Despite the increasing prevalence of algorithm-mediated public services, there continues to be a limited understanding of citizens’ perspectives on this matter, particularly in the Global South. This study explores citizens’ experiences as users and affected stakeholders of algorithm-supported decision-making. From a qualitative perspective, we conducted and analyzed face-to-face interviews (N = 27) in Santiago, Chile. From the standpoint of folk theories as behavior guides, we identified that people tend to associate AI and algorithms with expanding the State’s monitoring, organizing, and decision-making capacity. At the same time, they express a prevailing sense of trust, but with certain boundaries. This trust is influenced by factors, such as a belief in AI’s future promise, a need for human mediation, and limitations related to structural inequalities. These findings underscore the responsibility placed on technology developers and public policymakers, emphasizing the importance of adopting an intersectional and position-based approach to AI design.

Abstract With over 300 language communities, Wikipedia offers a multilingual environment for collective reporting of events worldwide. However, most research on documenting events has focused on English Wikipedia. Our work explores the extent of global coverage of event articles in the English Wikipedia and Wikipedia communities associated with three of the most spoken languages globally: Arabic, Chinese and Spanish. We also compare the process of collaboratively writing event articles across these communities. Our results provide evidence that while there is an indication of self-focus bias, there is also strong evidence of a global representation of events across different Wikipedia communities. Moreover, we observe that while limited resources in smaller Wikipedia communities have different collaboration patterns, their efforts lead to similar levels of content quality after a week. We discuss the implications of our results for Wikipedia and the design of multi-language information production communities.

As the adoption of knowledge graphs grows, more and more non-experts users need to be able to explore and query such graphs. These users are not typically familiar with graph query languages such as SPARQL, and may not be familiar with the knowledge graph's structure. In this extended abstract, we provide a summary of our work on a language and visual interface -- called RDF Explorer -- that help non-expert users to navigate and query knowledge graphs. A usability study over Wikidata shows that users successfully complete more tasks with RDF Explorer than with the existing Wikidata Query Helper interface.

Although a variety of user story refinement techniques have been proposed, there are still few empirical studies that assess their effectiveness in the industry. This paper reports the results of a mixed methods approach to evaluate the combined use of techniques for refining user stories in a Chilean banking organization. A combination of INVEST, 3 Cs and Specification by Example (SbE) techniques was proposed to improve the quality of user stories that were being generated in the organization during its transition from traditional development methods to agility. To validate the proposal, a comparison of case studies was carried out. A group of user stories that were created and refined with the method previously used in the organization was contrasted with a second and third group of stories for which the proposed technique was used. The results show that the combined use of INVEST, 3 Cs and SbE improved the user stories quality and was related to positive changes in the development team motivation.

Various information systems have emerged to facilitate citizen participation in the life of their communities. However, there is a lack of robust understanding of what enables the sustainability of such systems. This work introduces a framework to identify and analyze various factors that influence the sustainability of “hyper-local” information systems. Using longitudinal observations of participation from 35 online neighborhood discussion forums over six years, we analyze the relationship between sustainability and online–offline community characteristics. Our results not only show patterns consistent with previous observations but reveal the dubious influences of member heterogeneity and network structure. Design insights are discussed.

We survey across generations of work in authorized cheat sheets, and emphasize on extracting generic features for designing one. We construct generic models to address cognitive aspects of learning and focus on the content of knowledge components in the domain of programming language learning. We evaluate the models with real classroom study data and found that the amount of notes on a cheat sheet is associated with gains in students' declarative knowledge, but not procedural knowledge. We also discovered that working in creating new cheat sheets can help students to achieve better exam grades accumulatively beyond and above the effect of their performance in a prior exam. We discuss how these findings can guide the design of technology-based study guides.

We present a theoretical foundation and empirical findings demonstrating the effectiveness of personality-targeted design. Much like a medical treatment applied to a person based on his specific genetic profile, we argue that theory-driven, personality-targeted UI design can be more effective than design applied to the entire population. The empirical exploration focused on two settings, two populations and two personality traits: Study 1 shows that users' extraversion level moderates the relationship between the UI cue of audience size and users' contribution. Study 2 demonstrates that the effectiveness of social anchors in encouraging online contributions depends on users' level of emotional stability. Taken together, the findings demonstrate the potential and robustness of the interactionist approach to UI design. The findings contribute to the HCI community, and in particular to designers of social systems, by providing guidelines to targeted design that can increase online participation.

While there is significant potential for social technologies to strengthen local communities, creating viable online spaces for them remains difficult. Maintaining a reliable content stream is challenging for local communities with their bounded emphases and limited population of potential contributors. Some systems focus on specific information types (e.g. restaurant, events). Others allow many different information types. This paper reports our findings about the consequences of content diversity from a study of neighborhood-oriented Facebook groups. The findings raise questions about the viability of designs for local online communities that focus narrowly on single topics, goals, and audiences.

Successful contributors in online communities go through a lifecycle of membership status starting from the periphery and moving to the core over time. We argue that a personalized incremental engagement strategy can mobilize a larger proportion of members through this process. This paper presents our approach to identify a progression of contributions in an online community and the design of personalized incremental engagement strategy which will drive users' contributions one step forward. The results of our field study show that the personalized incremental approach significantly boosts contributions in an online community for academic conferences.

Practice has proven that softgoal interdependency graphs(SIGs) are a very useful tool for recording and reasoning about non-functional requirements [4], [6], [8]. Practical reuse and design of SIGs, however, rely on the capacity of manually identifying reusable structures, interdependencies, and eliminating harmful redundancies. In this paper, we tackle this shortcomings by firstly proposing a frame representation, that allows us to represent SIGs in terms of lattice-like generalization/specialization hierarchies that can be queried. Secondly, we introduce a closeness criteria that, in the absence of perfect matches, will allow querying for similar or ldquogood enoughrdquo approximations. This mechanism is particularly useful in the identification of softgoal interdependencies. Finally, we argue how the proposed strategy can be used to help identify conflicts in SIG graphs.