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  • Creating Personas with Disabilities
    arXiv.cs.HC Pub Date : 2020-03-26
    Trenton Schulz; Kristin Skeide Fuglerud

    Personas can help raise awareness among stakeholders about users' needs. While personas are made-up people, they are based on facts gathered from user research. Personas can also be used to raise awareness of universal design and accessibility needs of people with disabilities. We review the current state of the art of the personas and review some research and industry projects that use them. We outline

    更新日期:2020-03-28
  • Pedestrian Models for Autonomous Driving Part II: high level models of human behaviour
    arXiv.cs.HC Pub Date : 2020-03-26
    Fanta Camara; Nicola Bellotto; Serhan Cosar; Florian Weber; Dimitris Nathanael; Matthias Althoff; Jingyuan Wu; Johannes Ruenz; André Dietrich; Gustav Markkula; Anna Schieben; Fabio Tango; Natasha Merat; Charles W. Fox

    Autonomous vehicles (AVs) must share space with human pedestrians, both in on-road cases such as cars at pedestrian crossings and off-road cases such as delivery vehicles navigating through crowds on high-streets. Unlike static and kinematic obstacles, pedestrians are active agents with complex, interactive motions. Planning AV actions in the presence of pedestrians thus requires modelling of their

    更新日期:2020-03-28
  • Incorporating User's Preference into Attributed Graph Clustering
    arXiv.cs.HC Pub Date : 2020-03-24
    Wei Ye; Dominik Mautz; Christian Boehm; Ambuj Singh; Claudia Plant

    Graph clustering has been studied extensively on both plain graphs and attributed graphs. However, all these methods need to partition the whole graph to find cluster structures. Sometimes, based on domain knowledge, people may have information about a specific target region in the graph and only want to find a single cluster concentrated on this local region. Such a task is called local clustering

    更新日期:2020-03-27
  • Artificial Intelligence for EU Decision-Making. Effects on Citizens Perceptions of Input, Throughput and Output Legitimacy
    arXiv.cs.HC Pub Date : 2020-03-25
    Christopher Starke; Marco Luenich

    A lack of political legitimacy undermines the ability of the European Union to resolve major crises and threatens the stability of the system as a whole. By integrating digital data into political processes, the EU seeks to base decision-making increasingly on sound empirical evidence. In particular, artificial intelligence systems have the potential to increase political legitimacy by identifying

    更新日期:2020-03-26
  • Privacy at Home: an Inquiry into Sensors and Robots for the Stay at Home Elderly
    arXiv.cs.HC Pub Date : 2020-03-25
    Trenton Schulz; Jo Herstad; Harald Holone

    The elderly in the future will use smart house technology, sensors, and robots to stay at home longer. Privacy at home for these elderly is important. In this exploratory paper, we examine different understandings of privacy and use Palen and Dourish's framework to look at the negotiation of privacy along boundaries between a human at home, the robot, and its sensors. We select three dilemmas: turning

    更新日期:2020-03-26
  • Differences of Human Perceptions of a Robot Moving using Linear or Slow in, Slow out Velocity Profiles When Performing a Cleaning Task
    arXiv.cs.HC Pub Date : 2020-03-25
    Trenton Schulz; Patrick Holthaus; Farshid Amirabdollahian; Kheng Lee Koay; Jim Torresen; Jo Herstad

    We investigated how a robot moving with different velocity profiles affects a person's perception of it when working together on a task. The two profiles are the common linear profile and a profile based on the animation principles of slow in, slow out. The investigation was accomplished by running an experiment in a home context where people and the robot cooperated on a clean-up task. We used the

    更新日期:2020-03-26
  • Emotion Recognition From Gait Analyses: Current Research and Future Directions
    arXiv.cs.HC Pub Date : 2020-03-13
    Shihao Xu; Jing Fang; Xiping Hu; Edith Ngai; Yi Guo; Victor C. M. Leung; Jun Cheng; Bin Hu

    Human gait refers to a daily motion that represents not only mobility, but it can also be used to identify the walker by either human observers or computers. Recent studies reveal that gait even conveys information about the walker's emotion. Individuals in different emotion states may show different gait patterns. The mapping between various emotions and gait patterns provides a new source for automated

    更新日期:2020-03-26
  • Hazard recognition in an immersive virtual environment: Framework for the simultaneous analysis of visual search and EEG patterns
    arXiv.cs.HC Pub Date : 2020-03-14
    Mojtaba Noghabaei; Kevin Han

    Unmanaged hazards in dangerous construction environments proved to be one of the main sources of injuries and accidents. Hazard recognition is crucial to achieve effective safety management and reduce injuries and fatalities in hazardous job sites. Still, there has been lack of effort that can efficiently assist workers in improving their hazard recognition skills. This study presents virtual safety

    更新日期:2020-03-24
  • Reward-Mediated Individual and Altruistic Behavior
    arXiv.cs.HC Pub Date : 2020-03-21
    Samuel Gomes; Tomás Alves; João Dias; Carlos Martinho

    Recent research has taken particular interest in observing the dynamics between altruistic and individual behavior. This is a commonly approached problem when reasoning about social dilemmas, which have a plethora of real world counterparts in the fields of education, health and economics. Weighing how incentives influence in-game behavior, our study examines individual and altruistic interactions

    更新日期:2020-03-24
  • Identifying At-Risk K-12 Students in Multimodal Online Environments: A Machine Learning Approach
    arXiv.cs.HC Pub Date : 2020-03-21
    Hang Li; Wenbiao Ding; Songfan Yang; Zitao Liu

    With the rapid emergence of K-12 online learning platforms, a new era of education has been opened up. By offering more affordable and personalized courses compared to in-person classrooms, K-12 online tutoring is pushing the boundaries of education to the general public. It is crucial to have a dropout warning framework to preemptively identify K-12 students who are at risk of dropping out of the

    更新日期:2020-03-24
  • RF Sensing for Continuous Monitoring of Human Activities for Home Consumer Applications
    arXiv.cs.HC Pub Date : 2020-03-21
    Moeness G. Amin; Arun Ravisankar; Ronny G. Guendel

    Radar for indoor monitoring is an emerging area of research and development, covering and supporting different health and wellbeing applications of smart homes, assisted living, and medical diagnosis. We report on a successful RF sensing system for home monitoring applications. The system recognizes Activities of Daily Living(ADL) and detects unique motion characteristics, using data processing and

    更新日期:2020-03-24
  • Analysis and Prediction of Pedestrian Crosswalk Behavior during Automated Vehicle Interactions
    arXiv.cs.HC Pub Date : 2020-03-22
    Suresh Kumaar Jayaraman; Dawn M. Tilbury; X. Jessie Yang; Anuj K. Pradhan; Lionel P. Robert Jr

    For safe navigation around pedestrians, automated vehicles (AVs) need to plan their motion by accurately predicting pedestrians trajectories over long time horizons. Current approaches to AV motion planning around crosswalks predict only for short time horizons (1-2 s) and are based on data from pedestrian interactions with human-driven vehicles (HDVs). In this paper, we develop a hybrid systems model

    更新日期:2020-03-24
  • Dragoon: Private Decentralized HITs Made Practical
    arXiv.cs.HC Pub Date : 2020-03-23
    Yuan Lu; Qiang Tang; Guiling Wang

    With the rapid popularity of blockchain, decentralized human intelligence tasks (HITs) are proposed to crowdsource human knowledge without relying on vulnerable third-party platforms. However, the inherent limits of blockchain cause decentralized HITs to face a few "new" challenges. For example, the confidentiality of solicited data turns out to be the sine qua non, though it was an arguably dispensable

    更新日期:2020-03-24
  • Efficient Behavior-aware Control of Automated Vehicles at Crosswalks using Minimal Information Pedestrian Prediction Model
    arXiv.cs.HC Pub Date : 2020-03-22
    Suresh Kumaar Jayaraman; Lionel P. Robert Jr.; Xi Jessie Yang; Anuj K. Pradhan; Dawn M. Tilbury

    For automated vehicles (AVs) to reliably navigate through crosswalks, they need to understand pedestrians crossing behaviors. Simple and reliable pedestrian behavior models aid in real-time AV control by allowing the AVs to predict future pedestrian behaviors. In this paper, we present a Behavior aware Model Predictive Controller (B-MPC) for AVs that incorporates long-term predictions of pedestrian

    更新日期:2020-03-24
  • From Bit To Bedside: A Practical Framework For Artificial Intelligence Product Development In Healthcare
    arXiv.cs.HC Pub Date : 2020-03-23
    David Higgins; Vince I. Madai

    Artificial Intelligence (AI) in healthcare holds great potential to expand access to high-quality medical care, whilst reducing overall systemic costs. Despite hitting the headlines regularly and many publications of proofs-of-concept, certified products are failing to breakthrough to the clinic. AI in healthcare is a multi-party process with deep knowledge required in multiple individual domains.

    更新日期:2020-03-24
  • On Interactive Machine Learning and the Potential of Cognitive Feedback
    arXiv.cs.HC Pub Date : 2020-03-23
    Chris J. Michael; Dina Acklin; Jaelle Scheuerman

    In order to increase productivity, capability, and data exploitation, numerous defense applications are experiencing an integration of state-of-the-art machine learning and AI into their architectures. Especially for defense applications, having a human analyst in the loop is of high interest due to quality control, accountability, and complex subject matter expertise not readily automated or replicated

    更新日期:2020-03-24
  • Automatic Detection of Reflective Thinking in Mathematical Problem Solving based on Unconstrained Bodily Exploration
    arXiv.cs.HC Pub Date : 2018-12-18
    Temitayo A. Olugbade; Joseph Newbold; Rose Johnson; Erica Volta; Paolo Alborno; Radoslaw Niewiadomski; Max Dillon; Gualtiero Volpe; Nadia Bianchi-Berthouze

    For technology (like serious games) that aims to deliver interactive learning, it is important to address relevant mental experiences such as reflective thinking during problem solving. To facilitate research in this direction, we present the weDraw-1 Movement Dataset of body movement sensor data and reflective thinking labels for 26 children solving mathematical problems in unconstrained settings

    更新日期:2020-03-24
  • Tell Me About Yourself: Using an AI-Powered Chatbot to Conduct Conversational Surveys with Open-ended Questions
    arXiv.cs.HC Pub Date : 2019-05-25
    Ziang Xiao; Michelle X. Zhou; Q. Vera Liao; Gloria Mark; Changyan Chi; Wenxi Chen; Huahai Yang

    The rise of increasingly more powerful chatbots offers a new way to collect information through conversational surveys, where a chatbot asks open-ended questions, interprets a user's free-text responses, and probes answers whenever needed. To investigate the effectiveness and limitations of such a chatbot in conducting surveys, we conducted a field study involving about 600 participants. In this study

    更新日期:2020-03-24
  • Privacy, Altruism, and Experience: Estimating the Perceived Value of Internet Data for Medical Uses
    arXiv.cs.HC Pub Date : 2019-06-20
    Gilie Gefen; Omer Ben-Porat; Moshe Tennenholtz; Elad Yom-Tov

    People increasingly turn to the Internet when they have a medical condition. The data they create during this process is a valuable source for medical research and for future health services. However, utilizing these data could come at a cost to user privacy. Thus, it is important to balance the perceived value that users assign to these data with the value of the services derived from them. Here we

    更新日期:2020-03-24
  • A Sketch-Based System for Human-Guided Constrained Object Manipulation
    arXiv.cs.HC Pub Date : 2019-11-17
    Sina Masnadi; Joseph J. LaViola Jr.; Xiaofan Zhu; Karthik Desingh; Odest Chadwicke Jenkins

    In this paper, we present an easy to use sketch-based interface to extract geometries and generate affordance files from 3D point clouds for robot-object interaction tasks. Using our system, even novice users can perform robot task planning by employing such sketch tools. Our focus in this paper is employing human-in-the-loop approach to assist in the generation of more accurate affordance templates

    更新日期:2020-03-24
  • BeSense: Leveraging WiFi Channel Data and Computational Intelligence for Behavior Analysis
    arXiv.cs.HC Pub Date : 2019-07-13
    Yu Gu; Xiang Zhang; Zhi Liu; Fuji Ren

    The ever evolving informatics technology has gradually bounded human and computer in a compact way. Understanding user behavior becomes a key enabler in many fields such as sedentary-related healthcare, human-computer interaction (HCI) and affective computing. Traditional sensor-based and vision-based user behavior analysis approaches are obtrusive in general, hindering their usage in realworld. Therefore

    更新日期:2020-03-24
  • How to choose the most appropriate centrality measure?
    arXiv.cs.HC Pub Date : 2020-03-02
    Pavel Chebotarev; Dmitry Gubanov

    We propose a new method to select the most appropriate network centrality measure based on the user's opinion on how such a measure should work on a set of simple graphs. The method consists in: (1) forming a set $\cal F$ of candidate measures; (2) generating a sequence of sufficiently simple graphs that distinguish all measures in $\cal F$ on some pairs of nodes; (3) compiling a survey with questions

    更新日期:2020-03-24
  • Neural Fuzzy Extractors: A Secure Way to Use Artificial Neural Networks for Biometric User Authentication
    arXiv.cs.HC Pub Date : 2020-03-18
    Abhishek Jana; Md Kamruzzaman Sarker; Monireh Ebrahimi; Pascal Hitzler; George T Amariucai

    Powered by new advances in sensor development and artificial intelligence, the decreasing cost of computation, and the pervasiveness of handheld computation devices, biometric user authentication (and identification) is rapidly becoming ubiquitous. Modern approaches to biometric authentication, based on sophisticated machine learning techniques, cannot avoid storing either trained-classifier details

    更新日期:2020-03-20
  • TILES-2018: A longitudinal physiologic and behavioral data set of hospital workers
    arXiv.cs.HC Pub Date : 2020-03-18
    Karel Mundnich; Brandon M. Booth; Michelle L'Hommedieu; Tiantian Feng; Benjamin Girault; Justin L'Hommedieu; Mackenzie Wildman; Sophia Skaaden; Amrutha Nadarajan; Jennifer L. Villatte; Tiago H. Falk; Kristina Lerman; Emilio Ferrara; Shrikanth Narayanan

    We present a novel longitudinal multimodal corpus of physiological and behavioral data collected from direct clinical providers in a hospital workplace. We designed the study to investigate the use of off-the-shelf wearable and environmental sensors to understand individual-specific constructs such as job performance, interpersonal interaction, and well-being of hospital workers over time in their

    更新日期:2020-03-20
  • Gaze-Sensing LEDs for Head Mounted Displays
    arXiv.cs.HC Pub Date : 2020-03-18
    Kaan Akşit; Jan Kautz; David Luebke

    We introduce a new gaze tracker for Head Mounted Displays (HMDs). We modify two off-the-shelf HMDs to be gaze-aware using Light Emitting Diodes (LEDs). Our key contribution is to exploit the sensing capability of LEDs to create low-power gaze tracker for virtual reality (VR) applications. This yields a simple approach using minimal hardware to achieve good accuracy and low latency using light-weight

    更新日期:2020-03-20
  • Conducting Privacy-Sensitive Surveys: A Case Study of Civil Society Organizations
    arXiv.cs.HC Pub Date : 2020-03-19
    Nikita Samarin; Alisa Frik; Sean Brooks; Coye Cheshire; Serge Egelman

    Compared to other organizations, civil society organizations (CSOs) often operate in elevated-risk contexts, and attacks against them carry much greater ramifications, including threats to freedom of expression, liberty, and life. We aim to capture the factors that affect the attitudes and intentions of CSO employees to engage in security and privacy behaviors by using a survey-based study to collect

    更新日期:2020-03-20
  • FineHand: Learning Hand Shapes for American Sign Language Recognition
    arXiv.cs.HC Pub Date : 2020-03-04
    Al Amin Hosain; Panneer Selvam Santhalingam; Parth Pathak; Huzefa Rangwala; Jana Kosecka

    American Sign Language recognition is a difficult gesture recognition problem, characterized by fast, highly articulate gestures. These are comprised of arm movements with different hand shapes, facial expression and head movements. Among these components, hand shape is the vital, often the most discriminative part of a gesture. In this work, we present an approach for effective learning of hand shape

    更新日期:2020-03-20
  • MagicEyes: A Large Scale Eye Gaze Estimation Dataset for Mixed Reality
    arXiv.cs.HC Pub Date : 2020-03-18
    Zhengyang Wu; Srivignesh Rajendran; Tarrence van As; Joelle Zimmermann; Vijay Badrinarayanan; Andrew Rabinovich

    With the emergence of Virtual and Mixed Reality (XR) devices, eye tracking has received significant attention in the computer vision community. Eye gaze estimation is a crucial component in XR -- enabling energy efficient rendering, multi-focal displays, and effective interaction with content. In head-mounted XR devices, the eyes are imaged off-axis to avoid blocking the field of view. This leads to

    更新日期:2020-03-20
  • Digitally Capturing Physical Prototypes During Early-Stage Engineering Design Projects for Initial Analysis of Project Output and Progression
    arXiv.cs.HC Pub Date : 2019-04-26
    Jorgen F. Erichsen; Heikki Sjöman; Martin Steinert; Torgeir Welo

    Aiming to help researchers capture output from the early stages of engineering design projects, this article presents a new research tool for digitally capturing physical prototypes. The motivation for this work is to collect observations that can aid in understanding prototyping in the early stages of engineering design projects, and this article investigates if and how digital capture of physical

    更新日期:2020-03-20
  • Can AI decrypt fashion jargon for you?
    arXiv.cs.HC Pub Date : 2020-03-18
    Yuan Shen; Shanduojiao Jiang; Muhammad Rizky Wellyanto; Ranjitha Kumar

    When people talk about fashion, they care about the underlying meaning of fashion concepts,e.g., style.For example, people ask questions like what features make this dress smart.However, the product descriptions in today fashion websites are full of domain specific and low level words. It is not clear to people how exactly those low level descriptions can contribute to a style or any high level fashion

    更新日期:2020-03-19
  • The Engagement-Diversity Connection: Evidence from a Field Experiment on Spotify
    arXiv.cs.HC Pub Date : 2020-03-17
    David Holtz; Benjamin Carterette; Praveen Chandar; Zahra Nazari; Henriette Cramer; Sinan Aral

    It remains unknown whether personalized recommendations increase or decrease the diversity of content people consume. We present results from a randomized field experiment on Spotify testing the effect of personalized recommendations on consumption diversity. In the experiment, both control and treatment users were given podcast recommendations, with the sole aim of increasing podcast consumption.

    更新日期:2020-03-19
  • MSRBot: Using Bots to Answer Questions from Software Repositories
    arXiv.cs.HC Pub Date : 2019-05-16
    Ahmad Abdellatif; Khaled Badran; Emad Shihab

    Software repositories contain a plethora of useful information that can be used to enhance software projects. Prior work has leveraged repository data to improve many aspects of the software development process, such as, help extract requirement decisions, identify potentially defective code and improve maintenance and evolution. However, in many cases, practitioners are not able to fully benefit from

    更新日期:2020-03-19
  • Harnessing Explanations to Bridge AI and Humans
    arXiv.cs.HC Pub Date : 2020-03-16
    Vivian Lai; Samuel Carton; Chenhao Tan

    Machine learning models are increasingly integrated into societally critical applications such as recidivism prediction and medical diagnosis, thanks to their superior predictive power. In these applications, however, full automation is often not desired due to ethical and legal concerns. The research community has thus ventured into developing interpretable methods that explain machine predictions

    更新日期:2020-03-18
  • AutoCogniSys: IoT Assisted Context-Aware Automatic Cognitive Health Assessment
    arXiv.cs.HC Pub Date : 2020-03-17
    Mohammad Arif Ul Alam; Nirmalya Roy; Sarah Holmes; Aryya Gangopadhyay; Elizabeth Galik

    Cognitive impairment has become epidemic in older adult population. The recent advent of tiny wearable and ambient devices, a.k.a Internet of Things (IoT) provides ample platforms for continuous functional and cognitive health assessment of older adults. In this paper, we design, implement and evaluate AutoCogniSys, a context-aware automated cognitive health assessment system, combining the sensing

    更新日期:2020-03-18
  • A Novel AI-enabled Framework to Diagnose Coronavirus COVID 19 using Smartphone Embedded Sensors: Design Study
    arXiv.cs.HC Pub Date : 2020-03-16
    Halgurd S. Maghdid; Kayhan Zrar Ghafoor; Ali Safaa Sadiq; Kevin Curran; Khaled Rabie

    Coronaviruses are a famous family of viruses that causes illness in human or animals. The new type of corona virus COVID-19 disease was firstly discovered in Wuhan-China. However, recently, the virus has been widely spread in most of the world countries and is reported as a pandemic. Further, nowadays, all the world countries are striving to control the coronavirus disease COVID-19. There are many

    更新日期:2020-03-18
  • FakeYou! -- A Gamified Approach for Building and Evaluating Resilience Against Fake News
    arXiv.cs.HC Pub Date : 2020-03-17
    Lena Clever; Dennis Assenmacher; Kilian Müller; Moritz Vinzent Seiler; Dennis M. Riehle; Mike Preuss; Christian Grimme

    Nowadays fake news are heavily discussed in public and political debates. Even though the phenomenon of intended false information is rather old, misinformation reaches a new level with the rise of the internet and participatory platforms. Due to Facebook and Co., purposeful false information - often called fake news - can be easily spread by everyone. Because of a high data volatility and variety

    更新日期:2020-03-18
  • Is This Really You? An Empirical Study on Risk-Based Authentication Applied in the Wild
    arXiv.cs.HC Pub Date : 2020-03-17
    Stephan Wiefling; Luigi Lo Iacono; Markus Dürmuth

    Risk-based authentication (RBA) is an adaptive security measure to strengthen password-based authentication. RBA monitors additional implicit features during password entry such as device or geolocation information, and requests additional authentication factors if a certain risk level is detected. RBA is recommended by the NIST digital identity guidelines, is used by several large online services

    更新日期:2020-03-18
  • Co-sleep: Designing a workplace-based wellness program for sleep deprivation
    arXiv.cs.HC Pub Date : 2018-09-26
    Bing Zhai; Stuart Nicholson; Kyle Montague; Yu Guan; Patrick Olivier; Jason Ellis

    Sleep deprivation is a public health issue. Awareness of sleep deprivation has not been widely investigated in workplace-based wellness programmes. This study adopted a three-stage design process with nine participants from a local manufacturing company to help raise awareness of sleep deprivation. The common causes of sleep deprivation were identified through the deployment of technology probes and

    更新日期:2020-03-18
  • Socratrees: Exploring the Design of Argument Technology for Layman Users
    arXiv.cs.HC Pub Date : 2018-12-11
    Steven Jeuris

    Terms like 'misinformation', 'fake news', and 'echo chambers' permeate current discussions on the state of the Internet. We believe a lack of technological support to evaluate, contest, and reason about information online---as opposed to merely disseminating it---lies at the root of these problems. Several argument technologies support such functionality, but have seen limited use outside of niche

    更新日期:2020-03-18
  • Sensitivity to Haptic-Audio Envelope Asynchrony
    arXiv.cs.HC Pub Date : 2019-06-27
    Alfonso Balandra; Shoichi Hasegawa

    We want to understand the human capabilities to perceive amplitude similarities between a haptic and an audio signal. So, four psychophysical experiments were performed. Three of them measured the asynchrony JND (Just Noticeable Difference) at the signals' attack, release and decay, while the forth experiment measured the amplitude decrease on the middle of the signal. All the experiments used a combination

    更新日期:2020-03-18
  • NaMemo: Enhancing Lecturers' Interpersonal Competence of Remembering Students' Names
    arXiv.cs.HC Pub Date : 2019-11-21
    Guang Jiang; Mengzhen Shi; Ying Su; Pengcheng An; Yunlong Wang; Brian Y. Lim

    Addressing students by their names helps a teacher to start building rapport with students and thus facilitates their classroom participation. However, this basic yet effective skill has become rather challenging for university lecturers, who have to handle large-sized (sometimes exceeding 100) groups in their daily teaching. To enhance lecturers' competence in delivering interpersonal interaction

    更新日期:2020-03-18
  • CRWIZ: A Framework for Crowdsourcing Real-Time Wizard-of-Oz Dialogues
    arXiv.cs.HC Pub Date : 2020-03-12
    Francisco J. Chiyah Garcia; José Lopes; Xingkun Liu; Helen Hastie

    Large corpora of task-based and open-domain conversational dialogues are hugely valuable in the field of data-driven dialogue systems. Crowdsourcing platforms, such as Amazon Mechanical Turk, have been an effective method for collecting such large amounts of data. However, difficulties arise when task-based dialogues require expert domain knowledge or rapid access to domain-relevant information, such

    更新日期:2020-03-16
  • Developing a Personality Model for Speech-based Conversational Agents Using the Psycholexical Approach
    arXiv.cs.HC Pub Date : 2020-03-13
    Sarah Theres Völkel; Ramona Schödel; Daniel Buschek; Clemens Stachl; Verena Winterhalter; Markus Bühner; Heinrich Hussmann

    We present the first systematic analysis of personality dimensions developed specifically to describe the personality of speech-based conversational agents. Following the psycholexical approach from psychology, we first report on a new multi-method approach to collect potentially descriptive adjectives from 1) a free description task in an online survey (228 unique descriptors), 2) an interaction task

    更新日期:2020-03-16
  • Investigating Error Injection to Enhance the Effectiveness of Mobile Text Entry Studies of Error Behaviour
    arXiv.cs.HC Pub Date : 2020-03-13
    Andreas Komninos; Emma Nicol; Mark Dunlop

    During lab studies of text entry methods it is typical to observer very few errors in participants' typing - users tend to type very carefully in labs. This is a problem when investigating methods to support error awareness or correction as support mechanisms are not tested. We designed a novel evaluation method based around injection of errors into the users' typing stream and report two user studies

    更新日期:2020-03-16
  • Mobile Text Entry Behaviour in Lab and In-the-Wild studies: Is it different?
    arXiv.cs.HC Pub Date : 2020-03-13
    Andreas Komninos; Kyriakos Katsaris; Emma Nicol; Mark Dunlop; John Garofalakis

    Text entry in smartphones remains a critical element of mobile HCI. It has been widely studied in lab settings, using primarily transcription tasks, and to a far lesser extent through in-the-wild (field) experiments. So far it remains unknown how well user behaviour during lab transcription tasks approximates real use. In this paper, we present a study that provides evidence that lab text entry behaviour

    更新日期:2020-03-16
  • Tendrils of Crime: Visualizing the Diffusion of Stolen Bitcoins
    arXiv.cs.HC Pub Date : 2019-01-07
    Mansoor Ahmed-Rengers; Ilia Shumailov; Ross Anderson

    The first six months of 2018 saw cryptocurrency thefts of $761 million, and the technology is also the latest and greatest tool for money laundering. This increase in crime has caused both researchers and law enforcement to look for ways to trace criminal proceeds. Although tracing algorithms have improved recently, they still yield an enormous amount of data of which very few datapoints are relevant

    更新日期:2020-03-16
  • Voter Verification of BMD Ballots Is a Two-Part Question: Can They? Mostly, They Can. Do They? Mostly, They Don't
    arXiv.cs.HC Pub Date : 2020-03-10
    Philip Kortum; Michael D. Byrne; Julie Whitmore

    The question of whether or not voters actually verify ballots produced by ballot marking devices (BMDs) is presently the subject of some controversy. Recent studies (e.g., Bernhard, et al. 2020) suggest the verification rate is low. What is not clear from previous research is whether this is more a result of voters being unable to do so accurately or whether this is because voters simply choose not

    更新日期:2020-03-12
  • Super-reflective Data: Speculative Imaginings of a World Where Data Works for People
    arXiv.cs.HC Pub Date : 2020-03-10
    Max Van Kleek

    It's the year 2020, and every space and place on- and off-line has been augmented with digital things that observe, record, transmit, and compute, for the purposes of recording endless data traces of what is happening in the world. Individually, these things (and the invisible services the power them) have reached considerable sophistication in their ability to analyse and dissect such observations

    更新日期:2020-03-12
  • ConceptScope: Organizing and Visualizing Knowledge in Documents based on Domain Ontology
    arXiv.cs.HC Pub Date : 2020-03-11
    Xiaoyu Zhang; Senthil Chandrasegaran; Kwan-Liu Ma

    Current text visualization techniques typically provide overviews of document content and structure using intrinsic properties such as term frequencies, term co-occurrences, and sentence structures. However, these visualization techniques do not provide conceptual overviews that consider domain-relevant knowledge that is needed when examining documents such as research articles, technical panels, or

    更新日期:2020-03-12
  • A Mobile Robot Hand-Arm Teleoperation System by Vision and IMU
    arXiv.cs.HC Pub Date : 2020-03-11
    Shuang Li; Jiaxi Jiang; Philipp Ruppel; Hongzhuo Liang; Xiaojian Ma; Norman Hendrich; Fuchun Sun; Jianwei Zhang

    In this paper, we present a multimodal mobile teleoperation system that consists of a novel vision-based hand pose regression network (Transteleop) and an IMU-based arm tracking method. Transteleop observes the human hand through a low-cost depth camera and generates not only joint angles but also depth images of paired robot hand poses through an image-to-image translation process. A keypoint-based

    更新日期:2020-03-12
  • Enterprise Social Networks as Digital Infrastructures -- Understanding the Utilitarian Value of Social Media at the Workplace
    arXiv.cs.HC Pub Date : 2020-03-11
    Christian Meske; Konstantin Wilms; Stefan Stieglitz

    In this study, we first show that while both the perceived usefulness and perceived enjoyment of enterprise social networks impact employees' intentions for continuous participation, the utilitarian value significantly outpaces its hedonic value. Second, we prove that the network's utilitarian value is constituted by its digital infrastructure characteristics: versatility, adaptability, interconnectedness

    更新日期:2020-03-12
  • Ethical Guidelines for the Construction of Digital Nudges
    arXiv.cs.HC Pub Date : 2020-03-11
    Christian Meske; Ireti Amojo

    Under certain circumstances, humans tend to behave in irrational ways, leading to situations in which they make undesirable choices. The concept of digital nudging addresses these limitations of bounded rationality by establishing a libertarian paternalist alternative to nudge users in virtual environments towards their own preferential choices. Thereby, choice architectures are designed to address

    更新日期:2020-03-12
  • Explainable Agents Through Social Cues: A Review
    arXiv.cs.HC Pub Date : 2020-03-11
    Sebastian Wallkotter; Silvia Tulli; Ginevra Castellano; Ana Paiva; Mohamed Chetouani

    How to provide explanations has experienced a surge of interest in Human-Robot Interaction (HRI) over the last three years. In HRI this is known as explainability, expressivity, transparency or sometimes legibility, and the challenge for embodied agents is that they offer a unique array of modalities to communicate this information thanks to their embodiment. Responding to this surge of interest, we

    更新日期:2020-03-12
  • Human-in-the-Loop Design Cycles -- A Process Framework that Integrates Design Sprints, Agile Processes, and Machine Learning with Humans
    arXiv.cs.HC Pub Date : 2020-02-29
    Chaehan So

    Demands on more transparency of the backbox nature of machine learning models have led to the recent rise of human-in-the-loop in machine learning, i.e. processes that integrate humans in the training and application of machine learning models. The present work argues that this process requirement does not represent an obstacle but an opportunity to optimize the design process. Hence, this work proposes

    更新日期:2020-03-12
  • Recognizing Affiliation: Using Behavioural Traces to Predict the Quality of Social Interactions in Online Games
    arXiv.cs.HC Pub Date : 2020-03-06
    Julian Frommel; Valentin Sagl; Ansgar E. Depping; Colby Johanson; Matthew K. Miller; Regan L. Mandryk

    Online social interactions in multiplayer games can be supportive and positive or toxic and harmful; however, few methods can easily assess interpersonal interaction quality in games. We use behavioural traces to predict affiliation between dyadic strangers, facilitated through their social interactions in an online gaming setting. We collected audio, video, in-game, and self-report data from 23 dyads

    更新日期:2020-03-10
  • Learn and Transfer Knowledge of Preferred Assistance Strategies in Semi-autonomous Telemanipulation
    arXiv.cs.HC Pub Date : 2020-03-07
    Lingfeng Tao; Michael Bowman; Xu Zhou; Xiaoli Zhang

    Increasing the autonomy level of a robot hand to accomplish remote object manipulation tasks faster and easier is a new and promising topic in teleoperation. Such semi-autonomous telemanipulation, however, is very challenging due to the physical discrepancy between the human hand and the robot hand, along with the fine motion constraints required for the manipulation task. To overcome these challenges

    更新日期:2020-03-10
  • A Human-Centered Review of the Algorithms used within the U.S. Child Welfare System
    arXiv.cs.HC Pub Date : 2020-03-07
    Devansh Saxena; Karla Badillo-Urquiola; Pamela J. Wisniewski; Shion Guha

    The U.S. Child Welfare System (CWS) is charged with improving outcomes for foster youth; yet, they are overburdened and underfunded. To overcome this limitation, several states have turned towards algorithmic decision-making systems to reduce costs and determine better processes for improving CWS outcomes. Using a human-centered algorithmic design approach, we synthesize 50 peer-reviewed publications

    更新日期:2020-03-10
  • Conceptual Model of Visual Analytics for Hands-on Cybersecurity Training
    arXiv.cs.HC Pub Date : 2020-03-07
    Radek Ošlejšek; Vít Rusňák; Karolína Burská; Valdemar Švábenský; Jan Vykopal; Jakub Čegan

    Hands-on training is an effective way to practice theoretical cybersecurity concepts and increase participants' skills. In this paper, we discuss the application of visual analytics principles to the design, execution, and evaluation of training sessions. We propose a conceptual model employing visual analytics that supports the sensemaking activities of users involved in various phases of the training

    更新日期:2020-03-10
  • Generating Emotionally Aligned Responses in Dialogues using Affect Control Theory
    arXiv.cs.HC Pub Date : 2020-03-07
    Nabiha Asghar; Ivan Kobyzev; Jesse Hoey; Pascal Poupart; Muhammad Bilal Sheikh

    State-of-the-art neural dialogue systems excel at syntactic and semantic modelling of language, but often have a hard time establishing emotional alignment with the human interactant during a conversation. In this work, we bring Affect Control Theory (ACT), a socio-mathematical model of emotions for human-human interactions, to the neural dialogue generation setting. ACT makes predictions about how

    更新日期:2020-03-10
  • Transferring Cross-domain Knowledge for Video Sign Language Recognition
    arXiv.cs.HC Pub Date : 2020-03-08
    Dongxu Li; Xin Yu; Chenchen Xu; Lars Petersson; Hongdong Li

    Word-level sign language recognition (WSLR) is a fundamental task in sign language interpretation. It requires models to recognize isolated sign words from videos. However, annotating WSLR data needs expert knowledge, thus limiting WSLR dataset acquisition. On the contrary, there are abundant subtitled sign news videos on the internet. Since these videos have no word-level annotation and exhibit a

    更新日期:2020-03-10
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