Showing papers by "Fabio Calefato published in 2017"
01 Oct 2017
TL;DR: EmoTxt as discussed by the authors is a toolkit for emotion recognition from text, trained and tested on a gold standard of about 9K question, answers, and comments from online interactions.
Abstract: We present EmoTxt, a toolkit for emotion recognition from text, trained and tested on a gold standard of about 9K question, answers, and comments from online interactions. We provide empirical evidence of the performance of EmoTxt. To the best of our knowledge, EmoTxt is the first open-source toolkit supporting both emotion recognition from text and training of custom emotion classification models.
102 citations
20 May 2017
TL;DR: A preliminary, quantitative analysis on how the propensity to trust affects the success of collaborations in a distributed project, where the success is represented by pull requests whose code changes and contributions are successfully merged in the project's repository.
Abstract: Establishing trust between developers working at distant sites facilitates team collaboration in distributed software development. While previous research has focused on how to build and spread trust in absence of direct, face-to-face communication, it has overlooked the effects of the propensity to trust, i.e., the trait of personality representing the individual disposition to perceive the others as trustworthy. In this study, we present a preliminary, quantitative analysis on how the propensity to trust affects the success of collaborations in a distributed project, where the success is represented by pull requests whose code changes and contributions are successfully merged into the project's repository.
37 citations
Posted Content•
TL;DR: EmoTxt as discussed by the authors is a toolkit for emotion recognition from text, trained and tested on a gold standard of about 9K question, answers, and comments from online interactions.
Abstract: We present EmoTxt, a toolkit for emotion recognition from text, trained and tested on a gold standard of about 9K question, answers, and comments from online interactions. We provide empirical evidence of the performance of EmoTxt. To the best of our knowledge, EmoTxt is the first open-source toolkit supporting both emotion recognition from text and training of custom emotion classification models.
12 citations
TL;DR: In this article, the authors present a preliminary, quantitative analysis on how the propensity to trust affects the success of collaborations in a distributed project, where the success is represented by pull requests whose code changes and contributions are successfully merged into the project's repository.
Abstract: Establishing trust between developers working at distant sites facilitates team collaboration in distributed software development. While previous research has focused on how to build and spread trust in absence of direct, face-to-face communication, it has overlooked the effects of the propensity to trust, i.e., the trait of personality representing the individual disposition to perceive the others as trustworthy. In this study, we present a preliminary, quantitative analysis on how the propensity to trust affects the success of collaborations in a distributed project, where the success is represented by pull requests whose code changes and contributions are successfully merged into the project's repository.
9 citations
TL;DR: In this paper, the authors present a study on creative collaboration in a music community where authors write songs together by "overdubbing," that is, by mixing a new track with an existing audio recording.
Abstract: Online communities have been able to develop large, open-source software (OSS) projects like Linux and Firefox throughout the successful collaborations carried out by their members over the Internet. However, online communities also involve creative arts domains such as animation, video games, and music. Despite their growing popularity, the factors that lead to successful collaborations in these communities are not entirely understood. In this paper, we present a study on creative collaboration in a music community where authors write songs together by 'overdubbing,' that is, by mixing a new track with an existing audio recording. We analyzed the relationship between song- and author-related measures and the likelihood of a song being overdubbed. We found that recent songs, as well as songs with many reactions, are more likely to be overdubbed; authors with a high status in the community and a recognizable identity write songs that the community tends to build upon.
3 citations
TL;DR: Senti4SD as discussed by the authors is a classifier specifically trained to support sentiment analysis in developers' communication channels, which is trained and validated using a gold standard of Stack Overflow questions, answers, and comments manually annotated for sentiment polarity.
Abstract: The role of sentiment analysis is increasingly emerging to study software developers' emotions by mining crowd-generated content within social software engineering tools. However, off-the-shelf sentiment analysis tools have been trained on non-technical domains and general-purpose social media, thus resulting in misclassifications of technical jargon and problem reports. Here, we present Senti4SD, a classifier specifically trained to support sentiment analysis in developers' communication channels. Senti4SD is trained and validated using a gold standard of Stack Overflow questions, answers, and comments manually annotated for sentiment polarity. It exploits a suite of both lexicon- and keyword-based features, as well as semantic features based on word embedding. With respect to a mainstream off-the-shelf tool, which we use as a baseline, Senti4SD reduces the misclassifications of neutral and positive posts as emotionally negative. To encourage replications, we release a lab package including the classifier, the word embedding space, and the gold standard with annotation guidelines.
3 citations
05 Jun 2017
TL;DR: The results of a preliminary study aimed at mining the communication network of a music community for collaborative songwriting, where users collaborate online by first uploading new songs and then by adding new tracks and providing feedback in forms of comments are reported.
Abstract: Comments play an important role within online creative communities because they make it possible to foster the production and improvement of authors’ artifacts. We investigate how comment-based communication help shape members’ behavior within online creative communities. In this paper, we report the results of a preliminary study aimed at mining the communication network of a music community for collaborative songwriting, where users collaborate online by first uploading new songs and then by adding new tracks and providing feedback in forms of comments.
3 citations
TL;DR: In this paper, the authors investigate how comment-based communication helps shape members' behavior within online creative communities and report the results of a preliminary study aimed at mining the communication network of a music community for collaborative songwriting, where users collaborate online by uploading new songs and then adding new tracks and providing feedback in forms of comments.
Abstract: Comments play an important role within online creative communities because they make it possible to foster the production and improvement of authors' artifacts. We investigate how comment-based communication help shape members' behavior within online creative communities. In this paper, we report the results of a preliminary study aimed at mining the communication network of a music community for collaborative songwriting, where users collaborate online by first uploading new songs and then by adding new tracks and providing feedback in forms of comments.
2 citations
TL;DR: In this article, the authors present a research model showing that social communication between distant developers enables the affective appraisal of trustworthiness even from a distance, thus increasing project performance, and they focus on software projects following a pull request-based development model and approximate the overall performance of a software project with the history of successful collaborations occurring between developers.
Abstract: Trust is a factor that dramatically contributes to the success or failure of distributed software teams. We present a research model showing that social communication between distant developers enables the affective appraisal of trustworthiness even from a distance, thus increasing project performance. To overcome the limitations of self-reported data, typically questionnaires, we focus on software projects following a pull request-based development model and approximate the overall performance of a software project with the history of successful collaborations occurring between developers.
1 citations