Affective Adaptation of Social Norms in Workplace Design

Open-plan offices are common in today's organisations. These types of workplaces require people to share a common space, where violation of (implicitly or explicitly stated) social norms can cause instances of incivility. If nothing is done to avoid these situations, bad feeling can lead to diminished productivity and cooperation, and, in the long-term, to more serious problems, such as conflict and aggression. A critical review of literature shows the effects of workplace incivility and the need for an internal reparation mechanism. Inspired by convergence of pervasive, adaptive and affective computing, we have designed and developed a self-regulatory platform for successful collective action, based on participatory adaptation and fair information practises, which we called MACS. MACS addresses the problem of incivility and aims at improving the Quality of Experience in shared workplaces. This thesis presents all studies that led to the development of MACS. Through the analysis of an online questionnaire we gathered information about incivility in shared workplaces, how people deal with those situations, and awareness about uncivil self-behaviours. We concluded the main issue while sharing a workplace is noise, and most people will try to change their own behaviour, rather than confronting the person being uncivil. MACS's avatar-based interface was developed with the purpose of heightening self-awareness and cueing the appropriate social norms, while providing a good User Experience (UX). Avatars created to people's image, rather than photos, were used, to keep MACS's tone light and relatively unintrusive, while still creating self-awareness. MACS's final version went through UX testing, where 6 people were filmed while performing tasks in MACS. The intended work-flow and user interfaces to support the smooth passage of the work-flow have been validated by the UX user testing. There is some preliminary evidence suggesting apology will elicit empathic responses in MACS. Finally, this thesis proposes guidelines for workplace design, which are founded on participatory creation and change of social norms, and ways to make sure they are enforced. In this sense, MACS can also be seen as a prototypical example of a socio-technical system being used as platform for successful collective action.Open Acces

Quality of experience in affective pervasive environments

The confluence of miniaturised powerful devices, widespread communication networks and mass remote storage has caused a fundamental shift in the user interaction design paradigm. The distinction between system and user in pervasive environments is evolving into an increasingly integrated loop of interaction, raising a number of opportunities to provide enhanced and personalised experiences. We propose a platform, based on a smart architecture, to address the identified opportunities in pervasive computing. Smart systems aim at acting upon an environment for improving quality of experience: a subjective measure that has been defined as an emotional reaction to products or services. The inclusion of an emotional dimension allows us to measure individual user responses and deliver personalised services with the potential to influence experiences positively. The platform, Cloud2Bubble, leverages pervasive systems to aggregate user and environment data with the goal of addressing personal preferences and supra-functional requirements. This, combined with its societal implications, results in a set of design principles as a concrete fruition of design contractualism. In particular, this thesis describes: - a review of intelligent ubiquitous environments and relevant technologies, including a definition of user experience as a dynamic affective construct; - a specification of main components for personal data aggregation and service personalisation, without compromising privacy, security or usability; - the implementation of a software platform and a methodological procedure for its instantiation; - an evaluation of the developed platform and its benefits for urban mobility and public transport information systems; - a set of design principles for the design of ubiquitous systems, with an impact on individual experience and collective awareness. Cloud2Bubble contributes towards the development of affective intelligent ubiquitous systems with the potential to enhance user experience in pervasive environments. In addition, the platform aims at minimising the risk of user digital exposure while supporting collective action.Open Acces

Emotional Design: An Overview

Emotional design has been well recognized in the domain of human factors and ergonomics. In this chapter, we reviewed related models and methods of emotional design. We are motivated to encourage emotional designers to take multiple perspectives when examining these models and methods. Then we proposed a systematic process for emotional design, including affective-cognitive needs elicitation, affective-cognitive needs analysis, and affective-cognitive needs fulfillment to support emotional design. Within each step, we provided an updated review of the representative methods to support and offer further guidance on emotional design. We hope researchers and industrial practitioners can take a systematic approach to consider each step in the framework with care. Finally, the speculations on the challenges and future directions can potentially help researchers across different fields to further advance emotional design.http://deepblue.lib.umich.edu/bitstream/2027.42/163319/1/Emotional_Design_Manuscript_Final.pdfSEL

Narrative Elements in Expository Texts: A Corpus Study of Educational Textbooks

While the use of narrative elements in educational texts seems to be an adequate means to enhance students’ engagement and comprehension, we know little about how and to what extent these elements are used in the present-day educational practice. In this quantitative corpus-based analysis, we chart how and when narrative elements are used in current Dutch educational texts (N=999). While educational texts have traditionally been considered prime exemplars of expository texts, we show that the distinction between the expository and narrative genre is not that strict in the educational domain: prototypical narrative elements – particularized events, experiencing characters, and landscapes of consciousness – occur in 45% of the corpus’ texts. Their distribution varies between school subjects: while specific events, specific people, and their experiences are often at the heart of the to-be-learned information in history texts, narrativity is less present in the educational content of biology and geography texts. Instead publishers employ narrative-like strategies to make these texts more concrete and imaginable, such as the addition of fictitious characters and representative entities

KEER2022

Avanttítol: KEER2022. DiversitiesDescripció del recurs: 25 juliol 202

Mind the gap: gap factors in intercultural business communication : a study of German-Indian semi-virtual tech/engineering teams

While the affordances of technology have facilitated virtual modes of global collaboration, cultural variances and a geographically-dispersed environment can also lead to impaired group communication in team interaction. This qualitative study draws on data gathered from four organizations to investigate the miscommunication and cognitive dissonances reported by virtual German-Indian engineering/tech communities of practice. The study argues that it is not so much the performance or doing of a communicative act that creates dissonances, but the gaps, i.e., the absence or not-doing of certain communicative actions expected in a collaborative context. The gap factors are experienced as unfulfilled reciprocal expectations, and are classified and explored against three parameters: 1) the culture of a technological community of practice, 2) the power relations between the interactants, and 3) the consequences of virtual communication. The findings indicate a complementary divergence between the two groups regarding the nature of gaps. While the German teams report gaps in communicative efficiency and content caused e.g., by non-disclosure, euphemistic language and a deficiency in push communication, the Indian teams perceive gaps in relationality and affective signaling. At the same time, they are two sides of the same coin, with the divergences arising from the way in which the intersecting structural parameters are viewed as being salient in interaction. The study concludes with implications and suggestions for organizational practice

Social media analytics with applications in disaster management and COVID-19 events

Social media such as Twitter offers a tremendous amount of data throughout an event or a disastrous situation. Leveraging social media data during a disaster is beneficial for effective and efficient disaster management. Information extraction, trend identification, and determining public reactions might help in the future disaster or even avert such an event. However, during a disaster situation, a robust system is required that can be deployed faster and process relevant information with satisfactory performance in real-time. This work outlines the research contributions toward developing such an effective system for disaster management, where it is paramount to develop automated machine-enabled methods that can provide appropriate tags or labels for further analysis for timely situation-awareness. In that direction, this work proposes machine learning models to identify the people who are seeking assistance using social media during a disaster and further demonstrates a prototype application that can collect and process Twitter data in real-time, identify the stranded people, and create rescue scheduling. In addition, to understand the people’s reactions to different trending topics, this work proposes a unique auxiliary feature-based deep learning model with adversarial sample generation for emotion detection using tweets related to COVID-19. This work also presents a custom Q&A-based RoBERTa model for extracting related phrases for emotions. Finally, with the aim of polarization detection, this research work proposes a deep learning pipeline for political ideology detection leveraging the tweet texts and the expressed emotions in the text. This work also studies and conducts the historical emotion and polarization analysis of the COVID-19 pandemic in the USA and several individual states using tweeter data --Abstract, page iv