Alexander C. Hubmann-Haidvogel is a Researcher and Lecturer in MODUL University Vienna’s Department of New Media Technology. His research interests include social networks, information visualization, and human-computer interaction. Hubmann-Haidvogel has an MSc in Telematics from Graz University of Technology.
He is involved in several Austrian and European research projects, leading the Web front-end development team at MODUL University responsible for the Media Watch on Climate Change and related technologies.
Prior to joining MODUL University, Hubmann-Haidvogel was a member of the Research Institute for Computational Methods at Vienna University of Economics and Business, and has been part of the development team at Gentics Software GmbH and Hyperwave GmbH.
Arno Scharl, Marta Sabou, Stefan Gindl, Alexander Hubmann-HaidvogelDIVINE - Dynamic Integration and Visualization of Information from Multiple Evidence Sources
DIVINE integrates data from structured, unstructured and social sources to build information spaces. Lightweight seed ontologies act as focal points for integrating new evidence from third-party sources. Since such evidence is inherently uncertain, source-specific transformation rules assign confidence values to newly acquired pieces of knowledge.
Organisations: MODUL University Vienna, Department of New Media Technology
Author: Arno Scharl, Marta Sabou, Stefan Gindl, Alexander Hubmann-Haidvogel
Date: 01.07.2011 - 31.12.2013
Managed By: Department of New Media Technology
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"Visualizing statistical linked knowledge for decision support"2017 in: Semantic Web Journal. Volume: 8. Issue number: 1 Pages: 113-137
In a global and interconnected economy, decision makers often need to consider information from various domains. A tourism destination manager, for example, has to correlate tourist behavior with financial and environmental indicators to allocate funds for strategic long-term investments. Statistical data underpins a broad range of such cross-domain decision tasks. A variety of statistical datasets are available as Linked Open Data, often incorporated into visual analytics solutions to support decision making. What are the principles, architectures, workflows and implementation design patterns that should be followed for building such visual cross-domain decision support systems. This article introduces a methodology to integrate and visualize cross-domain statistical data sources by applying selected RDF Data Cube (QB) principles. A visual dashboard built according to this methodology is presented and evaluated in the context of two use cases in the tourism and telecommunications domains.
Author(s): Adrian Brasoveanu, Marta Sabou, Arno Scharl, Alexander Hubmann-Haidvogel, Daniel Fischl
Publication date: 2017
Issue number: 1
Electronic version(s), related files and links: http://dx.doi.org/10.3233/SW-160225
Irem Önder, Wolfgang Körbitz, Alexander Hubmann-Haidvogel"Tracing Tourists by Their Digital Footprints - The Case of Austria"2016 in: Journal of Travel Research. Volume: 55. Issue number: 5 Pages: 1-8
Traditional tourism data collection includes surveys, interviews and focus groups. However, these methods are both expensive and time consuming. Moreover, there is a lag between the time of data collection and the receipt of that data for analysis. Today, almost all individuals leave digital footprints on the Internet, which can also be used for tourism research. One type of digital footprint is the photos uploaded on websites such as Flickr. The aim of this study is to determine whether the digital footprints in Flickr provide a useful indicator for tourism demand. Photos tagged with “Austria” between 2007 and 2011 were collected using Flickr API. Residents were distinguished from tourists using the data, and spatial analyses were conducted of the tourist-generated data. The results indicate that geotagged photos in Austria are more representative of actual tourist numbers at the city level than at the regional level.
Author(s): Irem Önder, Wolfgang Körbitz, Alexander Hubmann-Haidvogel
Publication date: 5. 2016
Issue number: 5
Arno Scharl, Alexander Hubmann-Haidvogel, Alistair Jones, Daniel Fischl, Ruslan Kamolov, Albert Weichselbraun, Walter Rafelsberger"Analyzing the public discourse on works of fiction – Detection and visualization of emotion in online coverage about HBO’s Game of Thrones - Emotion and Sentiment in Social and Expressive Media"2016 in: Information Processing & Management. Volume: 52. Issue number: 1 Pages: 129-138
This paper presents a Web intelligence portal that captures and aggregates news and social media coverage about “Game of Thrones”, an American drama television series created for the HBO television network based on George R.R. Martin’s series of fantasy novels. The system collects content from the Web sites of Anglo-American news media as well as from four social media platforms: Twitter, Facebook, Google+ and YouTube. An interactive dashboard with trend charts and synchronized visual analytics components not only shows how often Game of Thrones events and characters are being mentioned by journalists and viewers, but also provides a real-time account of concepts that are being associated with the unfolding storyline and each new episode. Positive or negative sentiment is computed automatically, which sheds light on the perception of actors and new plot elements.
Author(s): Arno Scharl, Alexander Hubmann-Haidvogel, Alistair Jones, Daniel Fischl, Ruslan Kamolov, Albert Weichselbraun, Walter Rafelsberger
Publication date: 1. 2016
Issue number: 1
Electronic version(s), related files and links: http://dx.doi.org/10.1016/j.ipm.2015.02.003
Arno Scharl, David Herring, Walter Rafelsberger, Alexander Hubmann-Haidvogel, Ruslan Kamolov, Daniel Fischl, Michael Föls, A. Weichselbraun"Semantic Systems and Visual Tools to Support Environmental Communication"2015 in: IEEE Systems Journal. Pages: 1-10
Given the intense attention that environmental topics such as climate change attract in news and social media coverage, scientists and communication professionals want to know how different stakeholders perceive observable threats and policy options, how specific media channels react to new insights, and how journalists present scientific knowledge to the public. This paper investigates the potential of semantic technologies to address these questions. After summarizing methods to extract and disambiguate context information, we present visualization techniques to explore the lexical, geospatial, and relational context of topics and entities referenced in these repositories. The examples stem from the Media Watch on Climate Change, the Climate Resilience Toolkit and the NOAA Media Watch—three applications that aggregate environmental resources from a wide range of online sources. These systems not only show the value of providing comprehensive information to the public, but also have helped to develop a novel communication success metric that goes beyond bipolar assessments of sentiment.
Author(s): Arno Scharl, David Herring, Walter Rafelsberger, Alexander Hubmann-Haidvogel, Ruslan Kamolov, Daniel Fischl, Michael Föls, A. Weichselbraun
Publication date: 8. 9. 2015
Electronic version(s), related files and links: http://dx.doi.org/10.1109/JSYST.2015.2466439
Arno Scharl, Alexander Hubmann-Haidvogel, Marta Sabou, Albert Weichselbraun, Heinz-Peter Lang"From Web Intelligence to Knowledge Co-Creation: A Platform for Analyzing and Supporting Stakeholder Communication"2013 in: IEEE Internet Computing. Volume: 17. Issue number: 5 Pages: 21-29
Organizations require tools that can assess their online reputations as well as the impact of their marketing and public outreach activities. The Media Watch on Climate Change is a Web intelligence and online collaboration platform that addresses this requirement. It aggregates large archives of digital content from multiple stakeholder groups and enables the co-creation and visualization of evolving knowledge archives. Here, the authors introduce the base platform and a context-aware document editor as an add-on that supports concurrent authoring by multiple users. While documents are being edited, semantic methods analyze them on the fly to recommend related content. The system computes positive or negative sentiment automatically to provide a better understanding of third-party perceptions. The editor is part of an interactive dashboard that uses trend charts and map projections to show how often and where relevant information is published, and to provide a real-time account of concepts that stakeholders associate with a topic.
Author(s): Arno Scharl, Alexander Hubmann-Haidvogel, Marta Sabou, Albert Weichselbraun, Heinz-Peter Lang
Publication date: 9. 2013
Issue number: 5
Electronic version(s), related files and links: http://dx.doi.org/doi.ieeecomputersociety.org/10.1109/MIC.2013.59
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