Jean Marcel dos Reis Costa

Mindless computing: designing technologies to subtly influence behavior

Persuasive technologies aim to influence users behaviors. In order to be effective, many of the persuasive technologies developed so far relies on users motivation and ability, which is highly variable and often the reason behind the failure of such technology. In this paper, we present the concept of Mindless Computing, which is a new approach to persuasive technology design. Mindless Computing leverages theories and concepts from psychology and behavioral economics into the design of technologies for behavior change. We show through a systematic review that most of the current persuasive technologies do not utilize the fast and automatic mental processes for behavioral change and there is an opportunity for persuasive technology designers to develop systems that are less reliant on users motivation and ability. We describe two examples of mindless technologies and present pilot studies with encouraging results. Finally, we discuss design guidelines and considerations for developing this type of persuasive technology.

The scale and evolution of coordination needs in large-scale distributed projects: implications for the future generation of collaborative tools

The past decade has witnessed the development of a new class of coordination tools that focus on automatically providing individuals a rich context for facilitating the coordination of their work. Despite their valuable contributions, current coordination tools have mostly been designed without taking into account scalability aspects beyond the small-group level. The increasing pervasiveness of large-scale projects suggests that those mechanisms need to scale dramatically to adequately support such work settings. In this paper, we used data from five distinct large-scale projects from three different companies to study the scale, range, and volatility of the coordination requirements that emerged over time within those projects. Our results showed that coordination requirements tend to be quite volatile, vary significantly in their magnitude across project members and a significant proportion of the coordination requirements cut across organizational and geographical boundaries. Furthermore, new coordination requirements represent, on average, a third of the coordination requirements faced by a project member on a monthly basis. The implications of these results for the design of collaborative tools are discussed.

Collective Smile: Measuring Societal Happiness from Geolocated Images

The increasing adoption of social media provides unprecedented opportunities to gain insight into human nature at vastly broader scales. Regarding the study of population-wide sentiment, prior research commonly focuses on text-based analyses and ignores a treasure trove of sentiment-laden content: images. In this paper, we make methodological and computational contributions by introducing the Smile Index as a formalized measure of societal happiness. Detecting smiles in 9 million geo-located tweets over 16 months, we validate our Smile Index against both text-based techniques and self-reported happiness. We further make observational contributions by applying our metric to explore temporal trends in sentiment, relate public mood to societal events, and predict economic indicators. Reflecting upon the innate, language-independent aspects of facial expressions, we recommend future improvements and applications to enable robust, global-level analyses. We conclude with implications for researchers studying and facilitating the expression of collective emotion through socio-technical systems.

EmotionCheck: leveraging bodily signals and false feedback to regulate our emotions

In this paper we demonstrate that it is possible to help individuals regulate their emotions with mobile interventions that leverage the way we naturally react to our bodily signals. Previous studies demonstrate that the awareness of our bodily signals, such as our heart rate, directly influences the way we feel. By leveraging these findings we designed a wearable device to regulate users anxiety by providing a false feedback of a slow heart rate. The results of an experiment with 67 participants show that the device kept the anxiety of the individuals in low levels when compared to the control group and the other conditions. We discuss the implications of our findings and present some promising directions for designing and developing this type of intervention for emotion regulation.

Analyzing the scalability of coordination requirements of a distributed software project

Collaborative tools have been proposed to support different domains, including software development. Despite important previous work on the design of collaborative tools, none directly addresses the required scalability of these collaborative tools. As such, the design of these tools is hindered because it does not take into account real-world requirements for handling and presenting information to support collaborative activities. In this paper, we use an approach to compute the coordination requirements of an actor, and by so doing, we are able to identify the required scalability of the collaborative tools to support these actors. The coordination requirements are the likely set of actors that a particular individual might need to coordinate/communicate with. We computed the coordination requirements of software developers involved in a large-scale distributed software development project. Software developers’ coordination requirements were computed in four different time intervals: 1, 7, 15, and 30 days so that we could assess the scalability of collaborative tools in both short and long term software development activities. Our results suggest that, in some cases, the number of coordination requirements of a given actor might be very large, and that current collaborative software development tools do not provide proper support for such values. Furthermore, we observed that coordination requirements often involved members of different teams and from different locations, which increases the importance of having collaborative tools properly designed, given the difficulty of collaborating across organizational and geographical boundaries.

An intelligent crowd-worker selection approach for reliable content labeling of food images

Food journaling is an effective way to regulate excessive food intake. However manual food journaling is burdensome, and crowd-assisted food journaling has been explored to ease user burden. The crowd-assisted journaling uses a label & verify approach where an end-user uploads his/her food image and paid crowd-workers label content of the image. Then another set of crowd-workers verify the labels for correctness. In this paper, we propose an alternative approach where we label food images with only high performing labelers. Since high performing labelers generally provide good quality labels, our approach achieves high accuracy without verifying the food labels for correctness. We also propose a machine learning algorithm to automatically identify high performing crowd-labelers from a dataset of 3925 images collected over 5 months. Such automated identification of high performing workers and elimination of needless verification reduce cost of food labeling. Specially for large scale deployments where large number of images need to be labeled, our approach can reduce overall expenses by half.

Regulating Feelings During Interpersonal Conflicts by Changing Voice Self-perception

Emotions play a major role in how interpersonal conflicts unfold. Although several strategies and technological approaches have been proposed for emotion regulation, they often require conscious attention and effort. This often limits their efficacy in practice. In this paper, we propose a different approach inspired by self-perception theory: noticing that people are often reacting to the perception of their own behavior, we artificially change their perceptions to influence their emotions. We conducted two studies to evaluate the potential of this approach by automatically and subtly altering how people perceive their own voice. In one study, participants that received voice feedback with a calmer tone during relationship conflicts felt less anxious. In the other study, participants who listened to their own voices with a lower pitch during contentious debates felt more powerful. We discuss the implications of our findings and the opportunities for designing automatic and less perceptible emotion regulation systems.

Using TransFlow to Analyze Open Source Developers' Evolution

Due to the success of many Open Source Software projects, both the industry and the academic community are interested in understanding how such software is produced. Particularly, there is interest in understanding how these communities are organized and maintained, and also how the contributors join and evolve their roles in these projects. However, few studies have been conducted around the evolution of the developers in the communities, i.e., how they reach roles of greater importance, and how the software changes over time through this evolution. This paper describes TransFlow a tool aimed to support the integrated study of the evolution of both: the software itself and the developers’ participation in open source projects. This integrated study is a requirement since the software architecture may support or hinder developers’ participation in the project. Transflow’s main features and architecture are described, as well as its evaluation with three open-source projects.

AlertnessScanner: what do your pupils tell about your alertness

Alertness is a crucial component of our cognitive performance. Reduced alertness can negatively impact memory consolidation, productivity and safety. As a result, there has been an increasing focus on continuous assessment of alertness. The existing methods usually require users to wear sensors, fill out questionnaires, or perform response time tests periodically, in order to track their alertness. These methods may be obtrusvie to some users, and thus have limited capability. In this work, we propose AlertnessScanner, a computer-vision-based system that collects in-situ pupil information to model alertness in the wild. We conducted two in-the-wild studies to evaluate the effectiveness of our solution, and found that AlertnessScanner passively and unobtrusively assess alertness. We discuss the implications of our findings and present opportunities for mobile applications that measure and act upon changes in alertness.

Dites-moi: wearable feedback on conversational behavior

Interpersonal communication skills are critical in certain industry sectors like sales and marketing. Recent advances in wearable technology are enabling the design of real-time behavioral feedback tools for apprentices in aforementioned industries. This paper describes the design and implementation of a conversational behavior awareness tool based on Google Glass. The goal of the system is to provide real-time feedback to young sales apprentices about the amount of time they talk in an interaction with a client. We evaluated our system with a pilot study involving 15 apprentices (ages 16--20). Overall, participants found the system fun, little distracting and useful. Furthermore, manual coding of the recorded videos, showed that wearable sensing and real-time feedback did not negatively influence the dyadic social interaction.