137 citations · 143 across the 6 of their papers we have counts for
6 papers
Extracting and Analyzing Context Information in User-Support Conversations on Twitter
Daniel Martens, Walid Maalej
While many apps include built-in options to report bugs or request features, users still provide an increasing amount of feedback via social media, like Twitter. Compared to tradit…
Release early, release often, and watch your users' emotions
Daniel Martens, Walid Maalej
App stores are highly competitive markets, sometimes offering dozens of apps for a single use case. Unexpected app changes such as a feature removal might incite even loyal users t…
Towards Understanding and Detecting Fake Reviews in App Stores
Daniel Martens, Walid Maalej
App stores include an increasing amount of user feedback in form of app ratings and reviews. Research and recently also tool vendors have proposed analytics and data mining solutio…
A Simple NLP-based Approach to Support Onboarding and Retention in Open Source Communities
Christoph Stanik, Lloyd Montgomery, Daniel Martens +2
Successful open source communities are constantly looking for new members and helping them become active developers. A common approach for developer onboarding in open source proje…
ReviewChain: Untampered Product Reviews on the Blockchain
Daniel Martens, Walid Maalej
Online portals include an increasing amount of user feedback in form of ratings and reviews. Recent research highlighted the importance of this feedback and confirmed that positive…
On the Emotion of Users in App Reviews
Daniel Martens, Timo Johann
App store analysis has become an important discipline in recent software engineering research. It empirically studies apps using information mined from their distribution platforms…