Abstracts for Papers (Preliminary Programme)

Monday, March 13, 15:30-17:30 - Information Behaviour

Comparing Information Literacy of Students from University of Graz (Austria) and Chungbuk National University (Republic of Korea) (long)
Rust Kathrin, Christian Schlögl and Dongback Seo

Abstract: In this article we present the results of a study in which we compared information literacy of master students from the University of Graz and Chungbuk National University (CBNU). Data were collected using a multiple-choice questionnaire which consisted of the following parts: demographic data, self-assessment of one’s information literacy, use of information sources, and knowledge test. The latter was designed on the basis of the Information Literacy Competency Standards for Higher Education (ALA 2000). Data were collected in two classes of the Business Administration program at the University of Graz. At CBNU, the study participants were subscribed to the master programs of Business Administration, Management Information Systems, and Psychology. Usually, it took the students 20 minutes to fill out the questionnaire. The results reveal that students from the University of Graz have a clearly higher level of information literacy than their colleagues from CBNU. To some degree, this might be due to cultural and social differences. It was expected that the Korean students are more open toward the use of modern information and communication technologies. However, this does not automatically go along with a higher level of information literacy.

Visualising Topics in Document Collections: An analysis of the interpretation processes of historians (long)
Anastasia Christoforidis, Ben Heuwing and Thomas Mandl

Abstract: This paper discusses the suitability of two multivariate visualisations that give insights into topic model distributions across sub-collections of a collection of historical textbooks in the context of a digital humanities project. Results of a qualitative user study with representatives of the target group (n=5) indicate that network graphs are more appropriate for revealing general connections among sub-collections, while small-multiples of heatmaps of topic correlations are more suitable for a finer grained analysis of the connections between specific topics. We analyse the user behaviour during analysis to identify general activities of the interpretation of topic models as well as activities of interpreting visual elements that are specific to each visualisation. Based on this, potential usability problems and resulting requirements are highlighted.

An Eye-Tracking Study on Differences in Information Transfer by Infographics (long)
Barbara Ströhl, Kilian Ganz, Stephanie Richter, Kilian Zieglmeier and Rainer Hammwöhner

Abstract: Information graphics are commonly used to display information. But the retention of information can differ depending on the presentation of the content. A topic that is currently present to all of us in the media is the refugee influx to Europe. As it caused a lot of chaos, confusion and anxiety, the transfer of information played and still plays a crucial role, which is why we chose two different graphics visualizing facts and information about refugees. Our aims were to get insights into the readers’ information behavior dealing with information graphics and to find differences in information transfer. Therefore, we conducted eye-tracking experiments and analyzed the fixation time and the fixation count on both textual and non-textual elements of the infographics. After reading, the retention of information was tested using free text questions and summed up in a score that was evaluated. Results showed that the subjects had spent most of their time on textual elements for each infographic. The viewing behavior did not differ significantly between the two graphics. Despite this, we found significant differences in information transfer. This might be due to the fact that one infographic had fewer sub-topics. Each of these sub-topics was backed by the repetition of several textual and non-textual elements as well as additional details, which broadened the context.

Are ads on Google search engine results pages labeled clearly enough? The influence of knowledge on search ads on users’ selection behavior (long)
Dirk Lewandowski, Sebastian Sünkler and Friederike Kerkmann

Abstract: In an online experiments using a representative sample of the German online population (n=1,000), we compare users’ selection behavior on two versions of the same Google search engine results page, one showing advertisements and organic results, the other showing organic results only. Selection behavior is analyzed in relation to users’ knowledge on Google’s business model, on SERP design, and on these users’ actual performance in marking advertisements on SERPs correctly. We find that users who were not able to mark ads correctly selected ads significantly more often. This leads to the conclusion that ads need to be labeled more clearly, and that there is a need for more information literacy in search engine users.

Tuesday, March 14, 10:30-12:30 - Designing Scholarly Information Systems

A Reference Architecture for Virtual Research Environments (long)
Keith Jeffery, Carlo Meghini, Cesare Concordia, Theodore Patkos, Valerie Brasse, Jacco van Ossenbruck, Yannis Marketakis, Nikos Minadakis and Eda Marchetti

Abstract: This paper describes the Reference Architecture of the enhanced VRE (e-VRE), a Virtual Research Environment defined in the context of the VRE4EIC Project, funded by EU H2020 e-Infrastructure program. e-VRE is designed to overcome limits of existing VREs with respect to a number of orthogonal dimensions: improving the quality of VRE user experience by providing user centered, secure, privacy compliant, sustainable environments for accessing data, composing workflows and tracking data publications; increasing VRE usage in multidisciplinary research domains by Abstracting and reusing building blocks and workflows from existing VRE initiatives; improving the interoperability of heterogeneous discovery, contextual and detailed metadata across all layers of the VRE.

VirtualPatent - Enabling the Traceability of Ideas Shared Online using Decentralized Trusted Timestamping (short)
Corinna Breitinger and Bela Gipp

Abstract: Online discussion and sharing platforms have allowed disseminating ideas more quickly than ever before. However, there are many good reasons why people hesitate to share ideas online. For instance, academics may want to ensure that their idea is not made public until they have published it in a paper to ensure that they are appropriately credited. As a consequence, some novel ideas or creative work might only be shared within a small circle of trusted peers instead of with wider audiences online. In such cases, other experts on a specific topic are unable to contribute to the discussion. In this paper, we present a proof-of-concept implementation of an online discussion and sharing platform that addresses this problem. The web-based application, coined VirtualPatent, automatically timestamps each post a user shares by creating a distributed timestamp on the blockchain of the cryptocurrency Bitcoin – a method for trusted-timestamp creation that we published in a previous paper. Unlike platform-managed timestamps, timestamps stored on the blockchain are persistent and cannot be tampered with. The system thus enables the author of a posting to retrospectively prove the exact time that a specific contribution was first shared online in a tamperproof manner – similar to a published paper, but with the simplicity of writing a post on a social media website.

Stereotype and Most-Popular Recommendations in the Digital Library Sowiport (long)
Joeran Beel, Siddharth Dinesh, Philipp Mayr, Zeljko Carevic and Raghvendra Jain

Abstract: Stereotype and most-popular recommendations are widely neglected in the research-paper recommender-system and digital-library community. In other domains such as movie recommendations and hotel search, however, these recommendation approaches have proven their effectiveness. We were interested to find out how stereotype and most-popular recommendations would perform in the scenario of a digital library. Therefore, we implemented the two approaches in the recommender system of GESIS’ digital library Sowiport, in cooperation with the recommendations-as-a-service provider Mr. DLib. We measured the effectiveness of most-popular and stereotype recommendations with click-through rate (CTR) based on 28 million delivered recommendations. Most-popular recommendations achieved a CTR of 0.11%, and stereotype recommendations achieved a CTR of 0.124%. Compared to a “random recommendations” baseline (CTR 0.12%), and a content-based filtering baseline (CTR 0.145%), the results are discouraging. However, for reasons explained in the paper, we concluded that more research is necessary about the effectiveness of stereotype and most-popular recommendations in digital libraries.

Tuesday, March 14, 14:00-15:30 – User Perceptions of Information Systems

Content, Physical Appearance, Copy Condition: Tagging Customer Book Reviews (short)
Tjaša Jug and Maja Žumer

Abstract: Users of online bookstores are not interested only in general book description when searching and buying books, but also in subjective reader opinion, which could be found in online reviews. Reviewers usually comment on book content, but may also mention other aspects of the received book, such as binding, illustrations, translation etc. Meanwhile buyers are not always interested in the same aspect of a book, especially when they need it for a special purpose. Currently, obtaining non-content book information from reviews is difficult, therefore it would be reasonable to rethink their presentation and organization. In our study, we used an interview and a task solving method to determine whether social tagging could be an appropriate aid for this purpose. The results show that free tagging offers insight into users’ vocabulary but is not optimal for online review presentation. Nevertheless, it represents a good basis for creation of categories that describe books on different levels of Abstraction and could be used as a filtering tool, which would select only those reviews containing the aspects of a book a buyer is interested in.

Virtual Assistants: A Study on the Usability and User Perception of Customer Service Systems for E-Commerce (long)
Valerie Claessen, Adrian Schmidt and Tamara Heck

Abstract: Virtual assistants are able to support users in finding the right information. These programs use natural language processing, learning techniques and social abilities to offer adequate usability experiences for users. In e-commerce, virtual assistants are applied support users in finding appropriate service information or products. This work evaluates the information service quality of three virtual assistants on e-commerce websites. The analyzed aspects cover service quality as well as user perception of virtual assistant systems. First results show that the technology used in the construction of the virtual assistant has a substantial influence on user experience, by the users’ perceived interaction with the assistant becoming more intuitive and therefore more enjoyable. Overall, all assistants were met with a general sense of enthusiasm. However, scores on the usefulness of the services show that they need to be improved regarding several relevant features.

Gamification Elements and Their Perception by Different Gamer Types: A Case Study for a Project Management Software (long)
Alexander von Janta Lipinski, Henrik Weber, Ralph Koelle and Thomas Mandl

Abstract: Gamification is more and more used in information systems. Similar strategies for the gamification of tasks are applied by many developers. A benchmark conducted in 22 mobile apps containing gamification elements showed reward points as one the major design elements applied in this context. We analyzed the user perception of three gamification elements including reward points in the context of project management by conducting a user experiment. Whereas reward points are evaluated as very motivating, a leader board is seen much more critical. It could be shown that the judgment of elements depends on the game personality type. The gamer type Killer had a medium and significant correlation with a positive evaluation of the gaming elements. Only the gamer type Achiever had a positive, significant correlation with a positive judgment of rewards points.

Tuesday, March 14, 16:30-18:30 - Information System Evaluation

Comparing Heuristic Walkthrough and User Studies in Evaluating Digital Appliances (long)
Meier Eva-Maria, Patricia Böhm and Christian Wolff

Abstract: In this paper we present an empirical study comparing user studies and expert evaluations based on a specific set of heuristics for evaluating information appliances with a heuristic walkthrough. The study looks at an e-book reader as well as a digital music player. In the user study, question-answer protocols are used as means of intervention during the experiments. The detailed analysis of problem sets found by the two different methods. Results for the thoroughness, validity and effective-ness are presented and compared with prior studies.

Development of a Benchmark System for Collaborative Online Knowledge Management Systems - Benchmark System and Visualisation for Analysing Personal Knowledge Behaviour (short)
Wolfgang Semar, Elena Mastrandrea and Fabian Odoni

Abstract: Network knowledge management in companies do not work without proactive motivation of their users. Users need to know what their benefits are when sharing knowledge and contributing actively in social network enterprise tools. This paper describes the development of the different benchmark means of quantifying work together in measuring and assessing users’ performance and thus stimulating their willingness to cooperate in their collaborative work as well as shows some examples of how the benchmarks can be visualised.

Multilinguality of Metadata - Measuring the Multilingual Degree of Europeana’s Metadata (long)
Juliane Stiller and Péter Király

Abstract: Offering multilingual access to digital cultural heritage collections is challenging and affects every component in an information system ranging from the user interface and the presented data to the retrieval system. For retrieving, browsing and presenting data in different languages, it is crucial that the underlying metadata offers the same information in different languages. This paper presents the concept and implementation of a score for measuring the multilingual degree of metadata in the digital cultural heritage portal Europeana. For every field in each record across the entire collection, the level of multilinguality can be assessed. This has tremendous benefits for increasing metadata quality and improving multilingual information access.

Text Mining for User Queries Analysis. A 5-step Methodology for Cultural Heritage Institutions (long)
Anne Chardonnens and Simon Hengchen

Abstract: The recent development of web analytics offers new perspectives to libraries, archives and museums to improve their knowledge of user needs and behaviours. In order to dive into the mind of their end users, institutions can explore queries from a digital catalog. However, a manual exploration demands a major time commitment and only leads to limited results. This paper explores how text mining techniques can help automate the analysis of large volumes of log files. A 5-step methodology including clustering is illustrated by a case study from the State Archives of Belgium.

Wednesday, March 15, 9:00-10:30 - Metrics & Altmetrics

A bibliometric framework to identify and delineate subfields of research on tribological wear - Part one: fundamental issues in clusters of similar journals (long)
Edgar Schiebel, Davide Bianchi and András Vernes

Abstract: This contribution presents a clustering and mapping of bibliographically coupled journals as the first part of a bibliometric framework to delineate subfields of tribological wear. The main objective was to identify new theory based approaches and fundamentals on research about wear. The framework uses indicators from information about journals and conferences, disciplines, authors’ keywords and research fronts extracted from publications. We collected slightly more than 5000 publications of relevant literature for the year 2015. In this contribution we report on structuring of journals and conference proceedings. The cluster analysis and a spring based on dimensional mapping of bibliographically coupled journals delivered some sharp delineated subfields like materials, mechanical engineering, dentistry, arthroplasty and machining. Clusters of journals on tribological wear delivered applied research as well as some more fundamental issues.

Are Altmetrics effective in Transdisciplinary Research Fields? : Altmetrical Coverage of Outputs in Educational Research (long)
Elisabeth Vogler, Christoph Schindler, Alexander Botte and Marc Rittberger

Abstract: This paper analyzes the accuracy of Altmetrics for heterogeneous scientific and extra-scientific outputs in a transdisciplinary research field. The transdisciplinary field of educational research is used as a case study to get first insight how current altmetric tools cover the field on the levels of its general publication output, and on the level of research relevant journals. Additionally, two experimental approaches analyze the Twitter mentions of a transdisciplinary research report and Twitter resonance during conferences.

Wednesday, March 15, 11:00-12:30 - (Social) Media Analysis

news-please: A Generic News Crawler and Extractor (short)
Felix Hamborg, Norman Meuschke, Corinna Breitinger and Bela Gipp

Abstract: The amount of news published and read online has increased tremendously in recent years, making news data an interesting resource for many research disciplines, such as the social sciences and linguistics. However, large scale collection of news data is cumbersome due to a lack of generic tools for crawling and extracting such data. We present news-please, a generic, multi-language, open-source crawler and extractor for news that works out-of-the-box for a large variety of news web-sites. Our system allows to crawl arbitrary news websites and to extract the major elements of news articles on those websites, i.e., title, lead paragraph, main content, publication date, author, and main image. In contrast to existing tools, news-please also features full website extraction requiring only the root URL.

Identification and Analysis of Media Bias in News Articles (long)
Felix Hamborg, Norman Meuschke, Akiko Aizawa and Bela Gipp

Abstract: Depending on the news source, a reader can be exposed to a different narrative and conflicting perceptions for the same event. Today, news aggregators help users cope with the large volume of news published daily. However, aggregators focus on presenting shared information, but do not expose the different perspectives from articles on same topics. Thus, users of such aggregators suffer from media bias, which is often implemented intentionally to influence public opinion. In this paper, we present NewsBird, an aggregator that presents shared and different information on topics. Currently, NewsBird reveals different perspectives on international news. Our system has led to insights about media bias and news analysis, which we use to propose approaches to be investigated in future research. Our vision is to provide a system that reveals media bias, and thus ultimately allows users to make their own judgement on the potential bias inherent in news.

Using Sessions from Clickstream Data Analysis to Uncover Different Types of Twitter Behaviour (long)
Florian Meier, Johannes Aigner and David Elsweiler

Abstract: While much is known about how Twitter is used for specific tasks or by particular groups of users, we understand surprisingly little about how the service is used generally on a daily basis. To learn more about general Twitter behaviour we perform a cluster analysis on a rich set of longitudinal interaction log data describing interactions 44 users had with the Twitter website over a 5 month period. We report on and interpret 5 clusters representing common usage patterns with the service.

ISI2017 is organized by: Berlin School of Library and Information Science,
Humboldt-Universität zu Berlin
In Cooperation with: HI - University Association of Information Science DIPF - Bildungsforschung und Bildungsinformation

Last modified: January 18th, 2017