Related papers: Exploring Indicators of Developers' Sentiment Perceptions in Student Software Projects

Exploring Indicators of Developers' Sentiment Perceptions in Student Software Projects

URL: http://arxiv.org/abs/2603.10864v1
Date: Wed, 11 Mar 2026 15:16:58 GMT
Title: Exploring Indicators of Developers' Sentiment Perceptions in Student Software Projects
Abstract summary: This paper investigates how mood traits and states, life circumstances, project phases, and group dynamics relate to the perception of text-based messages in software development.<n>We conducted a four-round survey study with 81 students in team-based software projects.
Score: 2.396425778177418
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Abstract: Communication is a crucial social factor in the success of software projects, as positively or negatively perceived statements can influence how recipients feel and affect team collaboration through emotional contagion. Whether a developer perceives a written message as positive, negative, or neutral is likely shaped by multiple factors. In this paper, we investigate how mood traits and states, life circumstances, project phases, and group dynamics relate to the perception of text-based messages in software development. We conducted a four-round survey study with 81 students in team-based software projects. Across rounds, participants reported these factors and labeled 30 decontextualized statements for sentiment, including meta-data on labeling rationale and uncertainty. Our results show: (1) Sentiment perception is only moderately stable within individuals, and label changes concentrate on ambiguity-prone statements; (2) Correlation-level signals are small and do not survive global multiple-testing correction; (3) In statement-level repeated-measures models (GEE), higher mood trait and reactivity are associated with more positive (and less neutral) labeling, while predictors of negative labeling are weaker and at most trend-level (e.g., task conflict); (4) We find no clear evidence of systematic project-phase effects. Overall, sentiment perception varies within persons and is strongly statement-dependent. Although our study was conducted in an academic setting, the observed variability and ambiguity effects suggest caution when interpreting sentiment analysis outputs and motivate future work with contextualized, in-project communication.

Related papers

Switchboard-Affect: Emotion Perception Labels from Conversational Speech [7.576840738395629]
We identify the Switchboard corpus as a promising source of naturalistic conversational speech.<n>We train a crowd to label the dataset for categorical emotions and dimensional attributes.<n>We evaluate state-of-the-art SER models and find variable performance across the emotion categories with especially poor generalization.
arXiv Detail & Related papers (2025-10-14T21:23:04Z)
Vibe Check: Understanding the Effects of LLM-Based Conversational Agents' Personality and Alignment on User Perceptions in Goal-Oriented Tasks [2.1117030125341385]
Large language models (LLMs) enable conversational agents (CAs) to express distinctive personalities.<n>This study investigates how personality expression levels and user-agent personality alignment influence perceptions in goal-oriented tasks.
arXiv Detail & Related papers (2025-09-11T21:43:49Z)
The Personality Illusion: Revealing Dissociation Between Self-Reports & Behavior in LLMs [60.15472325639723]
Personality traits have long been studied as predictors of human behavior.<n>Recent advances in Large Language Models (LLMs) suggest similar patterns may emerge in artificial systems.
arXiv Detail & Related papers (2025-09-03T21:27:10Z)
Sentient Agent as a Judge: Evaluating Higher-Order Social Cognition in Large Language Models [75.85319609088354]
Sentient Agent as a Judge (SAGE) is an evaluation framework for large language models.<n>SAGE instantiates a Sentient Agent that simulates human-like emotional changes and inner thoughts during interaction.<n>SAGE provides a principled, scalable and interpretable tool for tracking progress toward genuinely empathetic and socially adept language agents.
arXiv Detail & Related papers (2025-05-01T19:06:10Z)
Modeling Communication Perception in Development Teams Using Monte Carlo Methods [1.8369669715149237]
Mood surveys enable the early detection of underlying tensions or dissatisfaction within development teams.<n>This paper analyzes the diversity of perceptions within arbitrary development teams.<n>We present a preliminary mathematical model to calculate the minimum agreement among a subset of developers.
arXiv Detail & Related papers (2025-04-24T14:35:18Z)
Evaluating Large Language Models with Psychometrics [59.821829073478376]
This paper offers a comprehensive benchmark for quantifying psychological constructs of Large Language Models (LLMs)<n>Our work identifies five key psychological constructs -- personality, values, emotional intelligence, theory of mind, and self-efficacy -- assessed through a suite of 13 datasets.<n>We uncover significant discrepancies between LLMs' self-reported traits and their response patterns in real-world scenarios, revealing complexities in their behaviors.
arXiv Detail & Related papers (2024-06-25T16:09:08Z)
Characterising Developer Sentiment in Software Components: An Exploratory Study of Gentoo [6.253919624802852]
Collaborative software development happens in teams, that cooperate on shared artefacts, and discuss development on online platforms. Previous research has shown how communication between team members, especially in an open-source environment, can become extremely toxic. Our study shows that, in recent years, negative emotions have generally decreased in the communication between Gentoo developers.
arXiv Detail & Related papers (2024-05-27T09:22:47Z)
Overwhelmed software developers: An Interpretative Phenomenological Analysis [43.18707677931078]
We interviewed two software developers who have experienced overwhelm recently. We uncover seven categories of overwhelm (communication, disturbance, organizational, variety, technical, temporal, and positive overwhelm) Participants reported that overwhelm can sometimes be experienced to be positive and pleasant, and it can increase their mental focus, self ambition, and productivity.
arXiv Detail & Related papers (2024-01-05T12:39:08Z)
How are Prompts Different in Terms of Sensitivity? [50.67313477651395]
We present a comprehensive prompt analysis based on the sensitivity of a function. We use gradient-based saliency scores to empirically demonstrate how different prompts affect the relevance of input tokens to the output. We introduce sensitivity-aware decoding which incorporates sensitivity estimation as a penalty term in the standard greedy decoding.
arXiv Detail & Related papers (2023-11-13T10:52:01Z)
Measuring the Effect of Influential Messages on Varying Personas [67.1149173905004]
We present a new task, Response Forecasting on Personas for News Media, to estimate the response a persona might have upon seeing a news message. The proposed task not only introduces personalization in the modeling but also predicts the sentiment polarity and intensity of each response. This enables more accurate and comprehensive inference on the mental state of the persona.
arXiv Detail & Related papers (2023-05-25T21:01:00Z)
Co-Located Human-Human Interaction Analysis using Nonverbal Cues: A Survey [71.43956423427397]
We aim to identify the nonverbal cues and computational methodologies resulting in effective performance. This survey differs from its counterparts by involving the widest spectrum of social phenomena and interaction settings. Some major observations are: the most often used nonverbal cue, computational method, interaction environment, and sensing approach are speaking activity, support vector machines, and meetings composed of 3-4 persons equipped with microphones and cameras, respectively.
arXiv Detail & Related papers (2022-07-20T13:37:57Z)

This list is automatically generated from the titles and abstracts of the papers in this site.