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App Review Analysis

Since 2009, we have been conducting a series of studies and projects on app store analysis and app data analytics. This work has led to several tools and papers published in top venues or currently being under review. More information about the studies and the papers can be found below.

Extracting and Analyzing Context Information in User-Support Conversations on Twitter

Project summary

This project was conducted by Daniel Martens and Walid Maalej in the period from January 2019 to April 2019.

Project Data

Replication package (The replication package is available upon request for academic research, please contact ed.grubmah-inu.kitamrofninull@snetram)

On Fake App Reviews

Project summary

This project was conducted by Daniel Martens and Walid Maalej in the period from March 2017 to July 2018.

Project Data

Replication package (The replication package is available upon request for academic research, please contact ed.grubmah-inu.kitamrofninull@snetram)

Mining User Rationale from Software Reviews

Project Summary

This page includes preliminary information about the scientific study of University of Hamburg: mining user rationale from software reviews. The study was conducted by Zijad Kurtanović and Walid Maalej between Winter 2014 and Summer 2016.

Project Data

The study resulted in a scientific paper, that is currently being reviewed for the 25th IEEE International Requirements Engineering Conference (RE’17) that will be held in Lisbon, Portugal, from the 4th to the 8th of September, 2017.

On the Emotion of Users in App Reviews

Project summary

This project was conducted by Daniel Martens and Timo Johann in the period from December 2016 to January 2017.

Project Data

Data Set (The data set is available upon request for academic research, please contact ed.grubmah-inu.kitamrofninull@snetram)

On the automatic classification of app reviews

Project summary

This project was conducted by Walid Maleej, Zijad Kurtanović, Hadeer Nabil, and Christoph Stanik between November 2015 and March 2016. It has led to a paper for the special issue of the Requirements Engineering Journal. The paper extends the previous work of Walid Maalej and Hadeer Nabil published at the International IEEE Requirements Engineering Conference 2015.

Project Data

Source Code

Data

Acknowledgement

We thank D. Pagano for his support with the data collection, M. Häring for contributing to the development of the coding tool, as well as the RE15 reviewers, M. Nagappan, and T. Johann for the comments on the paper. This work was partly supported by Microsoft Research (SEIF Award 2014).

Bug Report, Feature Request, or Just a Rating? On Automatically Classifying App Reviews

Project summary

This project was conducted by Walid Maleej and Hadeer Nabil between summer 2014 and summer 2015. It has led to a master thesis and a paper that is currently under review in the IEEE International Conference on Requirements Engineering.

Project Data

  1. Data and Coding Guide 
  2. Results
  3. Source Code

Acknowledgement

We thank C. Stanik and D. Pagano for their support with the data collection and the feedback, M. Haering for contributing to development of the coding tool. This work is supported in part by the Microsoft Research Grant (SEIF-2014).

How Do Users Like this Feature? A Fine Grained Sentiment Analysis of App Reviews

Project Summary

This project was conducted with Emitza Guzman and Walid Maalej between Summer 2012 and Spring 2014.

Project Data

  1. Coding guide
  2. Coding tool
  3. Reviews and analysis database including the trough set.

The project resulted in a scientific paper, which was published at the IEEE International Conference on Requirement Engineering.

Acknowledgement

We thank Christoph Stanik for his support with the Google Play API, and Ghadeer Eresha, Safey Halim, Mathias Ellmann, Marlo Häring, Hoda Naguib, and Wolf Posdorfer for their support in the study.This work was partially supported by the Mexican Council of Science and Technology (Conacyt).

SAFE: A Simple Approach for Feature Extraction from App Descriptions and App Reviews

Project Summary

This project was conducted with Timo Johann, Christoph Stanik, Alireza M. Alizadeh B. and Walid Maalej in 2016 and the beginning of 2017.

Project Data

In case you are interested in the scripts or data used please contact Prof. Dr. Walid Maalej or Timo Johann. In your request, we kindly ask you to specify what data you exactly need and which data format you prefer (json, mongodump, or csv).

The project resulted in a scientific paper, which was published at the IEEE International Conference on Requirement Engineering.

Acknowledgement

This research is part of the OPENREQ project, funded by the Horizon 2020 program of the European Union. Project Id: 732463.

A Simple NLP-based Approach to Support Onboarding and Retention in Open Source Communities

Project Summary

This project was conducted with Christoph Stanik, Lloyd Montgomery, Daniel Martens, Davide Fucci and Walid Maalej in 2018.

In case you want to re-produce or follow up on the study consider to use our replication package.

The project resulted in a scientific paper, which will be published at the 34th IEEE International Conference on Software Maintenance and Evolution (ICSME).

Acknowledgement

This research is part of the OPENREQ project, funded by the Horizon 2020 program of the European Union. Project Id: 732463.