Context Community‐based collaborative approach in open source software paradigm promotes reuse of existing software packages. There are several repositories (e.g., npm) for packages and have their own set of metrics for ranking. Objective This study explores the diversity of different popularity metrics and also the relationship between popularity metrics and development activity of the packages. Another aim is to create a package popularity index by aggregating a set of noncollinear popularity metrics. Method Using 195 K packages from different repositories, we investigated the correlation between different popularity metrics. K‐medoids algorithm helped to identify packages with different levels of popularity. Random forests method is utilized to create the package popularity index. Lastly, we used scikit‐learn implementation for determining feature importance in the model. Results Popularity metrics of the Github platform are very strongly correlated (R ≥ 0.85) for highly popular packages. Popular packages have high‐development activity. However, the number of downloads of a package does not associate with development activity. Not all the metrics are important for determining popularity of a software package. Conclusion This study provides practical guidelines to understand important metrics to determine the popularity of software packages. Researchers should focus on non‐collinear metrics, thereby avoiding similar metrics while aggregating for building models.

Open Source Software (OSS) has become ubiquitous nowadays. It is crucial for the OSS project managers as well as developers to understand users' perception of quality to remain consistent with producing good quality software. To understand users' point of view, like many studies in the commercial product/service sectors which rely upon customer reviews to understand customer behaviour, the authors' main focus is to analyse user ratings and reviews of OSS projects that may represent user satisfaction for that particular software application. We have analysed 41,428 customer reviews (obtained from SourceForge.net) of 886 most popular OSS projects belonging to a specific domain and programming language. The results indicate that overall user ratings and reviews of the popular OSS projects contain a very positive sentiment and more frequent occurrence of emotions like joy, anticipation, and trust as compared to disgust, fear, and surprise. Further, we have examined that the affectiveness of customer reviews with respect to OSS popularity and quality aspects along with their programming languages and problem domains. The results show a stronger association of review affectiveness with the number of reviews than with the number of downloads of the OSS projects, and more downloads do not mean more reviews.

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