EEG classification is a promising approach to facilitate the life of handicapped people and to generate future human-computer-interfaces. In this paper we want to compare the effectiveness of current state of the art deep learning techniques for EEG classification. Therefore, we applied different approaches on various datasets and did a crosscomparison of the results in order to get more knowledge on the generalization capabilities. Additionally, we created a new EEG dataset and made it available for further research.

Human Factors in Hypertext 2022 (HUMAN'22) is the 5th workshop in this series. It is sponsored by ACM SIGWEB and is associated to the ACM Conference on Hypertext and Social Media 2022 (HT'22), which takes place between June 28th and July 1st in Barcelona, Spain as a hybrid event. HUMAN'22 takes place on June 28th—the conference's workshop day.

After two years of pandemic-caused virtual workshops, HUMAN'22 is organized as a hybrid event, which is in line with the organization of the main conference. We see this as a chance to allow in-presence meetings while providing remote participants the opportunity to get in touch by low registration costs and a reduced carbon footprint. Today's digital media enables us to communicate over distance or even attend larger meetings online and the Corona pandemic has taught us to use these tools in our daily life. This puts a special focus on the role of hypertext in our communication and information exchange demands, in particular from a human's perspective.

E-mail is nearly 50 years old and is still one of the most used communication protocols nowadays. However, it has no support for End-to-end encryption (E2EE) by default, which makes it inappropriate for sending sensitive information. This is why two e-mail encryption standards have been developed—namely, Secure/Multipurpose Internet Mail Extensions (S/MIME) and OpenPGP. Previous studies found that bad usability of encryption software can lead to software that is incorrectly used or not at all. Both consequences have a fatal impact on users’ security and privacy. In recent years, the number of e-mails that are read and written on mobile devices has increased drastically. In this paper, we conduct to the best of our knowledge, the first usability study of e-mail encryption apps on smartphones. We tested two mobile apps, one uses OpenPGP on Android and one uses S/MIME on iOS. In our usability study, we tested both apps with eleven participants and evaluated the usability with the System Usability Scale (SUS) and the Short Version of User Experience Questionnaire (UEQ-S). Our study shows that both apps have several usability issues which partly led to unencrypted e-mails and participants sending their passphrase instead of their public key.

Abstract. While modern-day static analysis tools are capable of finding standard vulnerabilities as well as complex patterns, implementing those tools is expensive regarding both development time and runtime performance. During the last years, domain specific languages like Datalog have gained popularity as they simplify the development process of analyses and rule sets dramatically. Similarly, intermediate representations like LLVM-IR are used to facilitate static source code analysis. In this paper, we present VANDALIR, a vulnerability analyzer and detector based on Datalog and LLVM-IR. VANDALIR is a static source code analyzer that allows to define and customize detection rules in a high-level, declarative way. We implement VANDALIR as a comprehensive static analysis tool, aiming to simplify vulnerability detection by a new combination of modern technologies. Besides the novel design of VANDALIR, we present a predefined detection rule set covering stack-based memory corruption, double free and format string vulnerabilities. As we show, our rule set achieves a detection rate of over 90% on test cases from the Juliet Test Suite, outperforming well-established vulnerability scanners such as the Clang Static Analyzer. Furthermore, we evaluated VANDALIR on open source projects and could reproduce existing vulnerabilities as well as identify previously unknown vulnerabilities.

In vielen Branchen gilt immer noch das Paradigma, dass es deutlich kostengünstiger sei, bestehende Kunden zu binden, als neue zu gewinnen. In diesem Kontext kommt einem zielgerichteten, analytischen Churn Management eine besondere Bedeutung zu. KI und Methoden des maschinellen Lernens scheinen dafür wie geschaffen.

Hypertext systems support users in navigating structured data sets and to find relevant information. Various interaction and visualization concepts aim to give users better insight into the data set, by suggesting queries and visualizing elements of interest in a meaningful way. Ranked lists are very common to show some sort of priority, while spatial layouts often help users to trace relations in the data. Only little research has been done in user studies that systematically show and reason about the differences of such spatial layouts and ranked lists. In this paper we report on a systematic comparison of a spatial visualization versus a ranked list layout. For this purpose, we did an between-subject study with 43 participants. One group performed a task with a system providing semantic visualization in 2D, the other group performed the same task with a ranked list. Both interfaces are very similar and only differ in how suggestions are visualized. The results show that users of the spatial layout finished their task in shorter time and have a tendency towards higher satisfaction. At the same time, they had more interactions with the system. Furthermore we discuss some in-depth data of the test sessions, which show that the visualization influences the users’ behavior.

In this paper, we report on a software demonstrator that utilizes a spatial hypertext UI to support knowledge management in the context of maintenance in industry. To demonstrate the flexibility of that approach, we re-use the software to visualize bibliographic data of the Hypertext conference series.

Associating information by means of linking it is a universal concept of human thinking, and by constructivist means, a possible way of learning through exploring and constructing individual information spaces related to a topic or cross topics. An application, facilitating and externalizing this activity by enabling users to create individual hyperlinks inside the environment of the Web, is a promising way to satisfy this exploratory use of information. The focus on an augmentative approach by lining hypertext's linking paradigm, in conjunction with the Web's vast amount of information, opens up for a broad spectrum of potential use scenarios. The possibilities reflect potential complexities concerning usability and limitations of usage. Therefore, preliminary and iterative evaluations are indispensable for meeting these challenges. We discuss a preliminary evaluation of usability and user behavior of said application by a conducted study based on cross-sectional quasi experimental design, using a controlled test scenario and collected client side data that serves as basis for interpretation on user behavior. Results indicate a strong habituation to document-centric processing and storing of information, and the tendency for transferring this behavior onto the more versatile linking mechanism introduced by the application. We argue for applying additional supportive features, specific for facilitating the reduction of complexity on user-side, and a longer testing period, in order to gain better insight into the possible overcome of habitual patterns concerning the tested use scenario.

This blue sky paper envisions a novel system which promotes emotional closeness through storytelling. Family members, who may be separated, collaboratively build a spatial hypertext of images and text fragments to express and structure their thoughts and memories. The system observes their reactions as well as their media while they work. Live recommendations prompt users in their thinking and storytelling. Family stories are thus collaboratively adapted to more tightly connect the thoughts and emotions of their loved ones.

Im Zuge von Algorithmic Governance wird zunehmend auf den Einsatz von Algorithmen und KI für Entscheidungen und deren Ausführung in der praktischen Politik zurückgegriffen. Aber wie lassen sich diese Eingriffe demokratisch legitimieren und unter gesellschaftlichen Aspekten rechtfertigen?

Der Rückgriff auf Algorithmen und datenbasierte Entscheidungsmuster sowie zunehmend auch auf KI im Rahmen der „Algorithmic Governance“ verändert die praktische Politik grundlegend. Dabei unterscheiden sich die Einsatzfelder hinsichtlich ihres Autonomiegrades. Das Spektrum reicht von klassischen Analyseleistungen bis hin zu völlig autonomen politischen Entscheidungen durch KI.

Unter dem Begriff der Algorithmic Governance wird verstärkt der Einsatz von Algorithmen als Ergänzung oder auch als vollständiger Ersatz menschlicher politischer Entscheidungen diskutiert. Kommen dabei Methoden des maschinellen Lernens und KI zum Einsatz verändert dies die Rahmenbedingungen des Regierens in der Demokratie grundlegend.

Die Informationen unserer DNA sind die persönlichsten Daten, die wir kennen. Kaum eine andere Datenkategorie erlaubt ähnlich tiefe Einblicke in die Kundenbedürfnisse. Die individuelle Zuschneidung von Angeboten kann demnach heute auch auf Basis unseres Erbgutes erfolgen, und zwar im Rahmen eines „DNA-Targetings“. Auf der Grundlage einer detaillierten Analyse des Erbgutes – vermarktet als eigenständiges Produkt, mit dem sich etwa ethnische Herkunft oder Krankheitsrisiken bestimmen ­lassen – eröffnen sich zahlreiche Einsatzmöglichkeiten, von der, „streuverlustfreien“ Kommunikation über ein DNA-basiertes Kunden-Clustering bis hin zu personalisierten Ernährungsprodukten und Medikamenten. Im internationalen Kontext spielen diese Anwendungsfälle eine noch ungleich größere Rolle als in Europa, ungeachtet der auch andernorts durchaus erkannten besonderen Datenschutzproblematik. Eine Auseinandersetzung mit der Thematik ist daher auch dringend im akademischen Marketing hierzulande dringend geboten.

Citizen science allows involving interested citizen in the entire research process in science. In the past, various citizen science projects have been performed in different research fields, especially in human medicine. We conducted a rapid scoping review to determine which citizen projects in human medicine already used software-based systems to engage citizens in the research process. Furthermore, we analysed which of the software-systems are publicly available, especially in the field of rare diseases, how citizens can participate using those tools and whether the usability was rated by the participants. To get insights for our project “SelEe (Seltene Erkrankungen bürgerwissenschaftlich erforschen)”, which is a citizen science project in rare diseases funded by the Federal Ministry of Education and Research (BMBF), we aimed to identify projects in this research area. We searched PubMed for articles between 2011 and 2021 and performed a title- and abstract screening, as well as a full-text screening. Finally, 12 studies were identified in different research areas like public health, genetic research and infectious diseases. We could not identify any study directly associated with rare diseases. None of the studies investigated usability of those systems. Furthermore, five publicly available citizen science software-systems were identified. Three of them are general systems that allow creating, operating, managing citizen science projects and including citizens in the research process. In further investigations, we will check and compare these systems, if they are appropriate for use in our SelEe-project.