Sentiment analysis tools in software engineering: A systematic map** study
Context: Software development is a collaborative task. Previous research has shown social
aspects within development teams to be highly relevant for the success of software projects …
aspects within development teams to be highly relevant for the success of software projects …
[HTML][HTML] Burnout in software engineering: A systematic map** study
Context: Burnout is a work-related syndrome that, similar to many occupations, influences
most software developers. For decades, studies in software engineering (SE) have explored …
most software developers. For decades, studies in software engineering (SE) have explored …
MAAT: a novel ensemble approach to addressing fairness and performance bugs for machine learning software
Machine Learning (ML) software can lead to unfair and unethical decisions, making software
fairness bugs an increasingly significant concern for software engineers. However …
fairness bugs an increasingly significant concern for software engineers. However …
A comprehensive empirical study of bias mitigation methods for machine learning classifiers
Software bias is an increasingly important operational concern for software engineers. We
present a large-scale, comprehensive empirical study of 17 representative bias mitigation …
present a large-scale, comprehensive empirical study of 17 representative bias mitigation …
Tourism forecasting with granular sentiment analysis
Generic sentiment calculations cannot fully reflect tourists' preferences, whereas fine-
grained sentiment analysis identifies tourists' precise attitudes. This study forecasted visitor …
grained sentiment analysis identifies tourists' precise attitudes. This study forecasted visitor …
An empirical study on deployment faults of deep learning based mobile applications
Deep learning (DL) is moving its step into a growing number of mobile software applications.
These software applications, named as DL based mobile applications (abbreviated as …
These software applications, named as DL based mobile applications (abbreviated as …
An analysis of cognitive change in online mental health communities: A textual data analysis based on post replies of support seekers
The replies of people seeking support in online mental health communities can be analyzed
to discover if they feel better after receiving support; feeling better indicates a cognitive …
to discover if they feel better after receiving support; feeling better indicates a cognitive …
An exploratory and automated study of sarcasm detection and classification in app stores using fine-tuned deep learning classifiers
App stores enable users to provide insightful feedback on apps, which developers can use
for future software application enhancement and evolution. However, finding user reviews …
for future software application enhancement and evolution. However, finding user reviews …
Machine learning techniques for emotion detection and sentiment analysis: current state, challenges, and future directions
Emotion detection and Sentiment analysis techniques are used to understand polarity or
emotions expressed by people in many cases, especially during interactive systems use …
emotions expressed by people in many cases, especially during interactive systems use …
Comprehensive review and comparative analysis of transformer models in sentiment analysis
Sentiment analysis has become an important task in natural language processing because it
is used in many different areas. This paper gives a detailed review of sentiment analysis …
is used in many different areas. This paper gives a detailed review of sentiment analysis …