Arno Scharl
Short Bio
Arno Scharl is a Professor of Information Systems and the Director of the Research Center for New Media Technology at Modul University Vienna. Prior to this appointment, he held professorships at Graz University of Technology and the University of Western Australia, and the position of a Key Researcher at the Austrian Competence Center for Knowledge Management. Mr. Scharl completed his doctoral research at the Vienna University of Economics and Business, and also holds a PhD and MSc from the University of Vienna, Department of Sports Physiology. Returning from fellowships at the University of California at Berkeley and Curtin University of Technology (funded by an Erwin Schrödinger Research Grant of the Austrian Science Fund), he submitted his habilitation on “Evolutionary Web Development” to the Vienna University of Economics and Business, for which he was awarded the venia docendi and the Senator Wilhelm Wilfling Award in 2000. Mr. Scharl edited two books in Springer’s Advanced Information and Knowledge Processing Series on "The Geospatial Web" and “Environmental Online Communication”, founded the ECOresearch Network and served as co-chair of the 20th International Conference on Informatics for Environmental Protection.
Research Interests
His current research interests focus on text mining, integrating semantic and geospatial Web technology, media monitoring, virtual communities and computer-mediated collaboration.
Courses @ MU
- Social Media Intelligence
- Search Engine Optimization and Marketing
- Master Thesis Tutorial
Awards
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2019 : Best Paper Award (International Conference on Blockchain 2019)
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2007 : Digital Earth 3D Visualization Grand Challenge Winner (NASA, Google, ESRI)
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1997 : Rudolf Sallinger-Award (Österreichischer Wirtschaftsbund)
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1998 : Excellent Doctoral Thesis Award (University of Vienna)
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1998 : Stephan Koren-Award (Wirtschaftsuniversität Wien)
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1999 : OeNB-WU Research Prize (Austrian National Bank)
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1999 : Erwin Schrödinger Research Grant (FWF Der Wissenschaftsfonds)
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2000 : Senator Wilhelm-Wilfling-Award (Senator Wilhelm Wilfling Stiftung)
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2008 : Austrian National Award for Multimedia and e-business (Bundesministerium für Wissenschaft, Forschung und Wirtschaft)
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2008 : FIT-IT Award 3rd prize (Bundesministerium für Verkehr, Innovation und Technology)
Projects
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A Digital Well-Being Index for Vienna
How can stakeholders get insights into perceived well-being in a timely manner and related to specific aspects of urban environments? Comprehensive national surveys are costly, require significant organizational effort and are a careful balance between knowledge to be gained and burden placed on respondents. To address these challenges, DWBI will use AI-based natural language processing in conjunction with evolving knowledge graphs to extract affective knowledge from user-generated digital content. Automatically mapped to existing indicators, this knowledge will complement and enrich survey-based approaches and traditional assessment methodologies, mitigating some of the associated problems.
Organisations: MODUL University Vienna, School of Sustainability, Governance, and Methods
Author: Arno Scharl, Ivo Ponocny, Sabine Sedlacek, Adrian Brasoveanu, Agnieszka Skwara
Date: 01.10.2021 - 30.09.2024
Managed By: MODUL University Vienna
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Qualifikationsnetzwerk "Smart Data Analytics für die Hotellerie"
The purpose of the qualification network is to teach employees of tourism businesses - especially accommodation providers - the use of data and advanced methods of analysis. Data management and analysis is considered a central element of digitalization in tourism and the added value of an efficient and effective data processing is given in the companies. The aim is to teach the state of research in a way that enables businesses to explore new sources of data and to link these sources to generate better information for decision-making. With this knowledge, businesses should be better able to accompany and to consult the guest during the whole "customer-journey". For this purpose, the scientific partners MODUL University Vienna and Technical University Vienna combine their expertise in the area of data management and tourism.
Organisations: School of Tourism and Service Management, MODUL University Vienna, Research Center of New Media Technology
Author: Hannes Antonschmidt, Astrid Dickinger, Ulrich Gunter, Lyndon Nixon, Daniel Dan, Arno Scharl
Date: 01.07.2019 - 31.12.2020
Managed By: School of Tourism and Service Management
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Digital Tourism Experts
The aim of the "Digital Tourism Expert" initiative is to provide the participating company partner with relevant digital know-how and to test and implement it with the help of initial digital projects (Transfer-Projects). Therefore, 14 educational modules were developed which on the one hand deliver digital marketing know-how and on the other hand provide knowledge to create the right structural requirements for becoming a digital tourism company. Both competencies will create the skills to implement a digital transfer project in the final phase of the project. In these projects the companies implement innovative digital processes or projects guided by the coaches from the universities.
Organisations: MODUL University Vienna, School of Tourism and Service Management, Research Center of New Media Technology
Author: Karl Wöber, Astrid Dickinger, Arno Scharl
Date: 01.01.2018 - 31.12.2020
Managed By: MODUL University Vienna
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RAVEN - Relation Analysis and Visualization for Evolving Networks
The RAVEN research project's aim is to keep users, analysts and decision-makers up-to-date about the unfolding of events in endogenous and exogenous information spaces, which themselves reflect interconnected events and processes of the real world. RAVEN aims to understand the evolution of these spaces by analyzing temporal-semantic relations between their elements. RAVEN has a social layer by enabling users to release non-confidential interpersonal messages to this repository, and by extracting annotations from retrieved documents. Third-party resources are added through a Web mining and media monitoring platform.
Organisations: MODUL University Vienna, Research Center of New Media Technology, School of Tourism and Service Management
Author: Arno Scharl, Stefan Gindl, Astrid Dickinger
Date: 01.01.2008 - 30.10.2010
Managed By: Research Center of New Media Technology
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UNEP Live
UNEP Live is a Web intelligence platform for global environmental indicators and related communication flows. It helps stakeholders to meet environmental goals and foster sustainable development. The platform analyzes public opinion trends on air quality, biodiversity and climate change from news and social media, policy makers, and environmental organizations. Fully integrated into the UNEP Live knowledge management platform, webLyzard helps align and compare relevant articles and postings from these online sources with various environmental indicators.
Organisations: MODUL University Vienna, Research Center of New Media Technology
Author: Arno Scharl, Ruslan Kamolov, Rod Michael Coronel, Lucas Gerrand, Tim Lammarsch
Date: 01.04.2015 - 31.05.2016
Managed By: MODUL University Vienna
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DIVINE - 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, Research Center of New Media Technology
Author: Arno Scharl, Marta Sabou, Stefan Gindl, Alexander Hubmann-Haidvogel
Date: 01.07.2011 - 31.12.2013
Managed By: Research Center of New Media Technology
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ETIHQ - Exposing Tourism Indicators as High Quality Linked Data
Although the tourism domain heavily relies on complex decision making, it currently lacks decision support systems with the capability to seamlessly integrate and visualise data from multiple data sources of tourism (and other) indicators. Linked Data technologies, by contrast, especially when adopted at large scale, greatly facilitate data integration at the syntactic and semantic level alike by providing a uniform data encoding format. Such technologies also help to clearly specify the meaning of the data and to establish links between various datasets. In this project we will use Linked Data technologies to create a reference repository of tourism indicators (ETIHQ) by exposing the content of TourMIS, a major source of European tourism statistics, as high-quality Linked Data. We will ensure data quality by providing semantically rich vocabularies that will support (i) the specification of the meaning of tourism statistics and (ii) the provenance of the data items. To demonstrate the benefits of using Linked Data, we will design and implement a decision support system that makes use of the ETIHQ repository and leverages its detailed semantic specifications to provide appropriate access control mechanisms.
Organisations: Research Center of New Media Technology, School of Tourism and Service Management, MODUL University Vienna
Author: Marta Sabou, Adrian Brasoveanu, Irem Önder, Arno Scharl, Karl Wöber
Date: 01.10.2013 - 01.10.2014
Managed By: Research Center of New Media Technology
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Media Watch on Climate Change
The Media Watch on Climate Change is a comprehensive and continuously updated knowledge repository on climate change and related environmental issues. The dashboard provides interactive means to access this repository, analyze stakeholder perceptions, and track emerging trends. It collects, filters, annotates and visualizes documents from a wide range of English, French and German online sources (news media, social networking platforms, Web sites of Fortune 1000 companies and environmental organizations).
Organisations: MODUL University Vienna, Research Center of New Media Technology
Author: Arno Scharl
Date: 01.08.2007 - 31.03.2015
Managed By: MODUL University Vienna
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Forstrat Cockpit 2
The project Foresight-Cockpit 2.0 supplements the preceding project by enabling the analysts to process a greater variety of topics simultaneously and independently. By this, it aims at improving the collaboration between different departments in the development of a common situational awareness based on real-time data. In order to achieve this, it integrates in the system modern methods and tools for social media analysis, which will support the creation, evaluation and deduction of trends and scenarios. Additionally, the improved software will make it easier to translate the results of the analyses in alternative strategic courses of action that are relevant from a national perspective.
Organisations: MODUL University Vienna, Research Center of New Media Technology
Author: Arno Scharl
Date: 01.10.2016 - 30.09.2017
Managed By: Research Center of New Media Technology
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US Election 2004 Web Monitor
The | US Election 2004 Web Monitor Web Monitor captures the Web sites of the Fortune 1000 (the biggest US companies in terms of revenue), environmental organizations and international media from the US, Canada, UK, Australia and New Zealand. From these sites, the system processes more than 500,000 documents each week, comprising about 125 million words in 11 million sentences. Estimates of attention and attitude towards the presidential candidates complement keywords summarizing key issues associated with each candidate.
Organisations: MODUL University Vienna, Research Center of New Media Technology
Author: Arno Scharl
Date: 01.01.2004 - 31.12.2005
Managed By: MODUL University Vienna
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Information Diffusion across Interactive Online Media
IDIOM is a two-year research project funded by FIT-IT Semantic Systems, a program of the Federal Ministry of Transport, Innovation and Technology in cooperation with the Austrian Research Promotion Agency (FFG) and Eutema Technology Management. IDIOM aims to: - investigate new visual interfaces to create, access and analyze electronic content; - reveal fundamental mechanisms of information diffusion across media with distinct interactive characteristics. Recent advances in collaborative Web technology are governed by strong network effects and the harnessing of collective intelligence through customer-self service and algorithmic data management. As a result, information spreads rapidly across Web sites, blogs, Wiki applications, and direct communication channels between members of online communities who utilize these services. The IDIOM (Information Diffusion across Interactive Online Media) project will support and investigate electronic interactivity by means of a generic, service-oriented architecture. This architecture will include ontology-based tools to build and maintain contextualized information spaces, a framework for analyzing content diffusion and interaction patterns within these spaces, and interface technology that enables users switch between semantic and geospatial topologies. IDIOM introduces Knowledge Planets as a radically new interface metaphor that leverages the new generation of geo-browsing platforms such as NASA World Wind and Google Earth as a front-end for its portfolio of semantic services. Linguists define “Idiom” as an expression whose meaning is different from the literal meanings of its component words. Similarly, the study of information diffusion promises insights that cannot be inferred from individual network elements. Despite growing research interest, the “Web 2.0” is still dominated by prototypes and mash-ups. At the same time, media monitoring and corporate knowledge management projects lack analytical frameworks, focus on one particular medium, or neglect the dual role of users as consumers and producers of information. IDIOM will address these gaps to reveal fundamental mechanisms of information diffusion across media with distinct interactive characteristics, providing a set of generic services to analyze the production and consumption of electronic content simultaneously.
Organisations: School of Tourism and Service Management, MODUL University Vienna, Research Center of New Media Technology
Author: Astrid Dickinger, Arno Scharl
Date: 06.07.2006 - 05.06.2009
Managed By: Research Center of New Media Technology
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Climate Change Collaboratory (Triple-C)
The Climate Change Collaboratory (Triple-C) aims to strengthen the relations between environmental stakeholders who recognize the need for climate change adaptation and mitigation, but differ in their specific worldviews, goals and agendas. For this purpose, the collaboratory provides tools to manage expert knowledge as well as a context-sensitive environment for creating and editing documents in a collaborative manner. Building upon the award-winning technology behind the Media Watch on Climate Change, the user's semantic context is provided by a real-time synchronization framework for rendering advanced visualizations including information landscapes, geographic projections, and ontology graphs. Innovative survey instruments in the tradition of “games with a purpose” create shared meaning through collaborative ontology building, and leverage the extensive user base of social networking platforms to capture indicators of environmental attitudes, lifestyles and behaviors. Two project workshops help align Triple-C with the research activities of its associate partners, increase the project’s visibility, and foster the collaboration with leading international organizations.
Organisations: MODUL University Vienna, Research Center of New Media Technology
Author: Arno Scharl, Sabine Sedlacek
Date: 01.03.2010 - 20.09.2012
Managed By: Research Center of New Media Technology
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uComp
The rapid growth and fragmented character of social media and publicly available structured data challenges established approaches to knowledge extraction. Many algorithms fail when they encounter noisy, multilingual and contradictory input. Efforts to increase the reliability and scalability of these algorithms face a lack of suitable training data and gold standards. Given that humans excel at interpreting contradictory and context-dependent evidence, the uComp project will address the above mentioned shortcomings by merging collective human intelligence and automated knowledge extraction methods in a symbiotic fashion. The project will build upon the emerging field of Human Computation (HC) in the tradition of games with a purpose and crowdsourcing marketplaces. It will advance the field of Web Science by developing a scalable and generic HC framework for knowledge extraction and evaluation, delegating the most challenging tasks to large communities of users and continuously learning from their feedback to optimise automated methods as part of an iterative process. A major contribution is the proposed foundational research on Embedded Human Computation (EHC), which will advance and integrate the currently disjoint research fields of human and machine computation. EHC goes beyond mere data collection and embeds the HC paradigm into adaptive knowledge extraction workflows. An open evaluation campaign will validate the accuracy and scalability of EHC to acquire factual and affective knowledge. In addition to novel evaluation methods, uComp will also provide shared datasets and benchmark EHC against established knowledge processing frameworks. While uComp methods will be generic and evaluated across domains, climate change was chosen as the main use case for its challenging nature, subject to fluctuating and often conflicting interpretations. Public showcases include the Media Watch on Climate Change and the Climate Resilience Toolkit. The ongoing collaboration with international organisations such as the Climate Program Office of the National Oceanic and Atmospheric Administration (NOAA) and the NASA Earth Observatory will increase impact, provide a rich stream of input data, attract and retain a critical mass of users, and promote the adoption of EHC among a wide range of stakeholders.
Organisations: MODUL University Vienna, Research Center of New Media Technology
Author: Arno Scharl
Date: 15.11.2012 - 14.05.2016
Managed By: MODUL University Vienna
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DecarboNet
DecarboNet is a research project funded by the European Commission to investigate the potential of social platforms in mitigating climate change. Engaging the public in energy debates and encouraging behaviour change are essential strategies for reducing energy consumption and saving our planet. Studies show that information and technology alone are insufficient for changing behaviour towards more sustainable lifestyle choices, and that what is needed is a combination of socio-technical interventions. How to raise awareness collectively by means of social platforms and how to transform it into behaviour change are some of the challenges addressed by the project’s research agenda. DecarboNet is funded by CAPS (Collective Awareness Platforms for Sustainability & Social Innovation), a FP7 and H2020 research programme of the European Commission to enable new forms of social innovation and leverage emerging network effects by combining social media, distributed knowledge creation and data from the “Internet of Things”, increasing awareness and identifying possible solutions to problems that require collective efforts. Witness emerging DecarboNet technologies in action by exploring the Media Watch on Climate Change, participating in the Climate Challenge, or using the faceted search of the Climate Resilience Toolkit.
Organisations: MODUL University Vienna, Research Center of New Media Technology
Author: Arno Scharl
Date: 01.10.2013 - 30.11.2016
Managed By: MODUL University Vienna
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PHEME – Computing Veracity across Media, Languages, and Social Networks
Analyzing big data repositories aggregated from context-dependent social media streams poses three major computational challenges: volume, velocity, and variety. This project will focus on a fourth, hitherto largely unstudied computational challenge: veracity. It will model, identify, and verify phemes (Internet memes with added information on truthfulness or deception) as they spread across media, languages, and social networks.
Organisations: MODUL University Vienna, Research Center of New Media Technology
Author: Arno Scharl
Date: 01.10.2013 - 31.03.2017
Managed By: MODUL University Vienna
Research Output
- 2020
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"Topics Compass: uncovering Trending Topics for Optimised Media Content Publication"2020
Author(s): Lyndon Nixon, Arno Scharl, Rasa Bocyte
Publication date: 14. 6. 2020
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"Automatic Expansion of Domain-Specific Affective Models for Web Intelligence Applications"2020 in: Cognitive Computation.
Background. Sentic computing relies on welldefined affective models of different complexity - polarity to distinguish positive and negative sentiment,
for example, or more nuanced models to capture expressions of human emotions. When used to measure
communication success, even the most granular affective model combined with sophisticated machine learning approaches may not fully capture an organisation’s
strategic positioning goals. Such goals often deviate from
the assumptions of standardised affective models. While
certain emotions such as Joy and Trust typically represent desirable brand associations, specific communication goals formulated by marketing professionals often
go beyond such standard dimensions. For instance, the
brand manager of a television show may consider fear
or sadness to be desired emotions for its audience.
Method. This article introduces expansion techniques
for affective models, combining common and commonsense knowledge available in knowledge graphs with
language models and affective reasoning, improving coverage and consistency as well as supporting domainspecific interpretations of emotions.
Results and Conclusions. An extensive evaluation
compares the performance of different expansion techniques: (i) a quantitative evaluation based on the revisited Hourglass of Emotions model to assess perfor
mance on complex models that cover multiple affective categories, using manually compiled gold standard
data, and (ii) a qualitative evaluation of a domainspecific affective model for television programme brands.
The results of these evaluations demonstrate that the
introduced techniques support a variety of embeddings
and pre-trained models. The paper concludes with a
discussion on applying this approach to other scenarios
where affective model resources are scarce.Author(s): Albert Weichselbraun, Jakob Steixner, Adrian Brasoveanu, Arno Scharl, Max Göbel, Lyndon Nixon
Publication date: 2020
Electronic version(s), related files and links: http://dx.doi.org/10.1007/s12559-021-09839-4
- 2019
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"Forecasting Tourist Arrivals With the Help of Web Sentiment: A Mixed-Frequency Modeling Approach for Big Data"2019 in: Tourism Analysis. Volume: 24. Issue number: 4 Pages: 437-452
Online news media coverage regarding a destination, a form of big data, can affect destination image and influence the number of tourist arrivals. Sentiment analysis extracts the valence of an author’s perception about a topic by rating a segment of text as either positive or negative. The sentiment of online news media can be viewed as a leading indicator for actual tourism demand. The aim of this study is to examine if web sentiment of online news media coverage of four European cities (Berlin, Brussels, Paris, and Vienna) possesses information to predict actual tourist arrivals. This study is the first to use web sentiment for forecasting tourism demand. Automated semantic routines were conducted to analyze the sentiment of online news media coverage. Due to the differing data frequencies of tourist arrivals (monthly) and web sentiment indicators (daily), the MIxed-DAta Sampling (MIDAS) modeling approach was applied. Results indicate that MIDAS models including various web sentiment indicators outperform time-series and naïve benchmarks in terms of typical accuracy measures. This study shows that utilizing online news media coverage as an indication of destination image can improve tourism demand forecasting. Because destination image is dynamic, the results can vary depending on time period of the analysis and the destination. A managerial implication of the forecast evaluation exercise is that destination management organizations (DMOs) should add models incorporating web sentiment data to their forecast modeling toolkit to further improve the accuracy of their tourism demand forecasts.
Author(s): Irem Önder, Ulrich Gunter, Arno Scharl
Publication date: 2019
Volume: 24
Issue number: 4
Pages: 437-452
Electronic version(s), related files and links: http://dx.doi.org/10.3727/108354219X15652651367442
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"Real time story detection and video retrieval from social media streams"2019 Pages: 17-52
Author(s): Lyndon Nixon, Arno Scharl, Daniel Fischl
Publication date: 2019
Publisher: Springer
Pages: 17-52
Host publication editor(s): V. Mezaris, L. Nixon, S. Papadopoulos, D. Teyssou
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"Multimodal analytics dashboard for story detection and visualisation"2019 Pages: 281-299
Author(s): Lyndon Nixon, Arno Scharl, Alexander Hubmann-Haidvogel, Max Göbel, Tobi Schäfer, Daniel Fischl
Publication date: 2019
Publisher: Springer
Pages: 281-299
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