Corpus ID: 22143343

Using Social Media Content in the Visual Analysis of Movement Data

@inproceedings{Krger2012UsingSM,
  title={Using Social Media Content in the Visual Analysis of Movement Data},
  author={Robert Kr{\"u}ger and Steffen Lohmann and Dennis Thom and Harald Bosch and Thomas Ertl},
  year={2012}
}
Data about the movement of people and objects is a rich source for visual analysis. However, understanding the data and inferring user behavior from it is often difficult due to missing context information. The goal of our research is to augment movement data by information derived from social media. In this paper, we present a visual concept that extends movement trajectories with terms extracted from geo-coded Twitter posts. The movement data comes from a large sample of e-bikes equipped with… Expand

Figures from this paper

Interactive Visual Discovering of Movement Patterns from Sparsely Sampled Geo-tagged Social Media Data
TLDR
This work proposes a heuristic model to reduce the uncertainty caused by the nature of social media data, and presents an interactive visual analytics system to support the exploration of sparsely sampled trajectory data from social media. Expand
Visual Analysis of Movement Behavior Using Web Data for Context Enrichment
TLDR
This work presents an approach to enrich trajectory data with semantic POI information and shows how additional insights can be gained to enable analysis of movement behavior, using a density-based clustering technique. Expand
Semantic Enrichment of Movement Behavior with Foursquare–A Visual Analytics Approach
TLDR
This work suggests to enrich trajectory data with POI information using social media services and shows how semantic insights can be gained, and how to handle semantic uncertainties in time and space, which result from noisy, unprecise, and missing data. Expand
Casual analytics: advancing interactive visualization by domain knowledge
TLDR
This thesis introduces novel approaches at the boundary of generic analysis tools and their domain-specific context to extend the usage of visual analytics to casual users by exploiting domain knowledge for supporting analysis tasks, input validation, and personalized information visualization. Expand
Uncertainty-aware visual analytics for exploring human behaviors from heterogeneous spatial temporal data
TLDR
This work proposed a semi-automatic approach, for users to solve the conflicts and identify the uncertainties, and combined with the uncertainty-aware methods, proposed a visual analytics system to analyze human behaviors, detect patterns and find outliers. Expand
Mobile-Based Intelligent Transportation for Bus Commuters Based on Twitter Analytics
In this paper, we present an intelligent, state-of-the-art, mobile-based transportation system called SAFAR (Safe and Fast around the Road), which provides dynamic information to Karachi busExpand
LDA Ensembles for Interactive Exploration and Categorization of Behaviors
TLDR
This work proposes an approach leveraging topic modeling techniques – LDA (Latent Dirichlet Allocation) Ensembles – to represent categories of typical behaviors by topics that are obtained through topic modeling a behavior collection. Expand
Visual Analytics of Social Media for Situation Awareness
TLDR
German Abstract — Zusammenfassung wirklich €1,000,000 (Bundesliga) — Einigkeit und Wirklichkeit zu einem ganzbereinigungsjahr 2017, 3:00-4:00 Uhr. Expand
Visual analytics of human mobility behavior
xiii

References

SHOWING 1-8 OF 8 REFERENCES
Spatiotemporal anomaly detection through visual analysis of geolocated Twitter messages
TLDR
This work uses a novel cluster analysis approach and distinguish between local event reports and global media reaction to detect spatiotemporal anomalies automatically to allow for an interactive analysis of location-based microblog messages in realtime by means of scalable aggregation and geolocated text visualization. Expand
Visual analytics tools for analysis of movement data
TLDR
It is argued that by using the right visual analytics tools for the analysis of massive collections of movement data, it is possible to effectively support human analysts in understanding movement behaviors and mobility patterns. Expand
Earthquake shakes Twitter users: real-time event detection by social sensors
TLDR
This paper investigates the real-time interaction of events such as earthquakes in Twitter and proposes an algorithm to monitor tweets and to detect a target event and produces a probabilistic spatiotemporal model for the target event that can find the center and the trajectory of the event location. Expand
A Visual Backchannel for Large-Scale Events
TLDR
The Visual Backchannel design provides an evolving, interactive, and multi-faceted visual overview of large-scale ongoing conversations on Twitter, and includes visual saliency for what is happening now and what has just happened in the context of the evolving conversation. Expand
The Backchannel: How Audiences are Using Twitter and Social Media and Changing Presentations Forever
Part 1: The Death of PowerPoint and the Rebirth of Conversation 1. A PowerPoint Chip on Our Shoulder 2. Opening the Backchannel Floodgates 3. Renegotiating a Social Contract: The new PresentationExpand
Document Word Clouds: Visualising Web Documents as Tag Clouds to Aid Users in Relevance Decisions
TLDR
The idea of enhancing the perception of web documents with visualisation techniques borrowed from the tag clouds of Web 2.0 is taken at. Expand
Comparison of Tag Cloud Layouts: Task-Related Performance and Visual Exploration
TLDR
Results from a comparative study of several tag cloud layouts show differences in task performance, leading to the conclusion that interface designers should carefully select the appropriate tag cloud layout according to the expected user goals. Expand
From Data Analysis and Visualization to Causality Discovery
As data becomes invisible, emerging technologies can help human analysts and decision makers understand, model, and visualize causal relationships.