Abstract

Abstract
The purpose of this study is to conduct a bibliometric and taxonomy-based analysis of the field of CSCW to map its recent evolution at a quantitative and qualitative level. A model for semantic analytics and social evaluation is also discussed with emphasis on the hypothesis of putting crowds into the loop of bibliography classification process to improve the current labor-intensive, time-consuming, unrepeatable and sometimes subjective task of scientometricians. A total of 1,480 publications were carefully reviewed and subjected to scientometric data analysis methods and techniques. Analyzed parameters included document orientation, deviation from trend in the total number of citations, and publication activity by author's affiliation country. A semantic classification of 541 publications allows identifying growing trends and lacking research indicators. At a human-centered perspective, limitations are unfilled in the limitative analytical spectrum, laborious and time-consuming processes of data seeking, gathering, cataloguing and analysis, subjective results at a taxonomic level, lack of more bibliographic data analytics perspectives, and absence of human-centered results concerning cognitive aspects in meta-knowledge research practices. Hypotheses are suggested towards a crowd-enabled model for bibliography evaluation in order to understand the ways as humans and machines can work cooperatively and massively on scientific data to solve complex problems. © 2013 Springer-Verlag.

Abstract

Abstract
Over the last decades, CSCW research has undergone significant structural changes and has grown steadily with manifested differences from other fields in terms of theory building, methodology, and socio-technicality. This paper provides a quantitative assessment of the scientific literature for mapping the intellectual structure of CSCW research and its scientific development over a 15-year period (2001-2015). A total of 1713 publications were subjected to examination in order to draw statistics and depict dynamic changes to shed new light upon the growth, spread, and collaboration of CSCW devoted outlets. Overall, our study characterizes top (cited and downloaded) papers, citation patterns, prominent authors and institutions, demographics, collaboration patterns, most frequent topic clusters and keywords, and social mentions by country, discipline, and professional status. The results highlight some areas of improvement for the field and a lot of well-established topics which are changing gradually with impact on citations and downloads. Statistical models reveal that the field is predominantly influenced by fundamental and highly recognized scientists and papers. A small number of papers without citations, the growth of the number of papers by year, and an average number of more than 39 citations per paper in all venues ensure the field a healthy and evolving nature. We discuss the implications of these findings in terms of the influence of CSCW on the larger field of HCI.

Abstract
Current times are denoting unprecedented indicators of scientific data production, and the involvement of the wider public (the crowd) on research has attracted increasing attention. Drawing on review of extant literature, this paper outlines some ways in which crowdsourcing and mass collaboration can leverage the design of intelligent systems to keep pace with the rapid transformation of scientific work. A systematic literature review was performed following the guidelines of evidence-based software engineering and a total of 148 papers were identified as primary after querying digital libraries. From our review, a lack of methodological frameworks and algorithms for enhancing interactive intelligent systems by combining machine and crowd intelligence is clearly manifested and we will need more technical support in the future. We lay out a vision for a cyberinfrastructure that comprises crowd behavior, task features, platform facilities, and integration of human inputs into AI systems. © Springer Nature Switzerland AG 2018.

Abstract
Technological evolution impacts the research and development of new solutions, as well as consumers’ expectations and behaviors. With the advent of the new millennium, collaboration systems and technologies were introduced to support ordinary cooperative work and inter-dependent, socially and culturally mediated practices as integral units of everyday life settings. Nevertheless, existing classification systems are limited in scope to analyze technological developments and capture the intellectual structure of a field, understood as an abstraction of the collective knowledge of its researchers and their socially mediated activities. Ten years after the introduction of Mittleman et al.’s taxonomy, we build upon earlier work and adopt this classification scheme to provide a descriptive, taxonomy-based analysis of four distinct venues focused on collaborative computing research: ACM CSCW, ACM GROUP, ECSCW, and CRIWG. The proposal consists of achieving evidence on technical attributes and impacts towards characterizing the evolution of socio-technical systems via (and for) taxonomic modeling. This study can also constitute an important step towards the emergence of new, potentially more valid and robust evaluation studies combining Grounded Theory with alternative methods and techniques. © Springer Nature Switzerland AG 2018.