Spatial and Temporal Sentiment Analysis of Twitter data

The public have used Twitter world wide for expressing opinions. This study focuses on spatio-temporal variation of georeferenced Tweets’ sentiment polarity, with a view to understanding how opinions evolve on Twitter over space and time and across communities of users. More specifically, the question this study tested is whether sentiment polarity on Twitter exhibits specific time-location patterns. The aim of the study is to investigate the spatial and temporal distribution of georeferenced Twitter sentiment polarity within the area of 1 km buffer around the Curtin Bentley campus boundary in Perth, Western Australia. Tweets posted in campus were assigned into six spatial zones and four time zones. A sentiment analysis was then conducted for each zone using the sentiment analyser tool in the Starlight Visual Information System software. The Feature Manipulation Engine was employed to convert non-spatial files into spatial and temporal feature class. The spatial and temporal distribution of Twitter sentiment polarity patterns over space and time was mapped using Geographic Information Systems (GIS). Some interesting results were identified. For example, the highest percentage of positive Tweets occurred in the social science area, while science and engineering and dormitory areas had the highest percentage of negative postings. The number of negative Tweets increases in the library and science and engineering areas as the end of the semester approaches, reaching a peak around an exam period, while the percentage of negative Tweets drops at the end of the semester in the entertainment and sport and dormitory area. This study will provide some insights into understanding students and staff ’s sentiment variation on Twitter, which could be useful for university teaching and learning management

European Handbook of Crowdsourced Geographic Information

"This book focuses on the study of the remarkable new source of geographic information that has become available in the form of user-generated content accessible over the Internet through mobile and Web applications. The exploitation, integration and application of these sources, termed volunteered geographic information (VGI) or crowdsourced geographic information (CGI), offer scientists an unprecedented opportunity to conduct research on a variety of topics at multiple scales and for diversified objectives. The Handbook is organized in five parts, addressing the fundamental questions: What motivates citizens to provide such information in the public domain, and what factors govern/predict its validity?What methods might be used to validate such information? Can VGI be framed within the larger domain of sensor networks, in which inert and static sensors are replaced or combined by intelligent and mobile humans equipped with sensing devices? What limitations are imposed on VGI by differential access to broadband Internet, mobile phones, and other communication technologies, and by concerns over privacy? How do VGI and crowdsourcing enable innovation applications to benefit human society? Chapters examine how crowdsourcing techniques and methods, and the VGI phenomenon, have motivated a multidisciplinary research community to identify both fields of applications and quality criteria depending on the use of VGI. Besides harvesting tools and storage of these data, research has paid remarkable attention to these information resources, in an age when information and participation is one of the most important drivers of development. The collection opens questions and points to new research directions in addition to the findings that each of the authors demonstrates. Despite rapid progress in VGI research, this Handbook also shows that there are technical, social, political and methodological challenges that require further studies and research.

Mapping and the Citizen Sensor

Maps are a fundamental resource in a diverse array of applications ranging from everyday activities, such as route planning through the legal demarcation of space to scientific studies, such as those seeking to understand biodiversity and inform the design of nature reserves for species conservation. For a map to have value, it should provide an accurate and timely representation of the phenomenon depicted and this can be a challenge in a dynamic world. Fortunately, mapping activities have benefitted greatly from recent advances in geoinformation technologies. Satellite remote sensing, for example, now offers unparalleled data acquisition and authoritative mapping agencies have developed systems for the routine production of maps in accordance with strict standards. Until recently, much mapping activity was in the exclusive realm of authoritative agencies but technological development has also allowed the rise of the amateur mapping community. The proliferation of inexpensive and highly mobile and location aware devices together with Web 2.0 technology have fostered the emergence of the citizen as a source of data. Mapping presently benefits from vast amounts of spatial data as well as people able to provide observations of geographic phenomena, which can inform map production, revision and evaluation. The great potential of these developments is, however, often limited by concerns. The latter span issues from the nature of the citizens through the way data are collected and shared to the quality and trustworthiness of the data. This book reports on some of the key issues connected with the use of citizen sensors in mapping. It arises from a European Co-operation in Science and Technology (COST) Action, which explored issues linked to topics ranging from citizen motivation, data acquisition, data quality and the use of citizen derived data in the production of maps that rival, and sometimes surpass, maps arising from authoritative agencies

The tasks of the crowd : a typology of tasks in geographic information crowdsourcing and a case study in humanitarian mapping

In the past few years, volunteers have produced geographic information of different kinds, using a variety of different crowdsourcing platforms, within a broad range of contexts. However, there is still a lack of clarity about the specific types of tasks that volunteers can perform for deriving geographic information from remotely sensed imagery, and how the quality of the produced information can be assessed for particular task types. To fill this gap, we analyse the existing literature and propose a typology of tasks in geographic information crowdsourcing, which distinguishes between classification, digitisation and conflation tasks. We then present a case study related to the “Missing Maps” project aimed at crowdsourced classification to support humanitarian aid. We use our typology to distinguish between the different types of crowdsourced tasks in the project and choose classification tasks related to identifying roads and settlements for an evaluation of the crowdsourced classification. This evaluation shows that the volunteers achieved a satisfactory overall performance (accuracy: 89%; sensitivity: 73%; and precision: 89%). We also analyse different factors that could influence the performance, concluding that volunteers were more likely to incorrectly classify tasks with small objects. Furthermore, agreement among volunteers was shown to be a very good predictor of the reliability of crowdsourced classification: tasks with the highest agreement level were 41 times more probable to be correctly classified by volunteers. The results thus show that the crowdsourced classification of remotely sensed imagery is able to generate geographic information about human settlements with a high level of quality. This study also makes clear the different sophistication levels of tasks that can be performed by volunteers and reveals some factors that may have an impact on their performance

Exploring the use of crowdsourced geographic information in defence: challenges and opportunities

Geographic data are used by United Kingdom (UK) defence for purposes including peacekeeping, humanitarian aid and disaster relief, and fighting wars. The geographic extent of defence data covers the world, with greater focus directed towards areas considered to be of current interest. Traditionally, these data have been officially sourced, e.g. via National Mapping Agencies, but there is now increasing interest in the potential of crowdsourced geographic data to supplement authoritative data where they are not available, outdated or incomplete. Volunteered geographic information (VGI) and social media have the potential to provide this needed missing information. This paper presents initial work carried out in identifying the potential of crowdsourced geographic information in defence. We first provide a short description of the role of UK defence and review the existing literature on crowdsourced geographic information in defence, as well as generic VGI quality assessment methods. We then explore the potential of crowdsourced data in real-world applications: the conflation of VGI and social media with official data for effective decision-making in war zones, and the potential for crowdsourcing to increase effective collaboration between machines and humans in disaster situations. Based on our review, we outline specific research challenges for deploying crowdsourced geographic information in defence, focussing on data quality and fitness-for-purpose assessment. Defence-specific constraints include the need for rapid quality assessment processes and the need to communicate high-quality information effectively in situations where rapid decision-making is required. Ethical issues are also of fundamental importance

Towards a Protocol for the Collection of VGI Vector Data

A protocol for the collection of vector data in Volunteered Geographic Information (VGI) projects is proposed. VGI is a source of crowdsourced geographic data and information which is comparable, and in some cases better, than equivalent data from National Mapping Agencies (NMAs) and Commercial Surveying Companies (CSC). However, there are many differences in how NMAs and CSC collect, analyse, manage and distribute geographic information to that of VGI projects. NMAs and CSC make use of robust and standardised data collection protocols whilst VGI projects often provide guidelines rather than rigorous data collection specifications. The proposed protocol addresses formalising the collection and creation of vector data in VGI projects in three principal ways: by manual vectorisation; field survey; and reuse of existing data sources. This protocol is intended to be generic rather than being linked to any specific VGI project. We believe that this is the first protocol for VGI vector data collection that has been formally described in the literature. Consequently, this paper shall serve as a starting point for on-going development and refinement of the protocol

Mapping and the citizen sensor

Maps are a fundamental resource in a diverse array of applications ranging from everyday activities, such as route planning through the legal demarcation of space to scientific studies, such as those seeking to understand biodiversity and inform the design of nature reserves for species conservation. For a map to have value, it should provide an accurate and timely representation of the phenomenon depicted and this can be a challenge in a dynamic world. Fortunately, mapping activities have benefitted greatly from recent advances in geoinformation technologies. Satellite remote sensing, for example, now offers unparalleled data acquisition and authoritative mapping agencies have developed systems for the routine production of maps in accordance with strict standards. Until recently, much mapping activity was in the exclusive realm of authoritative agencies but technological development has also allowed the rise of the amateur mapping community. The proliferation of inexpensive and highly mobile and location aware devices together with Web 2.0 technology have fostered the emergence of the citizen as a source of data. Mapping presently benefits from vast amounts of spatial data as well as people able to provide observations of geographic phenomena, which can inform map production, revision and evaluation. The great potential of these developments is, however, often limited by concerns. The latter span issues from the nature of the citizens through the way data are collected and shared to the quality and trustworthiness of the data. This book reports on some of the key issues connected with the use of citizen sensors in mapping. It arises from a European Co-operation in Science and Technology (COST) Action, which explored issues linked to topics ranging from citizen motivation, data acquisition, data quality and the use of citizen derived data in the production of maps that rival, and sometimes surpass, maps arising from authoritative agencies

Leveraging the value of crowdsourced geographic information to detect cultural ecosystem services

Within ecological research and environmental management, there is current focus on demonstrating the links existing between human well-being and nature conservation. There is a need for better understanding how and why people value certain places over others. At the same time, there is a lack of consolidated methodologies, and limited experimentation in the detection of places connected to the immaterial benefits we get from nature. Those benefits are termed Cultural Ecosystem Services (CES). This research analyses the potential of Crowdsourced Geographic Information (CGI) to support the detection of CES with large scale insights derived from the analysis of digital cultural practices. CGI is produced through social media, in situations where individuals choose to share content. Therefore, a CGI project is often the expression of a community of interest and different projects have different supporting communities with different demographics and cultural profiles. The research combines multiple projects pertaining to three different categories of CGI to avoid focusing only on a community or on a digital cultural practice. Using ecological and social considerations, this thesis contributes to the evaluation of such projects as potential analytical tools for CES research. The degree of appreciation of a specific place is derived from the number of people creating, sharing, or refining the information about it. The sequence of decisions and actions that leads to the sharing of information leaves digital proxies of spatial preferences, with people sharing specific information considering the place not only “worth visiting” but also “worth sharing”. Using south Wales and London as case studies, we demonstrate how the analysis of CGI can be included in methodologies used to detect CES. These results highlight how the inclusion of CGI, can be very effective in addressing some of the current priorities in conservation. It could potentially be used for better prioritisation, planning and management of natural and cultural resources towards a more sustainable development

REPRESENTING THE SOCIAL CHARACTER OF PLACES: ONTOLOGY MODELS OF THE URBAN ENVIRONMENT

The thesis aimed at rendering machine understandable the social dimension of urban places to provide a new generation of urban analytics based on peoples’ socio- spatial behaviour. The main outcome has been a formal framework, encoded in the form of Ontology Design Patterns, to represent the interaction between the architectural aspects of the city, its form, and the behaviour of city dwellers. Ontology models are based on place theories discussed by social and cultural geographers - such as Henri Lefevbre, Edward Soja and Doreen Massey - and experimented in a knowledge discovery pipeline by exploring geographic crowdsourced data coming from the TripAdvisor platform