A Local-Global LDA Model for Discovering Geographical Topics from Social Media

Micro-blogging services can track users' geo-locations when users check-in their places or use geo-tagging which implicitly reveals locations. This "geo tracking" can help to find topics triggered by some events in certain regions. However, discovering such topics is very challenging because of the large amount of noisy messages (e.g. daily conversations). This paper proposes a method to model geographical topics, which can filter out irrelevant words by different weights in the local and global contexts. Our method is based on the Latent Dirichlet Allocation (LDA) model but each word is generated from either a local or a global topic distribution by its generation probabilities. We evaluated our model with data collected from Weibo, which is currently the most popular micro-blogging service for Chinese. The evaluation results demonstrate that our method outperforms other baseline methods in several metrics such as model perplexity, two kinds of entropies and KL-divergence of discovered topics

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

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.

Automatic Image Annotation using Image Clustering in Multi – Agent Society

The rapid growth of the internet provides tremendous resource for information in different domains (text, image, voice, and many others). This growth introduces new challenge to hit an exact match due to huge number of document returned by search engines where millions of items can be returned for certain subject. Images have been important resources for information, and billions of images are searched to fulfill user demands, which face the mentioned challenge. Automatic image annotation is a promising methodology for image retrieval. However most current annotation models are not yet sophisticated enough to produce high quality annotations. This thesis presents online intelligent indexing for image repositories based on their contents, although content based indexing and retrieving systems have been introduced, this thesis is adding an intelligent technique to re-index images upon better understanding for its composed concepts. Collaborative Agent scheme has been developed to promote objects of an image to concepts and re-index it according to domain specifications. Also this thesis presents automatic annotation system based on the interaction between intelligent agents. Agent interaction is synonym to socialization behavior dominating Agent society. The presented system is exploiting knowledge evolution revenue due to the socialization to charge up the annotation process

Exploitation of information propagation patterns in social sensing

Online social media presents new opportunity for sensing the physical world. The sensors are essentially human, who share information in the broadcast social media. Such human sensors impose challenges like influence, bias, polarization, and data overload, unseen in the traditional sensor network. This dissertation addresses the aforementioned challenges by exploiting the propagation or prefential attachment patterns of the human sensors to distill a factual view of the events transpiring in the physical world. Our first contribution explores the correlated errors caused by the dependent sources. When people follow others, they are prone to broadcast information with unknown provenance. We show that using admission control mechanism to select an independent set of sensors improves the quality of reconstruction. The next contribution explores a different kind of correlated error caused by polarization and bias. During events related to conflict or disagreement, people take sides, and take a selective or preferential approach when broadcasting information. For example, a source might be less credible when it shares information conforming to its own bias. We present a maximum-likelihood estimation model to reconstruct the factual information in such cases, given the individual bias of the sources are already known. Our next two contributions relate to modeling polarization and unveiling polarization using maximum-likelihood and matrix factorization based mechanisms. These mechanisms allow us to automate the process of separating polarized content, and obtain a more faithful view of the events being sensed. Finally, we design and implement `SocialTrove', a summarization service that continuously execute in the cloud, as a platform to compute the reconstructions at scale. Our contributions have been integrated with `Apollo Social Sensing Toolkit', which builds a pipeline to collect, summarize, and analyze information from Twitter, and serves more than 40 users

Metalogues on the thickened ground: landscape production and urban morphologies

Could we consider urban morphologies as figures that emerge as ‘horizontal phenomena’? Could we consider urban morphologies as embedded within the complex systems of the city rather than assume they demarcate the city through an overlay of lines? Could the urban form then be considered as an affect which emerges from a dynamic thickened ground, creating a new landscape? If landscapes are understood in terms of their connectability to the order of things in the universe (as, for example, in physics), where landscape’s connectability is a reciprocation of forces between itself and its context at all scales, then each connection is a shared force, a received and distributed force. If the order of the landscape is inherent in its process of transformations, to what extent does this order produce the city? This research aims to contribute to the discourse on Landscape Urbanism which is often positioned and grounded within the philosophical and scientific fields. However, it is argued that the ability to open up new possibilities, new ways of thinking and acting, lies in the act of design. This research, therefore, aimed to reveal these possibilities through a structured design process which linked the disciplinary fields of Landscape Architecture and Architecture