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Background: Experiment-driven development with the help of real usage data helps to build software products and services that are of high value to their users. As more software companies use experimentation in their development practises, ethical concerns are increasingly important. Objective: There is a need for understanding the ethical issues companies must take into account when practising experimentation...
Background: Online forums are instruments through which information or problems are shared and discussed, including expressions of interests and intentions. Objective: In this paper, we present ongoing work aimed at analyzing the content of forum posts of a hybrid open source company that offers both free and commercial licenses, in order to help its community manager gain improved understanding of...
Software development in highly dynamic environments imposes high risks to development organizations. One such risk is that the developed software may be of only little or no value to customers, wasting the invested development efforts. Continuous experimentation, as an experiment-driven development approach, may reduce such development risks by iteratively testing product and service assumptions that...
The current paper explores the use of the social network platform Facebook, as a source of emotion annotated textual data as well as a source of annotators. The traditional approach of hiring experts to provide manually labeled (annotated) data for NLP research is time-consuming, tedious and expensive. Hence, crowdsourcing has emerged as a useful method for obtaining annotated data for natural language...
We report on experiments that demonstrate the relevance of our AntiSocial Behavior (ASB) corpus as a machine learning resource to detect antisocial behavior from text. We first describe the corpus and then, by using the corpus for training machine learning algorithms, we build a set of binary classifiers. Experimental evaluations revealed that classifiers built based on the ASB corpus produce reliable...
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