activity
20202022
most citedCorona-Warn-App: Tracing the Start of the Official COVID-19 Exposure Notification App for Germany

13 citations · 27 across the 6 of their papers we have counts for

collaborators

6 papers

cs.SI20221 cited

Characterizing the country-wide adoption and evolution of the Jodel messaging app in Saudi Arabia

Jens Helge Reelfs, Oliver Hohlfeld, Markus Strohmaier +1

Social media is subject to constant growth and evolution, yet little is known about their early phases of adoption. To shed light on this aspect, this paper empirically characteriz…

cs.SI20222 cited

Anonymous Hyperlocal Communities: What do they talk about?

Jens Helge Reelfs, Oliver Hohlfeld, Niklas Henckell

In this paper, we study what users talk about in a plethora of independent hyperlocal and anonymous online communities in a single country: Saudi Arabia (KSA). We base this perspec…

cs.SI20221 cited

Differences in Social Media Usage Exist Between Western and Middle-East Countries

Jens Helge Reelfs, Oliver Hohlfeld, Niklas Henckell

In this paper, we empirically analyze two examples of a Western (DE) versus Middle-East (SA) Online Social Messaging App. By focusing on the system interactions over time in compar…

cs.SI20218 cited

Understanding & Predicting User Lifetime with Machine Learning in an Anonymous Location-Based Social Network

Jens Helge Reelfs, Max Bergmann, Oliver Hohlfeld +1

In this work, we predict the user lifetime within the anonymous and location-based social network Jodel in the Kingdom of Saudi Arabia. Jodel's location-based nature yields to the…

cs.CY202013 cited

Corona-Warn-App: Tracing the Start of the Official COVID-19 Exposure Notification App for Germany

Jens Helge Reelfs, Oliver Hohlfeld, Ingmar Poese

On June 16, 2020, Germany launched an open-source smartphone contact tracing app ("Corona-Warn-App") to help tracing SARS-CoV-2 (coronavirus) infection chains. It uses a decentrali…

cs.CL20202 cited

Word-Emoji Embeddings from large scale Messaging Data reflect real-world Semantic Associations of Expressive Icons

Jens Helge Reelfs, Oliver Hohlfeld, Markus Strohmaier +1

We train word-emoji embeddings on large scale messaging data obtained from the Jodel online social network. Our data set contains more than 40 million sentences, of which 11 millio…