What Can OSS Mailing Lists Tell Us? A Preliminary Psychometric Text Analysis of the Apache Developer Mailing List

Author(s):  
Peter C. Rigby ◽  
Ahmed E. Hassan
2004 ◽  
Vol 48 (4) ◽  
pp. 634-641 ◽  
Author(s):  
Amparo Alcina-Caudet

Abstract How often students use IT resources is a key factor in the acquisition of skills associated to the new technologies. Strategies aimed at increasing student autonomy need to be developed and should offer resources that encourage them to make use of computing tools outside class hours. The mailing list INFOTRAD was created with the aim of encouraging the use of e-mail and of familiarising students of Translation and Interpreting with mailing lists. In this paper, we look at the chief characteristics of this list, how it came into being and the results obtained during its first six months in operation.


2021 ◽  
Vol 29 (1) ◽  
Author(s):  
Thomas Bock ◽  
Claus Hunsen ◽  
Mitchell Joblin ◽  
Sven Apel

AbstractMailing lists are a major communication channel for supporting developer coordination in open-source software projects. In a recent study, researchers explored temporal relationships (e.g., synchronization) between developer activities on source code and on the mailing list, relying on simple heuristics of developer collaboration (e.g., co-editing files) and developer communication (e.g., sending e-mails to the mailing list). We propose two methods for studying synchronization between collaboration and communication activities from a higher-level perspective, which captures the complex activities and views of developers more precisely than the rather technical perspective of previous work. On the one hand, we explore developer collaboration at the level of features (not files), which are higher-level concepts of the domain and not mere technical artifacts. On the other hand, we lift the view of developer communication from a message-based model, which treats each e-mail individually, to a conversation-based model, which is semantically richer due to grouping e-mails that represent conceptually related discussions. By means of an empirical study, we investigate whether the different abstraction levels affect the observed relationship between commit activity and e-mail communication using state-of-the-art time-series analysis. For this purpose, we analyze a combined history of 40 years of data for three highly active and widely deployed open-source projects: QEMU, BusyBox, and OpenSSL. Overall, we found evidence that a higher-level view on the coordination of developers leads to identifying a stronger statistical dependence between the technical activities of developers than a less abstract and rather technical view.


Crisis ◽  
2016 ◽  
Vol 37 (2) ◽  
pp. 140-147 ◽  
Author(s):  
Michael J. Egnoto ◽  
Darrin J. Griffin

Abstract. Background: Identifying precursors that will aid in the discovery of individuals who may harm themselves or others has long been a focus of scholarly research. Aim: This work set out to determine if it is possible to use the legacy tokens of active shooters and notes left from individuals who completed suicide to uncover signals that foreshadow their behavior. Method: A total of 25 suicide notes and 21 legacy tokens were compared with a sample of over 20,000 student writings for a preliminary computer-assisted text analysis to determine what differences can be coded with existing computer software to better identify students who may commit self-harm or harm to others. Results: The results support that text analysis techniques with the Linguistic Inquiry and Word Count (LIWC) tool are effective for identifying suicidal or homicidal writings as distinct from each other and from a variety of student writings in an automated fashion. Conclusion: Findings indicate support for automated identification of writings that were associated with harm to self, harm to others, and various other student writing products. This work begins to uncover the viability or larger scale, low cost methods of automatic detection for individuals suffering from harmful ideation.


Author(s):  
Natalie Shapira ◽  
Gal Lazarus ◽  
Yoav Goldberg ◽  
Eva Gilboa-Schechtman ◽  
Rivka Tuval-Mashiach ◽  
...  

1977 ◽  
Vol 16 (03) ◽  
pp. 144-153 ◽  
Author(s):  
E. Vaccari ◽  
W. Delaney ◽  
A. Chiesa

A software system for the automatic free-text analysis and retrieval of radiological reports is presented. Such software involves: (1) automatic translation of the specific natural language in a formalized metalanguage in order to transform the radiological report in a »normalized report« analyzable by computer; (2) content processing of the normalized report to select desired information. The approach used to accomplish point (1) is described in detail referring to a specific application.


1991 ◽  
Vol 30 (04) ◽  
pp. 275-283 ◽  
Author(s):  
P. M. Pietrzyk

Abstract:Much information about patients is stored in free text. Hence, the computerized processing of medical language data has been a well-known goal of medical informatics resulting in different paradigms. In Gottingen, a Medical Text Analysis System for German (abbr. MediTAS) has been under development for some time, trying to combine and to extend these paradigms. This article concentrates on the automated syntax analysis of German medical utterances. The investigated text material consists of 8,790 distinct utterances extracted from the summary sections of about 18,400 cytopathological findings reports. The parsing is based upon a new approach called Left-Associative Grammar (LAG) developed by Hausser. By extending considerably the LAG approach, most of the grammatical constructions occurring in the text material could be covered.


Author(s):  
Elena A. Fedorova ◽  
Diana V. Zaripova ◽  
Igor S. Demin

This work confirmed the hypotheses about the influence of the mood index on Twitter on the pricing of art objects and the difference between the experts' estimations and the final price of the auction. The hypotheses were tested with the use of a sample of 83 paintings selected on the basis of ratings of ARTNET's online resource about the most expensive works of art ever sold in the last 10–15 years. The sample consisted of 25 artists, for each of them was made an index of moods on Twitter. This index was created by a sentimental analysis of each tweet about the artist on the hashtag for a period of 2 to 4 months between the announcements of sales in the open sources and the direct sale of the work with the use of the two dictionaries AFINN and NRC.


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