1,720,961 research outputs found
An Abstract State Machine (ASM) Representation of Learning in FLOSS Communities
Free/Libre Open Source Software (FLOSS) communities as collaborative environments enable the occurrence of learning between participants in these groups. With the increasing interest research on understanding the mechanisms and processes through which learning occurs in FLOSS, there is an imperative to describe these processes. One successful way of doing this is through specification methods. In this paper, we describe the adoption of Abstract States Machines (ASMs) as a specification methodology for the description of learning processes in FLOSS. The goal of this endeavor is to represent the many possible steps and/or activities FLOSS participants go through during interactions that can be categorized as learning processes. Through ASMs, we express learning phases as states while activities that take place before moving from one state to another are expressed as transitions
Process Mining Event Logs from {FLOSS} Data: State of the Art and Perspectives
Free/Libre Open Source Software (FLOSS) is a phenomenon that has undoubtedly triggered extensive research endeavors. At the heart of these initiatives is the ability to mine data from FLOSS repositories with the hope of revealing empirical evidence to answer existing questions on the FLOSS development process. In spite of the success produced with existing mining techniques, emerging questions about FLOSS data require alternative and more appropriate ways to explore and analyse such data.
In this paper, we explore a different perspective called process mining. Process mining has been proved to be successful in terms of tracing and reconstructing process models from data logs (event logs). The chief objective of our analysis is threefold. We aim to achieve: (1) conformance to predefined models; (2) discovery of new model patterns; and, finally, (3) extension to predefined models
OntoLiFLOSS: Ontology for Learning Processes in {FLOSS} Communities
Free/Libre Open Source Software (FLOSS) communities are considered an example of commons-based peer-production models where groups of participants work together to achieve projects of common purpose. In these settings, many occurring activities can be documented and have established them as learning environments. As knowledge exchange is proved to occur in FLOSS, the dynamic and free nature of participation poses a great challenge in understanding activities pertaining to Learning Processes.
In this paper we raise this question and propose an ontology (called OntoLiFLOSS) in order to define terms and concepts that can explain learning activities taking place in these communities. The objective of this endeavor is to define in the simplest possible way a common definition of concepts and activities that can guide the identification of learning processes taking place among FLOSS members in any of the standard repositories such as mailing list, SVN, bug trackers and even discussion forums
Mining Learning Processes from FLOSS Mailing Archives
Part 4: E-Business, E-Services and E-SocietyInternational audienceEvidence suggests that Free/Libre Open Source Software (FLOSS) environments provide unlimited learning opportunities. Community members engage in a number of activities both during their interaction with their peers and while making use of these environments. As FLOSS repositories store data about participants’ interaction and activities, we analyze participants’ interaction and knowledge exchange in emails to trace learning activities that occur in distinct phases of the learning process. We make use of semantic search in SQL to retrieve data and build corresponding event logs which are then fed to a process mining tool in order to produce visual workflow nets. We view these nets as representative of the traces of learning activities in FLOSS as well as their relevant flow of occurrence. Additional statistical details are provided to contextualize and describe these models
Going Beyond Counting First Authors in Author Co-citation Analysis
The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
We provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
We conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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