End User Development in the IoT: a Semantic Approach

The Internet of Things (IoT) is, nowadays, a well recognized paradigm. In this field, End User Development (EUD) is a promising approach that allows users to program their devices and services. The representation models adopted by contemporary EUD interfaces, however, are often highly technology-dependent, and the interaction between users and the IoT ecosystem is put to a hard test. The goal of my research is to explore new approaches and tools for helping end-users to program their technological devices and services. For this purpose, I proposed EUPont, an ontological model able to represent abstract and technology independent trigger-action rules, that can be adapted to different contextual situations. EUPont has been evaluated in terms of understandability, completeness, and usefulness. Currently, I am using the semantic features of the model in different research projects, e.g., to optimize the layout of EUD interfaces, and to design a recommender system of trigger-action rules. Preliminary results are promising, and confirm the benefit of using the semantic information of EUPont for helping end-users to better deal with the forthcoming IoT world

Towards Understanding the Dark Patterns That Steal Our Attention

Contemporary digital services often adopt mechanisms, e.g., recommendations and infinite scrolling, that exploit users' psychological vulnerabilities to maximize time spent and daily visits. While these attention-capture dark patterns might contribute to technology overuse and problematic behaviors, they are relatively underexplored in the literature. In this paper, we first provide a definition of what are attention-capture dark patterns based on a review of recent works on digital wellbeing and dark patterns. Then, we describe a set 5 of attention-capture dark patterns extracted from a 1-week-long auto-ethnography during which we self-monitored our mobile and web interactions with Facebook and YouTube. Finally, we report on an initial study (N=7) that explores whether and how a widespread mechanism, i.e., social investment, influence usage and users' perception of the Facebook website. We discuss the implications that our work may have on the design of technologies that better align with users' digital wellbeing

End-User Development in the Internet of Things

L'abstract è presente nell'allegato / the abstract is in the attachmen

Nudging Users Towards Conscious Social Media Use

Social networks, especially on mobile interfaces, can potentially undermine users' digital wellbeing promoting passive and excessive use. Previous attempts to support users' self-control either focus on restricting use, e.g., through usage timers and blockers, or removing functionality, e.g., by hiding recommendations. In an attempt to avoid these generic and drastic methods, this paper builds on the idea of using nudging mechanisms to make users recognize those design patterns in a social network app that are deliberately adopted to capture attention, the so-called Attention-Capture Damaging Patterns (ACDPs). Being engineered to make users lose their sense of time and control, we hypothesize that making them visible can trigger conscious decisions and more meaningful usage sessions. Thanks to a co-design study with six mobile users, we designed two nudges for two different ACDPs commonly used on mobile social networks - infinite scroll and pull-to-refresh. Then, we implemented the two nudges in a mobile app, asking 17 users to try them in a 2-week exploratory study. Results show that the implemented nudges made participants feel more in control of their social media use and partially impacted their quantitative smartphone behaviors. Overall, our work points to exploring alternative - less intrusive - nudging methods to support users in self-regulating their smartphone use

Understanding, Discovering, and Mitigating Habitual Smartphone Use in Young Adults

People, especially young adults, often use their smartphones out of habit: They compulsively browse social networks, check emails, and play video-games with little or no awareness at all. While previous studies analyzed this phenomena qualitatively, e.g., by showing that users perceive it as meaningless and addictive, yet our understanding of how to discover smartphone habits and mitigate their disruptive effects is limited. Being able to automatically assess habitual smartphone use, in particular, might have different applications, e.g., to design better “digital wellbeing” solutions for mitigating meaningless habitual use. To close this gap, we first define a data analytic methodology based on clustering and association rules mining to automatically discover complex smartphone habits from mobile usage data. We assess the methodology over more than 130,000 phone usage sessions collected from users aged between 16 and 33, and we show evidence that smartphone habits of young adults can be characterized by various types of links between contextual situations and usage sessions, which are highly diversified and differently perceived across users. We then apply the proposed methodology in Socialize, a digital wellbeing app that (i) monitors habitual smartphone behaviors in real time and (ii) uses proactive notifications and just-in-time reminders to encourage users to avoid any identified smartphone habits they consider as meaningless. An in-the-wild study with 20 users (ages 19–31) demonstrates that Socialize can assist young adults in better controlling their smartphone usage with a significant reduction of their unwanted smartphone habits

Designing Technology That Promotes Users' Digital Wellbeing

Existing tools for digital self-control strongly rely on users' self-regulation strategies and capabilities. Recent work, however, highlights the importance of proactively assisting users in learning how to use technology through customizable and adaptable interventions

Coping with Digital Wellbeing in a Multi-Device World

While Digital Self-Control Tools (DSCTs) mainly target smartphones, more effort should be put into evaluating multi-device ecosystems to enhance digital wellbeing as users typically use multiple devices at a time. In this paper, we first review more than 300 DSCTs by demonstrating that the majority of them implements a single-device conceptualization that poorly adapts to multi-device settings. Then, we report on the results from an interview and a sketching exercise (N=20) exploring how users make sense of their multi-device digital wellbeing. Findings show that digital wellbeing issues extend beyond smartphones, with the most problematic behaviors deriving from the simultaneous usage of different devices to perform uncorrelated tasks. While this suggests the need of DSCTs that can adapt to different and multiple devices, our work also highlights the importance of learning how to properly behave with technology, e.g., through educational courses, which may be more effective than any lock-out mechanism

Towards Multi-Device Digital Self-Control Tools

Users can nowadays take advantage of Digital-Self Control Tools (DSCT) to self-regulate their usage of applications and websites by means of interventions like timers and lockout mechanisms. However, DSCTs mainly focus on the interaction between users and a single device at a time, while people typically use more than one device, and in a concurrent way. This motivates the need of exploring tools that can adapt to multi-device settings. We present FeelHabits, a DSCT that allows users to set up, through a novel approach, multi-device intentions, i.e., contextual time and launch limits for the simultaneous and/or alternating use of the PC and the smartphone. Stemming from the defined intentions, FeelHabits employs different levels of severity to warn the user about a reached limit on the currently used device. A preliminary study on 7 participants suggests that FeelHabits might be effective for reducing some multi-device behaviors, and opens the way for further research

Nudging Users or Redesigning Interfaces? Evaluating Novel Strategies for Digital Wellbeing Through inControl

As web designers may deliberately adopt design patterns to hook users' attention, researchers and practitioners have innovated several tools for supporting users' digital self-control, hoping to help users self-regulate technology use - especially social networks and video streaming platforms - and achieve digital wellbeing. Unfortunately, these tools often restrict usage, e.g., through self-imposed timers and blockers, limiting interaction possibilities. This paper describes the design, development, and evaluation of two alternative strategies for digital self-control targeting the Facebook and YouTube websites. Specifically, we implemented a Chrome extension that a) highlights when the user is scrolling infinitely by progressively darkening the background (nudging strategy), and b) redesigns the homepages isolating guilty pleasure recommendations and proposing a minimalistic interface (redesign strategy). We compared the two strategies in a three-week field study with 14 participants, finding that both strategies promoted intentional use and allowed participants to decrease time spent and passive scrolling. In particular, participants liked the nudging strategy more as it supported conscious use without changing the overall user experience. We conclude with design implications for moving from traditional digital self-control tools to diverse approaches that may better support digital wellbeing in the long term

A Debugging Approach for Trigger-Action Programming

Nowadays, end users can customize their technological devices and web applications by means of trigger-action rules, defined through End-User Development (EUD) tools. However, debugging capabilities are important missing features in these tools that limit their large-scale adoption. Problems in trigger-action rules, in fact, can lead to unpredictable behaviors and security issues, e.g., a door that is unexpectedly unlocked. In this paper, we present a novel debugging approach for trigger-action programming. The goal is to assists end users during the composition of trigger-action rules by: a) highlighting possible problems that the rules may generate, and b) allowing their step-by-step simulation. The approach, based on Semantic Web and Petri Nets, has been implemented in a EUD tool, and it has been preliminary evaluated in a user study with 6 participants. Results provide evidence that the tool is usable, and it helps users in understanding and identifying problems in trigger-action rules