Analysing Developers Affectiveness through Markov chain Models

In this paper, we present an analysis of more than 500K comments from open-source repositories of software systems. Our aim is to empirically determine how developers interact with each other under certain psychological conditions generated by politeness, sentiment and emotion expressed in developers' comments. Developers involved in open-source projects do not usually know each other; they mainly communicate through mailing lists, chat rooms, and tools such as issue tracking systems. The way in which they communicate affects the development process and the productivity of the people involved in the project. We evaluated politeness, sentiment, and emotions of comments posted by developers and studied the communication flow to understand how they interacted in the presence of impolite and negative comments (and vice versa). Our analysis shows that when in presence of impolite or negative comments, the probability of the next comment being impolite or negative is 14% and 25%, respectively; anger, however, has a probability of 40% of being followed by a further anger comment. The result could help managers take control the development phases of a system since social aspects can seriously affect a developer's productivity. In a distributed environment this may have a particular resonance.

• Publication year

  2018

• Venue

  arXiv.org

• Publication date

  2018-03-17

• Fields of study

  Computer Science, Psychology

• Identifiers
  arXiv 1803.06502
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• POLITICAL DISCOURSE CONTENT ANALYSIS: A CRITICAL OVERVIEW OF A COMPUTERIZED TEXT ANALYSIS PROGRAM LINGUISTIC INQUIRY AND WORD COUNT (LIWC)

  2020cited by this paper
• How diverse is your team? Investigating gender and nationality diversity in GitHub teams

  2017cited by this paper
• On the randomness and seasonality of affective metrics for software development

  2017cited by this paper
• Arsonists or Firefighters? Affectiveness in Agile Software Development

  2016cited by this paper
• Software development: do good manners matter?

  2016influential reference
• Mining Valence, Arousal, and Dominance - Possibilities for Detecting Burnout and Productivity?

  2016cited by this paper
• Easier contagion and weaker ties make anger spread faster than joy in social media

  2016cited by this paper
• The Emotional Side of Software Developers in JIRA

  2016cited by this paper
• Исследование влияния пола и психологических характеристик автора на количественные параметры его текста с использованием программы Linguistic Inquiry and Word Count

  2015cited by this paper
• Measuring and Understanding the Effectiveness of JIRA Developers Communities

  2015cited by this paper
• Understanding the affect of developers: theoretical background and guidelines for psychoempirical software engineering

  2015cited by this paper
• The JIRA Repository Dataset: Understanding Social Aspects of Software Development

  2015influential reference
• Would you mind fixing this issue? - An Empirical Analysis of Politeness and Attractiveness in Software Developed Using Agile Boards

  2015influential reference
• Choosing your weapons: On sentiment analysis tools for software engineering research

  2015cited by this paper
• Social Barriers Faced by Newcomers Placing Their First Contribution in Open Source Software Projects

  2015cited by this paper
• The challenges of sentiment detection in the social programmer ecosystem

  2015cited by this paper
• Quantifying the effect of sentiment on information diffusion in social media

  2015cited by this paper
• Are Bullies More Productive? Empirical Study of Affectiveness vs. Issue Fixing Time

  2015influential reference
• Behavioral software engineering: A definition and systematic literature review

  2015cited by this paper
• Bug report, feature request, or simply praise? On automatically classifying app reviews

  2015cited by this paper
• How can i improve my app? Classifying user reviews for software maintenance and evolution

  2015cited by this paper
• Sentiment Analysis in monitoring software development processes: An exploratory case study on GitHub's project issues

  2015cited by this paper
• Sentiment analysis of commit comments in GitHub: an empirical study

  2014cited by this paper
• Security and emotion: sentiment analysis of security discussions on GitHub

  2014cited by this paper
• Towards discovering the role of emotions in stack overflow

  2014cited by this paper
• Happy software developers solve problems better: psychological measurements in empirical software engineering

  2014cited by this paper
• Monitoring sentiment in open source mailing lists: exploratory study on the apache ecosystem

  2014cited by this paper
• Experimental evidence of massive-scale emotional contagion through social networks

  2014cited by this paper
• Let's talk about it: evaluating contributions through discussion in GitHub

  2014cited by this paper
• SENTIMENT ANALYSIS OF FREE/OPEN SOURCE DEVELOPERS: PRELIMINARY FINDINGS FROM A CASE STUDY

  2014cited by this paper
• Do developers feel emotions? an exploratory analysis of emotions in software artifacts

  2014influential reference
• How Do Users Like This Feature? A Fine Grained Sentiment Analysis of App Reviews

  2014cited by this paper
• The Role of Emotions in Contributors Activity: A Case Study on the GENTOO Community

  2013cited by this paper
• A computational approach to politeness with application to social factors

  2013influential reference
• On the Personality Traits of StackOverflow Users

  2013cited by this paper
• Micro Patterns in Agile Software

  2013cited by this paper
• How Does the Extraversion of Software Development Teams Influence Team Satisfaction and Software Quality?: A Controlled Experiment

  2012cited by this paper
• Micro Pattern Fault-Proneness

  2012cited by this paper
• An analysis of anti-micro-patterns effects on fault-proneness in large Java systems

  2012cited by this paper
• HMM modeling of user engagement in advice-giving dialogues

  2010cited by this paper
• The Effects of Extrinsic Motivations and Satisfaction in Open Source Software Development

  2010cited by this paper
• Dynamic spread of happiness in a large social network: longitudinal analysis over 20 years in the Framingham Heart Study

  2008cited by this paper
• Beanplot: A Boxplot Alternative for Visual Comparison of Distributions

  2008cited by this paper
• Towards individualized software engineering: empirical studies should collect psychometrics

  2008cited by this paper
• What Can OSS Mailing Lists Tell Us? A Preliminary Psychometric Text Analysis of the Apache Developer Mailing List

  2007cited by this paper
• Linguistic Inquiry and Word Count (LIWC2007)

  2007cited by this paper
• A two dimensional annotation scheme for emotion in dialogue

  2004cited by this paper
• Managing Psychological Factors in Information Systems Work: An Orientation to Emotional Intelligence

  2003cited by this paper
• Organizational behavior: affect in the workplace.

  2002cited by this paper
• The influence of positive affect on the components of expectancy motivation.

  2002cited by this paper
• On the universality and cultural specificity of emotion recognition: a meta-analysis.

  2002cited by this paper
• Manifesto for Agile Software Development

  2001cited by this paper
• The statistical evaluation of social network dynamics

  2001cited by this paper
• Spoken dialogue system using corpus-based hidden Markov model

  1998cited by this paper
• An argument for basic emotions

  1992cited by this paper

• No citing papers are available for this paper.