Abstract
The structure and evolution of a scientific research community can be quantitatively assessed taking into account the interactions between scientific agents dispersed geographically. In the recent years, CSCW has stabilized as a cross-disciplinary field suffering significant changes in its core structure, and there is limited understanding about the factors influencing the nature and progress of collaborative computing research. In this paper, we measure the correlation between a set of features related to the influence of collaboration types on the number of citations as well as the geographical distribution of the accumulated contribution to the CSCW literature. Overall, our work can represent a starting point to demonstrate how the study of scientific collaboration can partly explain the variations in the number of citations, frequency of papers, and topics addressed.

Abstract

Abstract
Crowdsourcing has shown to be a valuable problem-solving approach to handle the increasing complexity and scale of tasks for which the current AI algorithms are still struggling. Crowd intelligence can be particularly useful to train and supervise AI systems in a symbiotic, co-evolutionary relationship that raises long-term research challenges to the hybrid, crowd-computing design space. With the increase in the scale of mixed-initiative approaches, we need to gain a better understanding of the implications of crowd-powered systems as a scaffold for AI through the study of massive crowd-machine interactions. In this paper, we identify some open challenges and design implications for future crowd-AI hybrid systems. A framework is also proposed based on the practical challenges of addressing human-centered AI methods and processes.

Abstract
A substantial amount of work is often overlooked due to the exponential rate of growth in global scientific output across all disciplines. Current approaches for addressing this issue are usually limited in scope and often restrict the possibility of obtaining multidisciplinary views in practice. To tackle this problem, researchers can now leverage an ecosystem of citizens, volunteers and crowd workers to perform complex tasks that are either difficult for humans and machines to solve alone. Motivated by the idea that human crowds and computer algorithms have complementary strengths, we present an approach where the machine will learn from crowd behavior in an iterative way. This approach is embodied in the architecture of SciCrowd, a crowd-powered human-machine hybrid system designed to improve the analysis and processing of large amounts of publication records. To validate the proposal's feasibility, a prototype was developed and an initial evaluation was conducted to measure its robustness and reliability. We conclude this paper with a set of implications for design.

Abstract
The present study aims to translate and validate the Temple Presence Inventory (TPI) for the Portuguese context, respecting the maintenance of an equivalent semantics as well as the validity of its contents and concepts. This study also aims to verify the psychometric properties of the instrument (factor validity and internal consistency). The sample consisted of 455 individuals (male = 271, female = 184). The fidelity of the factors varied between 0.5 and 0.84. The confirmatory factor analysis produced a theoretical model with 38 items distributed among eight factors. The covariance between some residual errors of instrument items was considered, and the following fit indices were observed: chi 2/df = 2.073; GFI = 0.858; CFI = 0.887; RSMEA = 0.049; AIC = 1527. The results confirm the appropriateness of the version adapted to the Portuguese language of the TPI and that it can be used in research projects aiming to evaluate Presence in the Portuguese-speaking population (Europe).

Abstract
This investigation concerns the translation and validation of the ITC - Sense of Presence Inventory (ITC-SOPI) for the Portuguese-speaking population (in Europe), estimating the validity of the content and concepts and the maintenance of an equivalent semantics. It also sought to verify its psychometric properties, namely its factorial validity and internal consistency. The sample consisted of 459 individuals, 274 males and 185 females. The fidelity of the subscales varied between 0.67 and 0.89. Confirmatory factor analysis revealed a theoretical model of 35 items, divided by four factors. After fixing some of the residual errors between items, the following adjustment indexes were calculated: chi(2)/df = 2.301; goodness fit index = 0.860; comparative fitness index = 0.889; root mean square error of approximation = 0.053; Akaike's information criterion = 1420. Based on the observed results and the robustness of the sample size used, the obtained theoretical model shows that the ITC-SOPI is recommended to measure presence in virtual reality research projects with samples of Portuguese language speakers.