@article {Ripoche2006,
	title = {Experiences in Automating the Analysis of Linguistic Interactions for the Study of Distributed Collectives},
	journal = {Computer Supported Cooperative Work (CSCW)},
	volume = {15},
	number = {2},
	year = {2006},
	note = {flossmole is mentioned in passing},
	pages = {149{\textendash}183},
	abstract = {An important issue faced by research on distributed collective practices is the amount and nature of the data available for study. While persistent mediated interaction offers unprecedented opportunities for research, the wealth and richness of available data pose issues on their own, calling for new methods of investigation. In such a context, automated tools can offer coverage, both within and across collectives. In this paper, we investigate the potential contributions of semantic analyses of linguistic interactions for the study of collective processes and practices. In other words, we are interested in discovering how linguistic interaction is related to collective action, as well as in exploring how computational tools can make use of these relationships for the study of distributed collectives.},
	keywords = {flossmole cited},
	issn = {1573-7551},
	doi = {10.1007/s10606-006-9017-0},
	url = {http://dx.doi.org/10.1007/s10606-006-9017-0},
	author = {Gabriel Ripoche and Sansonnet, Jean-Paul}
}
@conference {Gasser04researchinfrastructure,
	title = {Research Infrastructure for Empirical Science of F/OSS},
	booktitle = {Proc. Intern. Workshop on Mining Software Repositories},
	year = {2004},
	pages = {12-16},
	abstract = {F/OSS research faces a new and unusual situation: the traditional difficulties of gathering enough empirical data have been replaced by issues of dealing with enormous amounts of freely available data from many disparate sources (forums, code, bug reports, etc.) At present no means exist for assembling these data under common access points and frameworks for comparative, longitudinal, and collaborative research. Gathering and maintaining large F/OSS data collections reliably and making them usable present several research challenges. For example, current projects usually rely on {\textquotedblleft}web scraping{\textquotedblright} or on direct access to raw data from groups that generate it, and both of these methods require unique effort for each new corpus, or even for updating existing corpora. In this paper we identify several common needs and critical factors in F/OSS empirical research, and suggest orientations and recommendations for the design of a shared research infrastructure.},
	keywords = {data, Data Collection, empirical, infrastructure},
	attachments = {https://flosshub.org/sites/flosshub.org/files/12ResearchInfrastructure.pdf},
	author = {Gasser, Les and Gabriel Ripoche and Sandusky, Robert J.}
}
@conference {1109,
	title = {Distributed Collective Practices and F/OSS Problem Management: Perspective and Methods},
	booktitle = {Conference on Cooperation, Innovation \& Technology (CITE 2003)},
	year = {2003},
	note = {"We have begun studying in detail the general issues raised above using a large collection of research data from the Mozilla project"
"Our Bugzilla snapshot contains over 128,000 problem reports, of which about 88,000 have been resolved"},
	abstract = {This paper presents the state of our research on Distributed Collective Practices (DCPs) in Free/Open-Source Software (F/OSS) projects, focusing on sensemaking and resolution of software problems. We are exploring the hypothesis that variations in the content and in the articulation of these socio-technical processes have an impact on the outcome of the activity of F/OSS collectives, and more specifically on problem resolution. Our preliminary techniques for combining qualitative data analysis with automated process extraction result in a scalable analysis method called Computational Amplification (CA). We are applying CA to 128,000 problem reports from the Mozilla F/OSS project. The paper illustrates how CA is used to create multidimensional process models and shows types of conclusions we can reach.},
	keywords = {Automated process extraction, bug fixing, bug reports, bugzilla, Collective knowledge management, Information extraction from natural language texts, mozilla, Software problem management},
	author = {Gasser, Les and Gabriel Ripoche}
}
