributes to research efforts toward gaining insights on the mechanisms that drive participation, contributions, and interaction in this social media platform during a disease outbreak. We collected 6,249,626 tweets referring to the Zika outbreak over a period of 12 weeks early in the outbreak (December 2015 through March 2016). We analyzed ...
The recent COVID-19 pandemic has brought the debate around vaccinations to the forefront of publi... more The recent COVID-19 pandemic has brought the debate around vaccinations to the forefront of public discussion. In this discussion, various social media platforms have a key role. While this has long been recognized, the way by which the public assigns attention to such topics remains largely unknown. Furthermore, the question of whether there is a discrepancy between people's opinions as expressed online and their actual decision to vaccinate remains open. To shed light on this issue, in this paper we examine the dynamics of online debates among four prominent vaccines (i.e., COVID-19, Influenza, MMR, and HPV) through the lens of public attention as captured on Twitter in the United States from 2015 to 2021. We then compare this to actual vaccination rates from governmental reports, which we argue serve as a proxy for real-world vaccination behaviors. Our results demonstrate that since the outbreak of COVID-19, it has come to dominate the vaccination discussion, which has led to a redistribution of attention from the other three vaccination themes. The results also show an apparent discrepancy between the online debates and the actual vaccination rates. These findings are in line with existing theories, that of agenda-setting and zero-sum theory. Furthermore, our approach could be extended to assess the public's attention toward other health-related issues, and provide a basis for quantifying the effectiveness of health promotion policies.
Proceedings of the 7th 2016 International Conference on Social Media & Society - SMSociety '16, 2016
Social media platforms have become extremely popular during the past few years, presenting an alt... more Social media platforms have become extremely popular during the past few years, presenting an alternate, and often preferred, avenue for information dissemination within massive global communities. Such user-generated multimedia content is emerging as a critical source of information for a variety of applications, and particularly during times of crisis. In order to fully explore this potential, there is a need to better assess, and improve when possible, the accuracy of such information. This paper addresses this issue by focusing in particular on user-contributed image tagging in Flickr. We use as case study a natural disaster event (wildfire), and assess the reliability of user-generated tags. Furthermore, we compare these data to the results of a content-based annotation approach in order to assess the potential performance of an alternative, user-independent, automated approach to annotate such imagery. Our results show that Flickr user annotations can be considered quite reliable (at the level of ~50%), and that using a spatially distributed training dataset for our content-based image retrieval (CBIR) annotation process improves the performance of the content-based image labeling (to the level of ~75%).
As spatial data becomes a central component in a variety of applications, the demand for up-to-da... more As spatial data becomes a central component in a variety of applications, the demand for up-to-date data is on the rise. In order to shorten the updating cycle time local updating is preferred, in which patches of up-to-date data must be incorporated into the existing data set. Although this can be done by using a global transformation model or a rubber-sheeting scheme, it is argued that in the case of patch-based updating the accuracy relations and its spatial variations must be considered. This requires adopting a field ...
International Archives of Photogrammetry and Remote Sensing, 2000
The requirement for maintaining up-to-date spatial data originates both from the end-user and fro... more The requirement for maintaining up-to-date spatial data originates both from the end-user and from the information provider, since inability to do so may result in reluctance to utilize the data. Maintaining up-to-date spatial data may be performed either by completely remapping the area of interest (a global strategy) or by a local updating cycle, in which limited areas (³patches) in the existing data set are updated according to need (a local strategy). When implementing the local strategy, two prerequisites must be fulfilled. The ...
Mass shootings, like other extreme events, have long garnered public curiosity and, in turn, sign... more Mass shootings, like other extreme events, have long garnered public curiosity and, in turn, significant media coverage. The media framing, or topic focus, of mass shooting events typically evolves over time from details of the actual shooting to discussions of potential policy changes (e.g., gun control, mental health). Such media coverage has been historically provided through traditional media sources such as print, television, and radio, but the advent of online social networks (OSNs) has introduced a new platform for accessing, producing, and distributing information about such extreme events. The ease and convenience of OSN usage for information within society’s larger growing reliance upon digital technologies introduces potential unforeseen risks. Social bots, or automated software agents, are one such risk, as they can serve to amplify or distort potential narratives associated with extreme events such as mass shootings. In this paper, we seek to determine the prevalence an...
Location and time are critical to the success of many organizations’ missions. Sensors, software,... more Location and time are critical to the success of many organizations’ missions. Sensors, software, processors, vehicles, and human analysts work together to accomplish these tasks of detecting and identifying specific entities as quickly as possible for these missions. This work aims to make a contribution by providing a team-based detection and identification performance model incorporating the theory of Distributed Situational Awareness (DSA) and its effect on completing a specific task. The task being the ability to detect and identify a specific entity within a complex urban environment. Conditions to accomplish the task is the utilization of two unmanned aerial vehicles mounted with electrooptical sensors, operated by two analysts, creating a team to execute this task. Our results provide an additional resource on the how technology and training might be utilized to find the best performance given these certain conditions and missions. A highly trained team might improve their performance with this technology, or a team with low training could perform at a high level given the appropriate technology in limited time scenarios. More importantly, the model presented in this paper provides an evaluation tool to compare new technologies and their impact on teams. Specifically, it enables answering questions, such as: is an investment in new technology appropriate if investing in additional training produces the same performance results? Future performance can also be evaluated based on the team’s level of training and use of technology for these specific tasks.
Using geolocated tweets to achieve situational awareness is an often researched topic in disaster... more Using geolocated tweets to achieve situational awareness is an often researched topic in disaster and emergency management. However, little has been done in the area of drug cartels, which, as transnational crime organizations, continue to pose great risk to the stability and safety of our communities. This paper made an initial effort in using geolocated social media (specifically Twitter) to achieve situational awareness of drug cartels through temporal and spatial analysis of derived named entity clusters. The results show that detecting peaks in the time series of frequently occurring entity clusters enabled the tracking of important events in public discourse surrounding drug cartels. Correlations between time series also provided valuable insights into the synchronicity between different events. Further examining the spatial distribution of key events for different countries, we identify thematic hotpots of public discourse on cartel activity. Our methodology also addresses issues of language ambiguity when working with noisy social media data in order to achieve situational awareness on drug cartels.
Participants will leave the session with concrete ideas and examples for materials that might be ... more Participants will leave the session with concrete ideas and examples for materials that might be included in their dossiers as part of the reappointment, renewal, promotion, and/or tenure processes.
Abstract: Pedestrian movement is woven into the fabric of urban regions. With more people living ... more Abstract: Pedestrian movement is woven into the fabric of urban regions. With more people living in cities than ever before, there is an increased need to understand and model how pedestrians utilize and move through space for a variety of applications, ranging from urban planning and architecture to security. Pedestrian modeling has been traditionally faced with the challenge of collecting data to calibrate and validate such models of pedestrian movement. With the increased availability of mobility datasets from video surveillance and enhanced geolocation capabilities in consumer mobile devices we are now presented with the opportunity to change the way we build pedestrian models. Within this paper we explore the potential that such information offers for the improvement of agent-based pedestrian models. We introduce a Scene- and Activity-Aware Agent-Based Model (SA2-ABM), a method for harvesting scene activity information in the form of spatiotemporal trajectories, and incorporate...
The emergence of social media has provided the public with an effective and irrepressible real-ti... more 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 cyberspac...
Social media content analysis often focuses on just the words used in documents or by users and o... more Social media content analysis often focuses on just the words used in documents or by users and often overlooks the structural components of document composition and linguistic style. We propose that document structure and emoji use are also important to consider as they are impacted by individual communication style preferences and social norms associated with user role and intent, topic domain, and dissemination platform. In this paper we introduce and demonstrate a novel methodology to conduct structural content analysis and measure user consistency of document structures and emoji use. Document structure is represented as the order of content types and number of features per document and emoji use is characterized by the attributes, position, order, and repetition of emojis within a document. With these structures we identified user signatures of behavior, clustered users based on consistency of structures utilized, and identified users with similar document structures and emoji...
The recent Zika outbreak witnessed the disease evolving from a regional health concern to a globa... more The recent Zika outbreak witnessed the disease evolving from a regional health concern to a global epidemic. During this process, different communities across the globe became involved in Twitter, discussing the disease and key issues associated with it. This paper presents a study of this discussion in Twitter, at the nexus of location, actors, and concepts. Our objective in this study was to demonstrate the significance of 3 types of events: location related, actor related, and concept related, for understanding how a public health emergency of international concern plays out in social media, and Twitter in particular. Accordingly, the study contributes to research efforts toward gaining insights on the mechanisms that drive participation, contributions, and interaction in this social media platform during a disease outbreak. We collected 6,249,626 tweets referring to the Zika outbreak over a period of 12 weeks early in the outbreak (December 2015 through March 2016). We analyzed ...
Social media have drastically altered the concept of information contribution and dissemination b... more Social media have drastically altered the concept of information contribution and dissemination by empowering the general public to publish and distribute user-generated content. These social media contributions may be viewed as expressions of humans acting as sensors, reporting events and activities in which they participate, or commenting on others that are somehow affecting them, or catching their attention. Thematically, the content of such media is diverse, ranging from reporting events like an earthquake to making mundane comments, pop culture references, or daily activity reports. Regardless of the topic, this information always has a temporal component, in the form of its submission time. Social media feeds also often have geolocation information associated with them, available in the form of precise coordinates, or as location descriptions listing for example only a city name. In this paper we focus on the spatiotemporal content of twitter feeds in order to assess their use as a hybrid form of a sensor network to monitor evolving events. Our objective is to investigate how social media contributions can be utilized to study the spatiotemporal evolution of dynamic sociocultural events. Towards this goal we use as a representative case the events of the Occupy Wall Street (OWS) movement in New York City, NY, on the International Day of Action of November 17th, 2011. We use twitter as a representative example to harvest social media for our study. We collected geolocated tweets during that day, making reference to the Occupy Wall Street movement (e.g. through its associated hashtags and usernames, such as #ows) and analyze them to investigate how well they capture that day’s activities.
The Internet and its World Wide Web (WWW) have revolutionised many aspects of our daily lives fro... more 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 through social media and the growth of augmented reality (AR) applications tied to specific locations.
The emergence of social media has provided the public with an effective and irrepressible real-ti... more 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.
The massive proliferation of traditional geospatial datasets like remote sensing imagery is prese... more The massive proliferation of traditional geospatial datasets like remote sensing imagery is presenting substantial computational challenges associated with the management, processing, and analysis of massive volumes of datasets. While these challenges are indeed substantial, they reflect an evolution rather than a breakpoint for the geoinformatics community: we are trying to apply established analysis techniques onto massive data. The emergence of social media however is posing a different type of Big Data challenge to the geoinformatics community: not only are the datasets large, but their analysis is also novel, and calls for a hybrid mix of spatial and social analysis. The geographical content of social media comprises coordinates from which the contributions originate, or of references to specific locations. At the same time, information on the underlying social structure of the user community can be derived by studying the interactions between users (e.g. formed as they respond to, or follow, other users), and this information can provide additional context to the data. The analysis of both the geographical and social content of social media feeds is referred to as geosocial analysis. It is emerging as a new research frontier for the geoinformatics and social sciences communities, and through its volume and richness opens new avenues and research challenges for understanding dynamic events and situations around the world.
Research Summary: Public mass shootings tend to capture the public's attention and receive substa... more Research Summary: Public mass shootings tend to capture the public's attention and receive substantial coverage in both traditional media and online social networks (OSNs) and have become a salient topic in them. Motivated by this, the overarching objective of this paper is to advance our understanding of how the public responds to mass shooting events in such media outlets. Specifically, it aims to examine whether distinct information seeking patterns emerge over time and space, and whether associations between public mass shooting events emerge in online activities and discourse. Towards this objective, we study a sequence of five public mass shooting events that have occurred in the United States between October 2017 and May 2018 across three major dimensions: the public's online information seeking activities, the media coverage, and the discourse that emerges in a prominent OSN. To capture these dimensions, respectively, data was collected and analyzed from Google Trends, LexisNexis, Wikipedia Page views, and Twitter. The results of our analysis suggest that distinct temporal patterns emerge in the public's information seeking activities across different platforms, Criminology & Public Policy. 2020;1-26. wileyonlinelibrary.com/journal/capp
This study presents a novel approach to expand the emergent area of social bot research. We emplo... more This study presents a novel approach to expand the emergent area of social bot research. We employ a methodological framework that aggregates and fuses data from multiple global Twitter conversations with an available bot detection platform and ultimately classifies the relative importance and persistence of social bots in online social networks (OSNs). In testing this methodology across three major global event OSN conversations in 2016, we confirmed the hyper-social nature of bots: suspected social bot accounts make far more attempts on average than social media accounts attributed to human users to initiate contact with other accounts via retweets. Social network analysis centrality measurements discover that social bots, while comprising less than 0.3% of the total corpus user population, display a disproportionately high level of structural network influence by ranking particularly high among the top users across multiple centrality measures within the OSN conversations of interest. Further, we show that social bots exhibit temporal persistence in centrality ranking density when examining these same OSN conversations over time.
Background: The recent Zika outbreak witnessed the disease evolving from a regional health concer... more Background: The recent Zika outbreak witnessed the disease evolving from a regional health concern to a global epidemic. During this process, different communities across the globe became involved in Twitter, discussing the disease and key issues associated with it. This paper presents a study of this discussion in Twitter, at the nexus of location, actors, and concepts.
Objective: Our objective in this study was to demonstrate the significance of 3 types of events: location related, actor related, and concept related, for understanding how a public health emergency of international concern plays out in social media, and Twitter in particular. Accordingly, the study contributes to research efforts toward gaining insights on the mechanisms that drive participation, contributions, and interaction in this social media platform during a disease outbreak.
Methods: We collected 6,249,626 tweets referring to the Zika outbreak over a period of 12 weeks early in the outbreak (December 2015 through March 2016). We analyzed this data corpus in terms of its geographical footprint, the actors participating in the discourse, and emerging concepts associated with the issue. Data were visualized and evaluated with spatiotemporal and network analysis tools to capture the evolution of interest on the topic and to reveal connections between locations, actors, and concepts in the form of interaction networks.
Results: The spatiotemporal analysis of Twitter contributions reflects the spread of interest in Zika from its original hotspot in South America to North America and then across the globe. The Centers for Disease Control and World Health Organization had a prominent presence in social media discussions. Tweets about pregnancy and abortion increased as more information about this emerging infectious disease was presented to the public and public figures became involved in this.
Conclusions: The results of this study show the utility of analyzing temporal variations in the analytic triad of locations, actors, and concepts. This contributes to advancing our understanding of social media discourse during a public health emergency of international concern.
With volunteered geographic information (VGI) platforms such as OpenStreetMap (OSM) becoming incr... more With volunteered geographic information (VGI) platforms such as OpenStreetMap (OSM) becoming increasingly popular, we are faced with the challenge of assessing the quality of their content, in order to better understand its place relative to the authoritative content of more traditional sources. Until now, studies have focused primarily on developed countries, showing that VGI content can match or even surpass the quality of authoritative sources, with very few studies in developing countries. In this paper, we compare the quality of authoritative (data from the Regional Center for Mapping of Resources for Development (RCMRD)) and non-authoritative (data from OSM and Google's Map Maker) road data in conjunction with population data in and around Nairobi, Kenya. Results show variability in coverage between all of these datasets. RCMRD provided the most complete, albeit less current, coverage when taking into account the entire study area, while OSM and Map Maker showed a degradation of coverage as one moves from central Nairobi towards rural areas. Furthermore, OSM had higher content density in large slums, surpassing the authoritative datasets at these locations, while Map Maker showed better coverage in rural housing areas. These results suggest a greater need for a more inclusive approach using VGI to supplement gaps in authoritative data in developing nations.
With volunteered geographic information (VGI) platforms such as OpenStreetMap (OSM) becoming incr... more With volunteered geographic information (VGI) platforms such as OpenStreetMap (OSM) becoming increasingly popular, we are faced with the challenge of assessing the quality of their content, in order to better understand its place relative to the authoritative content of more traditional sources. Until now, studies have focused primarily on developed countries, showing that VGI content can match or even surpass the quality of authoritative sources, with very few studies in developing countries. In this paper, we compare the quality of authoritative (data from the Regional Center for Mapping of Resources for Development (RCMRD)) and non-authoritative (data from OSM and Google's Map Maker) road data in conjunction with population data in and around Nairobi, Kenya. Results show variability in coverage between all of these datasets. RCMRD provided the most complete, albeit less current, coverage when taking into account the entire study area, while OSM and Map Maker showed a degradation of coverage as one moves from central Nairobi towards rural areas. Furthermore, OSM had higher content density in large slums, surpassing the authoritative datasets at these locations, while Map Maker showed better coverage in rural housing areas. These results suggest a greater need for a more inclusive approach using VGI to supplement gaps in authoritative data in developing nations.
Over 1 billion people currently live in slums, with the number of slum dwellers only expected to ... more Over 1 billion people currently live in slums, with the number of slum dwellers only expected to grow in the coming decades. The vast majority of slums are located in and around urban centres in the less economically developed countries, which are also experiencing greater rates of urbanization compared with more developed countries. This rapid rate of urbanization is cause for significant concern given that many of these countries often lack the ability to provide the infrastructure (e.g., roads and affordable housing) and basic services (e.g., water and sanitation) to provide adequately for the increasing influx of people into cities. While research on slums has been ongoing, such work has mainly focused on one of three constructs: exploring the socio-economic and policy issues; exploring the physical characteristics; and, lastly, those modelling slums. This paper reviews these lines of research and argues that while each is valuable, there is a need for a more holistic approach for studying slums to truly understand them. By synthesizing the social and physical constructs, this paper provides a more holistic synthesis of the problem, which can potentially lead to a deeper understanding and, consequently, better approaches for tackling the challenge of slums at the local, national and regional scales.
As the Ebola outbreak in West Africa wanes, it is time for the international scientific community... more As the Ebola outbreak in West Africa wanes, it is time for the international scientific community to reflect on how to improve the detection of and coordinated response to future epidemics. Our interdisciplinary team identified key lessons learned from the Ebola outbreak that can be clustered into three areas: environmental conditions related to early warning systems, host characteristics related to public health, and agent issues that can be addressed through the laboratory sciences. In particular, we need to increase zoonotic surveillance activities, implement more effective ecological health interventions, expand prediction modeling, support medical and public health systems in order to improve local and international responses to epidemics, improve risk communication, better understand the role of social media in outbreak awareness and response, produce better diagnostic tools, create better therapeutic medications, and design better vaccines. This list highlights research priorities and policy actions the global community can take now to be better prepared for future emerging infectious disease outbreaks that threaten global public health and security.
Place can be generally defined as a location that has been assigned meaning through human experie... more Place can be generally defined as a location that has been assigned meaning through human experience, and as such it is of multidisciplinary scientific interest. Up to this point place has been studied primarily within the context of social sciences as a theoretical construct. The availability of large amounts of user-generated content, e.g. in the form of social media feeds or Wikipedia contributions, allows us for the first time to computationally analyze and quantify the shared meaning of place. By aggregating references to human activities within urban spaces we can observe the emergence of unique themes that characterize different locations, thus identifying places through their discernible sociocultural signatures. In this paper we present results from a novel quantitative approach to derive such sociocul-tural signatures from Twitter contributions and also from corresponding Wikipedia entries. By contrasting the two we show how particular thematic characteristics of places (referred to herein as platial themes) are emerging from such crowd-contributed content, allowing us to observe the meaning that the general public, either individually or collectively, is assigning to specific locations. Our approach leverages probabilistic topic modelling, semantic association, and spatial clustering to find locations are conveying a collective sense of place. Deriving and quantifying such meaning allows us to observe how people transform a location to a place and shape its characteristics.
Due to ongoing urbanization trends the worldwide urban population is projected to grow from half ... more 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.
Urban form and function have been studied extensively in urban planning and geographical informat... more Urban form and function have been studied extensively in urban planning and geographical information science. However, gaining a greater understanding of how they merge to define the urban morphology remains a substantial scientific challenge. Toward this goal, this paper addresses the opportunities presented by the emergence of crowdsourced data to gain novel insights into form and function in urban spaces. We are focusing in particular on information harvested from social media and other open-source and volunteered datasets (e.g. trajectory and OpenStreetMap data). These data provide a first-hand account of form and function from the people who define urban space through their activities. This novel bottom-up approach to study these concepts complements traditional urban studies to provide a new lens for studying urban activity. By synthesizing recent advancements in the analysis of open-source data, we provide a new typology for characterizing the role of crowdsourcing in the study of urban morphology. We illustrate this new perspective by showing how social media, trajectory, and traffic data can be analyzed to capture the evolving nature of a city’s form and function. While these crowd contributions may be explicit or implicit in nature, they are giving rise to an emerging research agenda for monitoring, analyzing, and modeling form and function for urban design and analysis.
Background: The emergence of social media is providing an alternative avenue for information exch... more 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. We aimed to contribute to the analysis of the data, as well as presenting a quantitative interdisciplinary approach to analyze such open-source data in the context of health narratives.
Methods: We collected 669,136 tweets referring to vaccination from February 1 to March 9, 2015. 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 antivaccination 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, thus supporting the design of more effective strategies that take into account the complex and evolving public views of health issues.
Pedestrian movement is woven into the fabric of urban regions. With more people living in cities ... more Pedestrian movement is woven into the fabric of urban regions. With more people living in cities than ever before, there is an increased need to understand and model how pedestrians utilize and move through space for a variety of applications, ranging from urban planning and architecture to security. Pedestrian modeling has been traditionally faced with the challenge of collecting data to calibrate and validate such models of pedestrian movement. With the increased availability of mobility datasets from video surveillance and enhanced geolocation capabilities in consumer mobile devices we are now presented with the opportunity to change the way we build pedestrian models. Within this paper we explore the potential that such information offers for the improvement of agent-based pedestrian models. We introduce a Scene- and Activity-Aware Agent-Based Model (SA2-ABM), a method for harvesting scene activity information in the form of spatiotemporal trajectories, and incorporate this information into our models. In order to assess and evaluate the improvement offered by such information, we carry out a range of experiments using real-world datasets. We demonstrate that the use of real scene information allows us to better inform our model and enhance its predictive capabilities.
The international community can be viewed as a set of networks manifested through various transna... more The international community can be viewed as a set of networks manifested through various transnational activities. The availability of longitudinal data sets 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 (IRs). The comparison of these two network types offers a new lens to study the alignment between states and their people. This article presents a network-driven approach to analyze communities as they are established through different forms of bottom-up (e.g., Twitter) and topdown (e.g., UNGA voting records and international arms trade records) IRs. 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 in Syria within Twitter over a sample period of 1 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).
Over the last decade we have witnessed a significant growth in the use of social media. Interacti... more 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.
The analysis of social media content for the extraction of geospatial information and event-relat... more The analysis of social media content for the extraction of geospatial information and event-related knowledge has recently received substantial attention. In this article 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 both 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 Flickr imagery accordingly 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 article presents our approach and demonstrates its performance using a real-world wildfire event as a representative application case study.
The proliferation of volunteered geographic information (VGI), such as OpenStreetMap (OSM) enable... more 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 assessment of the quality and accuracy of Volunteered Geographic Information (VGI) contribut... more The assessment of the quality and accuracy of Volunteered Geographic Information (VGI) contributions, and by extension the ultimate utility of VGI data has fostered much debate within the geographic community. The limited research to date has been focused on VGI data of linear features and has shown that the error in the data is heterogeneously distributed. Some have argued that data produced by numerous contributors will produce a more accurate product than an individual and some research on crowd-sourced initiatives has shown that to be true, although research on VGI is more infrequent. This paper proposes a method for quantifying the completeness and accuracy of a select subset of infrastructure-associated point datasets of volunteered geographic data within a major metropolitan area using a national geospatial dataset as the reference benchmark with two datasets from volunteers used as test datasets. The results of this study illustrate the benefits of including quality control in the collection process for volunteered data.
The proliferation of social media has led to the emergence of a new type of geospatial informatio... more 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.
Social media feeds are rapidly emerging as a novel avenue for the contribution and dissemination ... more Social media feeds are rapidly emerging as a novel avenue for the contribution and dissemination of information that is often geographic. Their content often includes references to events occurring at, or affecting specific locations. Within this article we analyze the spatial and temporal characteristics of the twitter feed activity responding to a 5.8 magnitude earthquake which occurred on the East Coast of the United States (US) on August 23, 2011. We argue that these feeds represent a hybrid form of a sensor system that allows for the identification and localization of the impact area of the event. By contrasting this with comparable content collected through the dedicated crowdsourcing ‘Did You Feel It?’ (DYFI) website of the U.S. Geological Survey we assess the potential of the use of harvested social media content for event monitoring. The experiments support the notion that people act as sensors to give us comparable results in a timely manner, and can complement other sources of data to enhance our situational awareness and improve our understanding and response to such events.
As the Ebola outbreak in West Africa wanes, it is time for the international scientific community... more As the Ebola outbreak in West Africa wanes, it is time for the international scientific community to reflect on how to improve the detection of and coordinated response to future epidemics. Our interdisciplinary team identified key lessons learned from the Ebola outbreak that can be clustered into three areas: environmental conditions related to early warning systems, host characteristics related to public health, and agent issues that can be addressed through the laboratory sciences. In particular, we need to increase zoonotic surveillance activities, implement more effective ecological health interventions, expand prediction modeling, support medical and public health systems in order to improve local and international responses to epidemics, improve risk communication, better understand the role of social media in outbreak awareness and response, produce better diagnostic tools, create better therapeutic medications, and design better vaccines. This list highlights research priorities and policy actions the global community can take now to be better prepared for future emerging infectious disease outbreaks that threaten global public health and security. Paul L. Delamater, Jhumka Gupta, , Mariaelena Pierobon, Katherine E. Rowan, J. Reid Schwebach, Padmanabhan Seshaiyer ... ; ; ; ; ; >
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Papers by Arie Croitoru
Objective: Our objective in this study was to demonstrate the significance of 3 types of events: location related, actor related, and concept related, for understanding how a public health emergency of international concern plays out in social media, and Twitter in particular. Accordingly, the study contributes to research efforts toward gaining insights on the mechanisms that drive participation, contributions, and interaction in this social media platform during a disease outbreak.
Methods: We collected 6,249,626 tweets referring to the Zika outbreak over a period of 12 weeks early in the outbreak (December 2015 through March 2016). We analyzed this data corpus in terms of its geographical footprint, the actors participating in the discourse, and emerging concepts associated with the issue. Data were visualized and evaluated with spatiotemporal and network analysis tools to capture the evolution of interest on the topic and to reveal connections between locations, actors, and concepts in the form of interaction networks.
Results: The spatiotemporal analysis of Twitter contributions reflects the spread of interest in Zika from its original hotspot in South America to North America and then across the globe. The Centers for Disease Control and World Health Organization had a prominent presence in social media discussions. Tweets about pregnancy and abortion increased as more information about this emerging infectious disease was presented to the public and public figures became involved in this.
Conclusions: The results of this study show the utility of analyzing temporal variations in the analytic triad of locations, actors, and concepts. This contributes to advancing our understanding of social media discourse during a public health emergency of international concern.
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.
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. We aimed to contribute to the analysis of the data, as well as presenting a quantitative interdisciplinary approach to analyze such open-source data in the context of health narratives.
Methods: We collected 669,136 tweets referring to vaccination from February 1 to March 9, 2015. 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 antivaccination 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, thus supporting the design of more effective strategies that take into account the complex and evolving public views of health issues.
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.