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Rob Laubacher

Bio: Rob Laubacher is an academic researcher from Massachusetts Institute of Technology. The author has contributed to research in topics: The Internet & Social network analysis. The author has an hindex of 1, co-authored 1 publications receiving 145 citations.

Papers
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Proceedings ArticleDOI
03 Nov 2003
TL;DR: First results of a project that examines innovation networks by analyzing the e-mail archives of some W3C (WWW consortium) working groups are reported, which revealed significant variations between the communication patterns and network structures of the different groups.
Abstract: Collaborative Innovation Networks (COINs) are groups of self-motivated individuals from various parts of an organization or from multiple organizations, empowered by the Internet, who work together on a new idea, driven by a common vision. In this paper we report first results of a project that examines innovation networks by analyzing the e-mail archives of some W3C (WWW consortium) working groups. These groups exhibit ideal characteristics for our purpose, as they form truly global networks working together over the Internet to develop next generation technologies. We first describe the software tools we developed to visualize the temporal communication flow, which represent communication patterns as directed acyclic graphs, We then show initial results, which revealed significant variations between the communication patterns and network structures of the different groups., We were also able to identify distinctive communication patterns among group leaders, both those who were officially appointed and other who were assuming unofficial coordinating roles.

147 citations

Journal ArticleDOI
TL;DR: In this article , the authors derive seven AI affordances that support 17 facilitation activities in macro-task crowdsourcing and identify specific manifestations that illustrate the affordances, which can help practitioners identify potential ways to integrate AI into crowdsourcing facilitation.
Abstract: Abstract Crowdsourcing holds great potential: macro-task crowdsourcing can, for example, contribute to work addressing climate change. Macro-task crowdsourcing aims to use the wisdom of a crowd to tackle non-trivial tasks such as wicked problems. However, macro-task crowdsourcing is labor-intensive and complex to facilitate, which limits its efficiency, effectiveness, and use. Technological advancements in artificial intelligence (AI) might overcome these limits by supporting the facilitation of crowdsourcing. However, AI’s potential for macro-task crowdsourcing facilitation needs to be better understood for this to happen. Here, we turn to affordance theory to develop this understanding. Affordances help us describe action possibilities that characterize the relationship between the facilitator and AI, within macro-task crowdsourcing. We follow a two-stage, bottom-up approach: The initial development stage is based on a structured analysis of academic literature. The subsequent validation & refinement stage includes two observed macro-task crowdsourcing initiatives and six expert interviews. From our analysis, we derive seven AI affordances that support 17 facilitation activities in macro-task crowdsourcing. We also identify specific manifestations that illustrate the affordances. Our findings increase the scholarly understanding of macro-task crowdsourcing and advance the discourse on facilitation. Further, they help practitioners identify potential ways to integrate AI into crowdsourcing facilitation. These results could improve the efficiency of facilitation activities and the effectiveness of macro-task crowdsourcing.

1 citations


Cited by
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Journal ArticleDOI
TL;DR: The Flink system for the extraction, aggregation and visualization of online social networks is presented and a novel method to social science based on electronic data is demonstrated using the example of the Semantic Web research community.

416 citations

Book
18 Sep 2007
TL;DR: This paper presents an ontology for the representation of social networks and relationships, a hybrid system for online data acquisition that combines traditional web mining techniques with the collection of Semantic Web data, and a case study highlighting some of the possible analysis of this data using methods from Social Network Analysis.
Abstract: A formal, web-based representation of social networks is both a necessity in terms of infrastructure as well as a prominent application for the Semantic Web. In this paper we present three advances in exploiting the opportunity of semantically-enriched network data: (1) an ontology for the representation of social networks and relationships (2) a hybrid system for online data acquisition that combines traditional web mining techniques with the collection of Semantic Web data (2) a case study highlighting some of the possible analysis of this data using methods from Social Network Analysis, the branch of sociology concerned with relational data.

320 citations

Proceedings ArticleDOI
16 May 2009
TL;DR: Although it was found that no individual measure could indicate whether a build will fail or succeed, the combination of communication structure measures were leveraged into a predictive model that indicates whether an integration will fail.
Abstract: A critical factor in work group coordination, communication has been studied extensively. Yet, we are missing objective evidence of the relationship between successful coordination outcome and communication structures. Using data from IBM's Jazz™ project, we study communication structures of development teams with high coordination needs. We conceptualize coordination outcome by the result of their code integration build processes (successful or failed) and study team communication structures with social network measures. Our results indicate that developer communication plays an important role in the quality of software integrations. Although we found that no individual measure could indicate whether a build will fail or succeed, we leveraged the combination of communication structure measures into a predictive model that indicates whether an integration will fail. When used for five project teams, our predictive model yielded recall values between 55% and 75%, and precision values between 50% to 76%.

238 citations

Journal ArticleDOI
TL;DR: This study finds a considerable degree of co-authorship clustering and a positive impact of the extent of co -authorship on the diffusion of works on enterprise architecture and proposes an agenda for future research based on the findings from the above analyses and their comparison to empirical insights from the literature.
Abstract: Management of the enterprise architecture has become increasingly recognized as a crucial part of both business and IT management. Still, a common understanding and methodological consistency seems far from being developed. Acknowledging the significant role of research in moving the development process along, this article employs different bibliometric methods, complemented by an extensive qualitative interpretation of the research field, to provide a unique overview of the enterprise architecture literature. After answering our research questions about the collaboration via co-authorships, the intellectual structure of the research field and its most influential works, and the principal themes of research, we propose an agenda for future research based on the findings from the above analyses and their comparison to empirical insights from the literature. In particular, our study finds a considerable degree of co-authorship clustering and a positive impact of the extent of co-authorship on the diffusion of works on enterprise architecture. In addition, this article identifies three major research streams and shows that research to date has revolved around specific themes, while some of high practical relevance receive minor attention. Hence, the contribution of our study is manifold and offers support for researchers and practitioners alike.

194 citations

Journal ArticleDOI
TL;DR: The altruistic sharing of knowledge between knowledge providers and knowledge seekers in the Developer and User mailing lists of the Debian project is discussed and the knowledge sharing activity of self-organizing Free/Open Source communities could best be explained in terms of what is called ''Fractal Cubic Distribution'' rather than the power-law distribution mostly reported in the literature.

160 citations