How to Ask for Technical Help? Evidence-based Guidelines for Writing Questions on Stack Overflow

Context: The success of Stack Overflow and other community-based question-and-answer (Q&A) sites depends mainly on the will of their members to answer others' questions. In fact, when formulating requests on Q&A sites, we are not simply seeking for information. Instead, we are also asking for other people's help and feedback. Understanding the dynamics of the participation in Q&A communities is essential to improve the value of crowdsourced knowledge. Objective: In this paper, we investigate how information seekers can increase the chance of eliciting a successful answer to their questions on Stack Overflow by focusing on the following actionable factors: affect, presentation quality, and time. Method: We develop a conceptual framework of factors potentially influencing the success of questions in Stack Overflow. We quantitatively analyze a set of over 87K questions from the official Stack Overflow dump to assess the impact of actionable factors on the success of technical requests. The information seeker reputation is included as a control factor. Furthermore, to understand the role played by affective states in the success of questions, we qualitatively analyze questions containing positive and negative emotions. Finally, a survey is conducted to understand how Stack Overflow users perceive the guideline suggestions for writing questions. Results: We found that regardless of user reputation, successful questions are short, contain code snippets, and do not abuse with uppercase characters. As regards affect, successful questions adopt a neutral emotional style. Conclusion: We provide evidence-based guidelines for writing effective questions on Stack Overflow that software engineers can follow to increase the chance of getting technical help. As for the role of affect, we empirically confirmed community guidelines that suggest avoiding rudeness in question writing.Comment: Preprint, to appear in Information and Software Technolog

Emotion Detection Using Noninvasive Low Cost Sensors

Emotion recognition from biometrics is relevant to a wide range of application domains, including healthcare. Existing approaches usually adopt multi-electrodes sensors that could be expensive or uncomfortable to be used in real-life situations. In this study, we investigate whether we can reliably recognize high vs. low emotional valence and arousal by relying on noninvasive low cost EEG, EMG, and GSR sensors. We report the results of an empirical study involving 19 subjects. We achieve state-of-the- art classification performance for both valence and arousal even in a cross-subject classification setting, which eliminates the need for individual training and tuning of classification models.Comment: To appear in Proceedings of ACII 2017, the Seventh International Conference on Affective Computing and Intelligent Interaction, San Antonio, TX, USA, Oct. 23-26, 201

EmoTxt: A Toolkit for Emotion Recognition from Text

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.Comment: In Proc. 7th Affective Computing and Intelligent Interaction (ACII'17), San Antonio, TX, USA, Oct. 23-26, 2017, p. 79-80, ISBN: 978-1-5386-0563-

Pre-diabetes and sympathetic nervous system mediated microvascular dysregulation in skeletal muscle

Pre-diabetes is associated with impairments in cardiovascular health that manifest prior to the onset of overt type 2 diabetes. Characterized by hyperinsulinemia and insulin resistance, pre-diabetes has been associated with increases in sympathetic nerve activity, which may result in augmented sympathetic control of the peripheral vasculature within skeletal muscle. Currently however, there are no studies investigating the impact of pre-diabetes on sympathetically-mediated vascular control. The primary study of this thesis investigated the effects of pre-diabetes on baseline sympathetic neuropeptide Y Y1 receptor (NPY Y1R) and alpha 1 adrenergic receptor (a1R) control of hindlimb vascular tone. Experiments were carried out in anesthetized pre-diabetic Zucker Diabetic Fatty (ZDF) rats and control lean ZDF rats during drug delivery of sympathetic antagonists while measuring femoral artery blood flow (Qfem) and calculated vascular conductance (VC). Despite similar baseline Qfem and VC, Y1R, a1R and dual Y1R+a1R blockade (via BIBP3226 and prazosin) elicited increases in Qfem and VC that were greater in pre-diabetic rats compared to controls, demonstrating heightened Y1R and a1R control of baseline vascular tone. These results were also supported by increased Y1R, a1R and NPY expression in hindlimb tissue of pre-diabetic rats. In effort to determine whether pre-diabetes effects microvascular network function in contracting skeletal muscle, intravital microscopy was used to evaluate arteriolar rapid onset vasodilation (ROV) and steady-state vasodilation and blood flow responses to tetanic and rhythmic contraction of the gluteus maximus muscle in pre-diabetic (The Pound Mouse, c57bl6 background) and control mice (c57bl6). Baseline diameter and blood flow of arterioles were similar between groups; however, contraction-evoked vasodilatory and blood flow responses were blunted in pre-diabetic compared to control mice. In addition, the magnitude of contraction-evoked dilation was greater in distal arterioles compared to proximal arterioles in GM arteriolar networks of control mice; however, such spatially-dependent differences in contraction-evoked dilation was disrupted in pre-diabetic mice. Blockade of Y1R and a1R (via BIBP3226 and prazosin) restored ROV and steady-state vasodilation to tetanic and rhythmic contractions in pre-diabetic mice to levels similar to controls. Blockade of arteriolar sympathetic receptors also restored dilatory magnitude of distal arterioles in pre-diabetic mice. In conclusion, the results presented in this dissertation provide evidence that peripheral arteriolar Y1R and a1R activation are enhanced in pre-diabetes, resulting in augmented sympathetic modulation of basal skeletal muscle blood flow and VC, as well as deficits in arteriolar vasodilation to skeletal muscle contraction

The Role of Social Media in Affective Trust Building in Customer-Supplier Relationships

Trust represents a key issue in building successful customer-supplier relationships. In this sense, social software represents a powerful means for fostering trust by establishing a direct, more personal communication channel with customers. Therefore, companies are now investing in so-cial media for building their social digital brand and strengthening relationships with their cus-tomers. In this paper, we presented two experiments by means of which we investigated the role of traditional websites and social media in trust building along the cognitive and affective di-mensions. We hypothesize that traditional websites (content-oriented) and social media (interac-tion-oriented) may have a different effect on trust building in customer-supplier relationships, based on the first impression provided to potential customers. Although additional research is still needed, our findings add to the existing body of evidence that both cognitive and affective trust can be successfully fostered through online presence. Specifically, social media provides companies with tools to communicate benevolence to potential customer and, therefore, foster the affective commitment of customers. Traditional websites, instead, are more appropriate for communicating the competence and reliability of a company, by fostering trust building along the cognitive dimension. The results of our studies provide implications for researchers and practi-tioners, by highlighting the importance of combining the two media for effectively building a trustworthy online company image

A Gold Standard for Emotion Annotation in Stack Overflow

Software developers experience and share a wide range of emotions throughout a rich ecosystem of communication channels. A recent trend that has emerged in empirical software engineering studies is leveraging sentiment analysis of developers' communication traces. We release a dataset of 4,800 questions, answers, and comments from Stack Overflow, manually annotated for emotions. Our dataset contributes to the building of a shared corpus of annotated resources to support research on emotion awareness in software development.Comment: To appear in Proceedings of the 15th International Conference on Mining Software Repositories (MSR '18) Data Showcase Track, 28-29 May, Gothenburg, Swede

Recognizing Developers' Emotions while Programming

Developers experience a wide range of emotions during programming tasks, which may have an impact on job performance. In this paper, we present an empirical study aimed at (i) investigating the link between emotion and progress, (ii) understanding the triggers for developers' emotions and the strategies to deal with negative ones, (iii) identifying the minimal set of non-invasive biometric sensors for emotion recognition during programming task. Results confirm previous findings about the relation between emotions and perceived productivity. Furthermore, we show that developers' emotions can be reliably recognized using only a wristband capturing the electrodermal activity and heart-related metrics.Comment: Accepted for publication at ICSE2020 Technical Trac

Assessment of Off-the-Shelf SE-specific Sentiment Analysis Tools: An Extended Replication Study

Sentiment analysis methods have become popular for investigating human communication, including discussions related to software projects. Since general-purpose sentiment analysis tools do not fit well with the information exchanged by software developers, new tools, specific for software engineering (SE), have been developed. We investigate to what extent SE-specific tools for sentiment analysis mitigate the threats to conclusion validity of empirical studies in software engineering, highlighted by previous research. First, we replicate two studies addressing the role of sentiment in security discussions on GitHub and in question-writing on Stack Overflow. Then, we extend the previous studies by assessing to what extent the tools agree with each other and with the manual annotation on a gold standard of 600 documents. We find that different SE-specific sentiment analysis tools might lead to contradictory results at a fine-grain level, when used 'off-the-shelf'. Conversely, platform-specific tuning or retraining might be needed to take into account differences in platform conventions, jargon, or document lengths.Comment: Accepted for publication in Empirical Software Engineerin