96 research outputs found
Visual design recommendations for situation awareness in social media
The use of online Social Media is increasingly popular amongst emergency services to support Situational
Awareness (i.e. accurate, complete and real-time information about an event). Whilst many software solutions
have been developed to monitor and analyse Social Media, little attention has been paid on how to visually
design for Situational Awareness for this large-scale data space. We describe an approach where levels of SA
have been matched to corresponding visual design recommendations using participatory design techniques with
Emergency Responders in the UK. We conclude by presenting visualisation prototypes developed to satisfy the
design recommendations, and how they contribute to Emergency Responders’ Situational Awareness in an
example scenario. We end by highlighting research issues that emerged during the initial evaluation
Context-Preserving Visual Analytics of Multi-Scale Spatial Aggregation.
Spatial datasets (i.e., location-based social media, crime incident reports, and demographic data) often exhibit varied distribution patterns at multiple spatial scales. Examining these patterns across different scales enhances the understanding from global to local perspectives and offers new insights into the nature of various spatial phenomena. Conventional navigation techniques in such multi-scale data-rich spaces are often inefficient, require users to choose between an overview or detailed information, and do not support identifying spatial patterns at varying scales. In this work, we present a context-preserving visual analytics technique that aggregates spatial datasets into hierarchical clusters and visualizes the multi-scale aggregates in a single visual space. We design a boundary distortion algorithm to minimize the visual clutter caused by overlapping aggregates and explore visual encoding strategies including color, transparency, shading, and shapes, in order to illustrate the hierarchical and statistical patterns of the multi-scale aggregates. We also propose a transparency-based technique that maintains a smooth visual transition as the users navigate across adjacent scales. To further support effective semantic exploration in the multi-scale space, we design a set of text-based encoding and layout methods that draw textual labels along the boundary or filled within the aggregates. The text itself not only summarizes the semantics at each scale, but also indicates the spatial coverage of the aggregates and their hierarchical relationships. We demonstrate the effectiveness of the proposed approaches through real-world application examples and user studies
Visual exploration of topics in multimedia news corpora
As news contents grow daily, the demand for tools to help users make sense of large document corpus will continuously be on the increase. Such tools will particularly be useful for journalist and ordinary users who intend to explore large collection of news documents for various analytical tasks. When users attempt to explore documents, they are usually in search for a particular topic of interest, or to compare various topics for similarity, or to see when in time a particular topic was discussed or to explore the distribution of a topic over time or to see how frequent a particular topic was discussed in the corpus or in general to test a particular hypothesis. Existing tools fall short in providing effective and suitable interaction mechanism to enable users answer these questions in a single application framework.
In this paper we presented a framework that gives users the opportunity to easily answer questions relating to their exploratory tasks. We developed new visual elements and augment them with existing interfaces to provide users with ample options and flexibility to explore multimedia news corpus from different angles depending on their analytic tasks. Our method uses machine learning for topic extraction, clustering and word cloud generation. Our approach effectively combines both overview + detail and focus + context schemes to enrich users experience with exploring large collection of multimedia news documents. Our framework ensures synchronization of the various visual interfaces to provide immediate feedback on user's interactions. To demonstrate the effectiveness of our approach, we presented some realistic use cases from the perspective of a news analyst. And based on our observations, we identified some possible directions for future studies
Supporting exploratory browsing with visualization of social interaction history
This thesis is concerned with the design, development, and evaluation of information visualization tools for supporting exploratory browsing. Information retrieval (IR) systems currently do not support browsing well. Responding to user queries, IR systems typically compute relevance scores of documents and then present the document surrogates to users in order of relevance. Other systems such as email clients and discussion forums simply arrange messages in reverse chronological order. Using these systems, people cannot gain an overview of a collection easily, nor do they receive adequate support for finding potentially useful items in the collection.
This thesis explores the feasibility of using social interaction history to improve exploratory browsing. Social interaction history refers to traces of interaction among users in an information space, such as discussions that happen in the blogosphere or online newspapers through the commenting facility. The basic hypothesis of this work is that social interaction history can serve as a good indicator of the potential value of information items. Therefore, visualization of social interaction history would offer navigational cues for finding potentially valuable information items in a collection.
To test this basic hypothesis, I conducted three studies. First, I ran statistical analysis of a social media data set. The results showed that there were positive relationships between traces of social interaction and the degree of interestingness of web articles. Second, I conducted a feasibility study to collect initial feedback about the potential of social interaction history to support information exploration. Comments from the participants were in line with the research hypothesis. Finally, I conducted a summative evaluation to measure how well visualization of social interaction history can improve exploratory browsing. The results showed that visualization of social interaction history was able to help users find interesting articles, to reduce wasted effort, and to increase user satisfaction with the visualization tool
WiFi-Based Human Activity Recognition Using Attention-Based BiLSTM
Recently, significant efforts have been made to explore human activity recognition (HAR) techniques that use information gathered by existing indoor wireless infrastructures through WiFi signals without demanding the monitored subject to carry a dedicated device. The key intuition is that different activities introduce different multi-paths in WiFi signals and generate different patterns in the time series of channel state information (CSI). In this paper, we propose and evaluate a full pipeline for a CSI-based human activity recognition framework for 12 activities in three different spatial environments using two deep learning models: ABiLSTM and CNN-ABiLSTM. Evaluation experiments have demonstrated that the proposed models outperform state-of-the-art models. Also, the experiments show that the proposed models can be applied to other environments with different configurations, albeit with some caveats. The proposed ABiLSTM model achieves an overall accuracy of 94.03%, 91.96%, and 92.59% across the 3 target environments. While the proposed CNN-ABiLSTM model reaches an accuracy of 98.54%, 94.25% and 95.09% across those same environments
Data visualization in the first person
Thesis (Ph. D.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, February 2013.Cataloged from PDF version of thesis. "February 2013."Includes bibliographical references (p. 103-107).This dissertation will examine what a first person viewpoint means in the context of data visualization and how it can be used for navigating and presenting large datasets. Recent years have seen rapid growth in Big Data methodologies throughout scientific research, business analytics, and online services. The datasets used in these areas are not only growing exponentially larger, but also more complex, incorporating heterogeneous data from many sources that might include digital sensors, websites, mass media, and others. The scale and complexity of these datasets pose significant challenges in the design of effective tools for navigation and analysis. This work will explore methods of representing large datasets as physical, navigable environments. Much of the related research on first person interfaces and 3D visualization has focused on producing tools for expert users and scientific analysis. Due to the complexities of navigation and perception introduced by 3D interfaces, work in this area has had mixed results. In particular, considerable efforts to develop 3D systems for more abstract data, like file systems and social networks, have had difficulty surpassing the efficiency of 2D approaches. However, 3D may offer advantages that have been less explored in this context. In particular, data visualization can be a valuable tool for disseminating scientific results, sharing insights, and explaining methodology. In these applications, clear communication of concepts and narratives are often more essential than efficient navigation. This dissertation will present novel visualization systems designed for large datasets that include audio-video recordings, social media, and others. Discussion will focus on designing visuals that use the first person perspective to give a physical and intuitive form to abstract data, to combine multiple sources of data within a shared space, to construct narratives, and to engage the viewer at a more visceral and emotional level.by Philip DeCamp.Ph.D
Helping users learn about social processes while learning from users : developing a positive feedback in social computing
Advisors: Philippe J. GiabbanelliSocial computing is concerned with the interaction of social behavior and computational systems. From its early days, social computing has had two foci. One was the development of technology and interfaces to support online communities. The other was to use computational techniques to study society and assess the expected impact of policies. This thesis seeks to develop systems for social computing, both in the context of online communities and the study of societal processes, that allow users to learn while in turn learning from users. Communities are approached through the problem of Massive Open Online Courses (MOOCs), via a complementary use of network analysis and text mining. In particular, we show that an efficient system can be designed such that instructors do not need to categorize the interactions of all students to assess their learning experience. This thesis explores the study of societal processes by showing how text analytics, visual analytics, and fuzzy cognitive map (FCM) can collectively help an analyst to understand complex scenarios such as obesity. Overall, this work had two key limitations. One was in the dataset we used, as it was small and didn't show all possible interactions, and the other is in the scalability of our systems. Future work can include the use of non-n-gram features to improve our MOOC system and the use of graph layouts for our visualization system.M.S. (Master of Science
Visualizing Evaluative Language in Relation to Constructing Identity in English Editorials and Op-Eds
This thesis is concerned with the problem of managing complexity in Systemic Functional Linguistic (SFL) analyses of language, particularly at the discourse semantics level. To deal with this complexity, the thesis develops AppAnn, a suite of linguistic visualization techniques that are specifically designed to provide both synoptic and dynamic views on discourse semantic patterns in text and corpus. Moreover, AppAnn visualizations are illustrated in a series of explorations of identity in a corpus of editorials and op-eds about the bin Laden killing. The findings suggest that the intriguing intricacies of discourse semantic meanings can be successfully discerned and more readily understood through linguistic visualization. The findings also provide insightful implications for discourse analysis by contributing to our understanding of a number of underdeveloped concepts of SFL, including coupling, commitment, instantiation, affiliation and individuation
Visual approaches to knowledge organization and contextual exploration
This thesis explores possible visual approaches for the representation of semantic structures, such as zz-structures. Some holistic visual representations of complex domains have been investigated through the proposal of new views - the so-called zz-views - that allow both to make visible the interconnections between elements and to support a contextual and multilevel exploration of knowledge. The potential of this approach has been examined in the context of two case studies that have led to the creation of two Web applications.
The \ufb01rst domain of study regarded the visual representation, analysis and management of scienti\ufb01c bibliographies. In this context, we modeled a Web application, we called VisualBib, to support researchers in building, re\ufb01ning, analyzing and sharing bibliographies. We adopted a multi-faceted approach integrating features that are typical of three di\ufb00erent classes of tools: bibliography visual analysis systems, bibliographic citation indexes and personal research assistants. The evaluation studies carried out on a \ufb01rst prototype highlighted the positive impact of our visual model and encouraged us to improve it and develop further visual analysis features we incorporated in the version 3.0 of the application.
The second case study concerned the modeling and development of a multimedia catalog of Web and mobile applications. The objective was to provide an overview of a significant number of tools that can help teachers in the implementation of active learning approaches supported by technology and in the design of Teaching and Learning Activities (TLAs). We analyzed and documented 281 applications, preparing for each of them a detailed multilingual card and a video-presentation, organizing all the material in an original purpose-based taxonomy, visually represented through a browsable holistic view. The catalog, we called AppInventory, provides contextual exploration mechanisms based on zz-structures, collects user contributions and evaluations about the apps and o\ufb00ers visual analysis tools for the comparison of the applications data and user evaluations. The results of two user studies carried out on groups of teachers and students shown a very positive impact of our proposal in term of graphical layout, semantic structure, navigation mechanisms and usability, also in comparison with two similar catalogs
Immersive Experience: Evoking the Elements of Contemplative Space in Japanese Architecture
This research project investigates the creation of
immersive contemplative viewing experiences within my visual arts
practice by identifying and adapting the fundamental elements of
Japanese contemplative space into my aesthetic and conceptual
lexicon. Contemplative experience is an intrinsic aspect of the
human experience which has become increasingly scarce in this age
of perpetual overstimulation and increasing secularisation. The
primary goal of the research project is to provide a significant
opportunity for new audiences to engage in meaningful
contemplative experience informed by the centuries-old principles
of yūgen 幽玄, ma 間, and hikari to kage 光と影 within
Japanese architecture. The studio-based research first explores
the creation of contemplative objects constructed with glass,
followed by a series of maquettes of potential immersive
contemplative environments. The research culminates with the
immersive installation, Lux Mandala, which utilises the material
characteristics of glass microspheres to synthesise the ephemeral
optical phenomenon of the “glory” into a meditative encounter
with light, shadow, space, transience and profundity. By
aesthetically locating the viewer at the centre of this
phenomenon, the viewer’s presence and perceptual mechanisms
complete a participatory loop, allowing the phenomenon to enter
into existence while enabling the viewer to reflect upon its
nature, notions of perception and transience, and the
significance of their own presence within this evanescent
tableau. The outcomes of this research project represent a
significant new nexus between visual arts practice, immersive
experience, and the essence of Japanese contemplative space
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