Reviewerly/exHarmony huggingface dataset:
Detection and analysis of graduate students’ academic emotions in the online academic forum based on text mining with a deep learning approach

The possibility of mental illness caused by the academic emotions and academic pressure of graduate students has received widespread attention. Discovering hidden academic emotions by mining graduate students' speeches in social networks has strong practical significance for the mental state discovery of graduate students.Through data collected from online academic forum, a text based BiGRU-Attention model was conducted to achieve academic emotion recognition and classification, and a keyword statistics and topic analysis was performed for topic discussion among graduate posts.Female graduate students post more than male students, and graduates majoring in chemistry post the most. Using the BiGRU-Attention model to identify and classify academic emotions has a performance with precision, recall and F1 score of more than 95%, the category of PA (Positive Activating) has the best classification performance. Through the analysis of post topics and keywords, the academic emotions of graduates mainly come from academic pressure, interpersonal relationships and career related.A BiGRU-Attention model based on deep learning method is proposed to combine classical academic emotion classification and categories to achieve a text academic emotion recognition method based on user generated content.
AVOCUS: A Voice Customization System for Online Personas

Many digital applications offer avatar customization options, positively affecting user experience. However, the adoption of auditory aspects in avatar customization has often been neglected and may have been understudied for its potential. Inspired by prior research that uncovers end-user's demands for voice customization, we seek to apply the identified implications into practice and discover end-user's voice preferences and behavior towards voice customization systems. To this end, we designed and deployed AVOCUS, a web application that enables users to search for specific voices or manipulate voice-related parameters to generate a voice similar to a target voice. Our findings suggest that (1) searching for specific voice using hashtags were perceived to be easy, (2) customized voices generated from voice reflection and voice parameter control functions had high satisfaction, and (3) participants tend to reflect the features of their desired voices when customizing their own voice.
Disability Activism on Social Media: Sociotechnical Challenges in the Pursuit of Visibility

Activism efforts have played a central role in advancing the rights of disabled people in the United States. Social media offers new opportunities for people with disabilities to engage in activism while bypassing the accessibility issues involved in traditional activism. At the same time, disabled people face various forms of social and technical exclusion that may also complicate their use of social media for disability activism. To understand how disabled activists advocate for social change online, we interviewed 20 disabled content creators about their goals, strategies, and challenges around posting activism content on social media. We find that visibility is essential for successful online activism, but that the pursuit of visibility requires disabled content creators to navigate additional challenges including social stigma, algorithmic suppression, accessibility issues, and a heightened risk of harassment. We identify three main types of disability-related harassment faced by disabled activists, along with six ways in which they respond to such harassment. We examine the sociotechnical nature of the strategies disabled activists use to gain visibility, and identify key trade-offs involved in mitigating harassment while engaging in activism on social media.
Modality and intensionality without possible worlds

Abstract This chapter argues that types of situations are better placed to deal with modality and intensionality than possible worlds. In standard formal semantics propositions are regarded as sets of possible worlds. Propositions are modelled as types rather than sets of possible worlds. One important difference is that sets of possible worlds are extensional sets whereas our types are intensional. Thus it is possible to have two distinct types which have exactly the same witnesses. Notions of conversational background and ideals in modality can be seen as resources based on types and topoi as introduced in the TTR literature. Attitudes like ‘believe’ can be seen as a relation between individuals and types. For an individual to believe a type it has to be the case that the type matches the type which models the beliefs (or long-term memory) of the individual.
A Blockchain-Based System for Aid Delivery

Climate-related catastrophes leave people in dire need of aid. A major obstacle in providing help to people is the lack of trust in the aid process. Charity organizations want to ensure that funds and materials reach the intended destinations. Blockchain technology injects trust into business transactions through impeccable record keeping and can alleviate the trust problems in aid delivery. Another major problem in disaster recovery is broken infrastructure (e.g., broken bridges and unavailable roads). Unmanned aerial vehicles (UAV), generally referred to as drones, can address this access problem. In this paper, the authors design a system that uses drone technology for delivery of aid and blockchain technology for the assurance of such delivery. This system records and shares data on the interaction of various participants involved in a disaster aid delivery scenario. The simulation studies validate the applicability of this proposed system showing high throughput and satisfactory performance are attainable with integration of blockchain in large-scale aid delivery.
Speech-Augmented Cone-of-Vision for Exploratory Data Analysis

Mutual awareness of visual attention is crucial for successful collaboration. Previous research has explored various ways to represent visual attention, such as field-of-view visualizations and cursor visualizations based on eye-tracking, but these methods have limitations. Verbal communication is often utilized as a complementary strategy to overcome such disadvantages. This paper proposes a novel method that combines verbal communication with the Cone of Vision to improve gaze inference and mutual awareness in VR. We conducted a within-group study with pairs of participants who performed a collaborative analysis of data visualizations in VR. We found that our proposed method provides a better approximation of eye gaze than the approximation provided by head direction. Furthermore, we release the first collaborative head, eyes, and verbal behaviour dataset. The results of this study provide a foundation for investigating the potential of verbal communication as a tool for enhancing visual cues for joint attention.
Surch: Enabling Structural Search and Comparison for Surgical Videos

Video is an effective medium for learning procedural knowledge, such as surgical techniques. However, learning procedural knowledge through videos remains difficult due to limited access to procedural structures of knowledge (e.g., compositions and ordering of steps) in a large-scale video dataset. We present Surch, a system that enables structural search and comparison of surgical procedures. Surch supports video search based on procedural graphs generated by our clustering workflow capturing latent patterns within surgical procedures. We used vectorization and weighting schemes that characterize the features of procedures, such as recursive structures and unique paths. Surch enhances cross-video comparison by providing video navigation synchronized by surgical steps. Evaluation of the workflow demonstrates the effectiveness and interpretability (Silhouette score = 0.82) of our clustering for surgical learning. A user study with 11 residents shows that our system significantly improves the learning experience and task efficiency of video search and comparison, especially benefiting junior residents.
Improving Automatic Summarization for Browsing Longform Spoken Dialog

Longform spoken dialog delivers rich streams of informative content through podcasts, interviews, debates, and meetings. While production of this medium has grown tremendously, spoken dialog remains challenging to consume as listening is slower than reading and difficult to skim or navigate relative to text. Recent systems leveraging automatic speech recognition (ASR) and automatic summarization allow users to better browse speech data and forage for information of interest. However, these systems intake disfluent speech which causes automatic summarization to yield readability, adequacy, and accuracy problems. To improve navigability and browsability of speech, we present three training agnostic post-processing techniques that address dialog concerns of readability, coherence, and adequacy. We integrate these improvements with user interfaces which communicate estimated summary metrics to aid user browsing heuristics. Quantitative evaluation metrics show a 19% improvement in summary quality. We discuss how summarization technologies can help people browse longform audio in trustworthy and readable ways.
Learning to Navigate Health Taboos through Online Safe Spaces

Social and cultural taboos frequently prevent meaningful conversation around gendered health and wellbeing, across the globe and to varying degrees. Safe spaces can offer potential avenues to nurture non-judgmental environments for dialogue and opportunities for learning to talk through taboos. To this end, we curated an online safe space on WhatsApp—with 35 participants of Indian origin—to facilitate conversations around diverse topics related to gendered health and wellbeing. We observed participant activity for two weeks, before conducting in-depth interviews with 10 participants to better understand their experiences of engaging within the WhatsApp group. We use the lens of Legitimate Peripheral Participation to examine how peripheral and core members of the community drew on new audiences and support systems as they questioned existing structures upholding taboos. We discuss scaffolding mechanisms that could enhance learning about taboo topics in online safe spaces, and the tensions of anonymity in such learning spaces.
The Impacts of Government Expenditure on Poverty Alleviation in Arab Spring Countries

Examining in this study the effects of macroeconomic factors, particularly health and education, on poverty in particular Arab Spring nations over a 15-year from (2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014).Finding out how these factors affect poverty is the goal.Panel data analysis is used to gather annual data from 2000 to 2014 for the chosen Arab nations.According to the analysis, in the sample nations, government spending on health (GEH)has a positive relationship and government expenditure on education (GEE) has negative relationships with poverty during the same time period.The findings reveal that between 2000 and 2014, government spending on health had a favorable impact on poverty in the Arab Spring countries, according to the fixed-effects model, as shown by the Hausman test at a 5% level of confidence.Government spending on education, on the other hand, has had a negative, although insignificant, impact on poverty.
Living Bits and Radical Aminos: A Workshop on Bio-Digital Interfaces for Human-Computer Interaction

As knowledge around bio-digital interaction continues to unfold, there are new opportunities for HCI researchers to integrate biology as a design and computational material. Our motivation for the workshop is to bring together interdisciplinary researchers with interest in exploring the next generation of biological HCI and exploring novel bio-digital interfaces implicating diverse contexts, scales, and stakeholders. The workshop aims to provide a space for interactive discussions, presentations, and brainstorming regarding opportunities and approaches for HCI around bio-digital interfaces. We invite researchers from both academia and industry to submit a short position paper in the following areas: Synthetic Biology, Biological Circuits, Do-It-Yourself Biology (DIYBio), Biomimetic Interfaces, Living Interfaces, Living Artefacts, and Bio-ethics. We will evaluate submissions on fit, ability to stimulate discussion, and contribution to HCI. On our website we have included examples of past work in this area to help inspire and inform position papers. Our website will host a recording of the entire workshop session with accepted papers to support asynchronous viewing for participants who are unable to attend in-person or synchronously.
Supporting User Protection Requirements in Cloud-Based Data Outsourcing

Abstract The cloud is nowadays widely used for storing and managing data, and leveraging scalable and flexible IT infrastructures while guaranteeing continuous data and application availability from anywhere at any time. The cloud market is characterized by a rich and diversified offering that usually comes as predefined configurations (plans), which can be adopted to outsource data collections. Such plans exhibit different features and characteristics, which make different plans suitable to different scenarios. Seemingly a trivial problem, selecting a plan that responds well to the needs of a data owner is actually far from easy. In fact, the problem entails a number of challenges that need to be carefully addressed, ranging from representing and reasoning on plans’ characteristics, to permitting data owners to formulate (and have enforced) expressive requirements to identify an optimal (combination of) plan(s) without requiring deep technical knowledge of the cloud technology and jargon. In this paper, we address this problem, discussing some of its main challenges, and illustrating some research directions and state-of-the-art solutions.
The tactile dimension: a method for physicalizing touch behaviors

Traces of touch provide valuable insight into how we interact with the physical world. Measuring touch behavior, however, is expensive and imprecise. Utilizing a fluorescent UV tracer powder, we developed a low-cost analog method to capture persistent, high-contrast touch records on arbitrary objects. We describe our process for selecting a tracer, methods for capturing, enhancing, and aggregating traces, and approaches to examining qualitative aspects of the user experience. Three user studies demonstrate key features of this method. First, we show that it provides clear and durable traces on objects representative of scientific visualization, physicalization, and product design. Second, we demonstrate how this method could be used to study touch perception, by measuring how task and narrative framing elicit different touch behaviors on the same object. Third, we demonstrate how this method can be used to evaluate data physicalizations by observing how participants touch two different physicalizations of COVID-19 time-series data.
TexonMask: Facial Expression Recognition Using Textile Electrodes on Commodity Facemasks

This paper presents TexonMask, a facial expression recognition system using lightweight electrode-augmented commodity facemasks. With a matrix of textile electrodes carefully deployed on a commodity mask, our edge computing system recognizes the wearer's facial expressions with machine learning based on the capacitive sensor readings, provides a wearable affective display and communicates with external devices using low bandwidth. Results from user studies show that the system is effective and efficient at recognizing five or ten facial expressions with an accuracy of around , using a personalized classifier trained with only six data points per expression. The system's performance is stable across the use sessions and further improves when more data points are collected. We further developed two LiveEmoji applications for facilitating online and face-to-face communication of facemask wearers, demonstrated them in user interviews, and obtained positive participant feedback. Based on the results and findings of the study, we discuss implications and future research directions for facilitating emotional communication between facemask wearers and others.
Integrative Objects in Sociotechnical Contexts: Constructing Digital Well-Being with Generic Epistemology

This paper presents a generative approach to interdisciplinary collaboration based on generic epistemology. Informed by the work of philosopher Anne-Françoise Schmid, we introduce the concept of the integrative object as a means to reorient interdisciplinary collaboration toward the requirements of the object of research itself, rather than via the requirements of particular disciplinary languages, methods, or operative logics. We show how such an approach is useful for research into sociotechnical phenomena that exceed the boundaries of discrete disciplines and their convergence. We introduce digital well-being as a case study, drawing on the authors' own interdisciplinary collaborative experiences in this area as its empirical matter. From this, and in order to aid future research into similarly complex sociotechnical objects, we then provide practical tools to help those in the HCI community prepare and conduct interdisciplinary research in a similarly generative, non-dogmatic, and non-hierarchical manner.
Communicating Consequences: Visual Narratives, Abstraction, and Polysemy in Rural Bangladesh

Information communication and visualization practices reflect two centuries of developments of conventions and best practices which may not be reflective of global audiences' methods for conveying information. Contrasting between rural traditional visual culture and contemporary HCI and data-visualization, we argue that an understanding of traditional practices for information visualization is required for building rich data-narratives and making data-driven systems more accessible and culturally situated. Our ten-month ethnographic study investigates how rural Bangladeshi communities construct narratives through visual media. 1 Our observation, interviews, and FGDs (n=54) expose how participants convey risk management, decision-making, and monetary management practices to their peers. We find that villagers used a rich network of polysemic symbols and abstractions to manifest subjectivity, factuality, consequence, situatedness, and uncertainty; varied visual attributes for constructing narratives; and emphasized material relations among components in visuals. These findings inform the design of future systems for decision support in a culturally situated manner.
Models of Applied Privacy (MAP): A Persona Based Approach to Threat Modeling

The paradigm of Privacy by Design aims to integrate privacy early in the product development life cycle. One element of this is to conduct threat modeling with developers to identify privacy threats that engender from the architecture design of the product. In this paper, we propose a systematic lightweight privacy threat modeling framework (MAP) based on attacker personas that is both easy to operationalize and scale. MAP leverages existing privacy threat frameworks to provide an operational roadmap based on relevant threat actors, associated threats, and resulting harm to individuals as well as organizations. We implement MAP as a persona picker tool that threat modelers can use as a menu select to identify, investigate, and remediate relevant threats based on product developer's scope of privacy risk. We conclude by testing the framework using a repository of 207 privacy breaches extracted from the VERIS Community Database.
Augmented Reality in Service of Human Operations on the Moon: Insights from a Virtual Testbed

Future astronauts living and working on the Moon will face extreme environmental conditions impeding their operational safety and performance. While it has been suggested that Augmented Reality (AR) Head-Up Displays (HUDs) could potentially help mitigate some of these adversities, the applicability of AR in the unique lunar context remains underexplored. To address this limitation, we have produced an accurate representation of the lunar setting in virtual reality (VR) which then formed our testbed for the exploration of prospective operational scenarios with aerospace experts. Herein we present findings based on qualitative reflections made by the first 6 study participants. AR was found instrumental in several use cases, including the support of navigation and risk awareness. Major design challenges were likewise identified, including the importance of redundancy and contextual appropriateness. Drawing on these findings, we conclude by outlining directions for future research aimed at developing AR-based assistive solutions tailored to the lunar setting.
Diverse Migration Journeys and Security Practices: Engaging with Longitudinal Perspectives of Migration and (Digital) Security

There has been a growing body of work on migration within the HCI community, as well as within the social science and public policy communities. More specifically, human-centered security researchers have been exploring the needs and concerns of migrants, starting to contend with the harms created by digital technologies and experienced by those who are and have been marginalized. Case studies through which migration and (digital) security within the HCI domain intersect have been localized to specific contexts such as, e.g., particular issues related to data processing and sharing in refugee camps, or a narrow set of security threats and harms experienced by migrant workers in their new places of work. However, more holistic approaches to understanding the intersections of migration and (digital) security are yet to be fully explored while accounting for the past (including home country security practices, use of localized digital technologies, and interactions with technologies throughout the migration journey), the present (current security practices and experiences in the place or country migrants are situated), and the future migrants are trying to secure for themselves and their families. This workshop aims to build a community of HCI researchers interested in how migration and (digital) security intersect to braid together research narratives, perspectives, and methods, design for inclusive technologies, and build an agenda for future research and practice.
Community Voice as Data: Affordances of Participatory Videos for International Program Development

International program development is a complex process involving many stakeholders. Current international practice affords limited, if any, opportunities for direct community-led input into the program commissioning process, resulting in programs that may not meet the specific needs of communities on the ground. Community voice is one source of data that could help focus the design of effective development programs and interventions. However, development programs are primarily formulated based on representative and often quantitative data conducted by experts from outside the community. Through a participatory video production process with disadvantaged women farmers in rural Bangladesh, we explore the opportunities for including meaningful community voices in these institutionalized processes. We present practical design implications for how community-generated voices can act as rich data, establishing confidence, community bonds and senses of accountability to inform early stages of project development, and to specifically augment and contextualize other data sources.