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Geographic Differences in Social Media Interactions Exist Between Western and Middle-East Countries
(2022)
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 comparison, we identify inherent differences in user engagement. We take a deep dive and shed light onto differences in user attention shifts and showcase their structural implications to the user experience. Our main findings show that in comparison to the German counterparts, the Saudi communities prefer creating content in longer conversations, while voting more conservative.
We train word-emoji embeddings on large scale messagingdata obtained from the Jodel online social network. Our dataset contains more than 40 million sentences, of which 11 million sentences are annotated with a subset of the Unicode13.0 standard Emoji list. We explore semantic emoji associations contained in this embedding by analyzing associations between emojis, between emojis and text, and betweentext and emojis. Our investigations demonstrate anecdotallythat word-emoji embeddings trained on large scale messaging data can reflect real-world semantic associations. To enable further research we release the Jodel Emoji EmbeddingDataset (JEED1488) containing 1488 emojis and their embeddings along 300 dimensions.
We study the extent to which emoji can be used to add interpretability to embeddings of text and emoji. To do so, we extend the POLAR-framework that transforms word embeddings to interpretable counterparts and apply it to word-emoji embeddings trained on four years of messaging data from the Jodel social network. We devise a crowdsourced human judgement experiment to study six usecases, evaluating against words only, what role emoji can play in adding interpretability to word embeddings. That is, we use a revised POLAR approach interpreting words and emoji with words, emoji or both according to human judgement. We find statistically significant trends demonstrating that emoji can be used to interpret other emoji very well.
Corona-Warn-App: Tracing the Start of the Official COVID-19 Exposure Notification App for Germany
(2020)
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 decentralized, privacy-preserving design based on the Exposure Notification APIs in which a centralized server is only used to distribute a list of keys of SARS-CoV-2 infected users that is fetched by the app once per day. Its success, however, depends on its adoption. In this poster, we characterize the early adoption of the app using Netflow traces captured directly at its hosting infrastructure. We show that the app generated traffic from allover Germany---already on the first day. We further observe that local COVID-19 outbreaks do not result in noticeable traffic increases.
High packet rates at ≥ 10 GBit/s challenge the packet processing performance of network stacks. A common solution is to offload (parts of) the user-space packet processing to other execution environments, e.g., into the device driver (kernel-space), the NIC or even from virtual machines into the host operating system (OS), or any combination of those. While common wisdom states that offloading optimizes performance, neither benefits nor negative effects are comprehensively studied. In this paper, we aim to shed light on the benefits and shortcomings of eBPF/XDP-based offloading from the user-space to i) the kernel-space or ii) a smart NIC-including VM virtualization. We show that offloading can indeed optimize packet processing, but only if the task is small and optimized for the target environment. Otherwise, offloading can even lead to detrimental performance.
Characterizing the country-wide adoption and evolution of the Jodel messaging app in Saudi Arabia
(2022)
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 characterizes the initial and country-wide adoption of a new type of social media in Saudi Arabia that happened in 2017. Unlike established social media, the studied network Jodel is anonymous and location-based to form hundreds of independent communities country-wide whose adoption pattern we compare. We take a
detailed and full view from the operators perspective on the temporal and geographical dimension on the evolution of these different communities—from their very first the first months of establishment to saturation. This way, we make the early adoption of a new type of social media visible, a process that is often invisible due to the lack of data covering the first days of a new network.
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 perspective on performing a content classification of the Jodel network in the KSA. To do so, we first contribute a content classification schema that assesses both the intent (why) and the topic (what) of posts. We use the schema to label 15k randomly sampled posts and further classify the top 1k hashtags. We observe a rich set of benign (yet at times controversial in conservative regimes) intents and topics that dominantly address information requests, entertainment, or dating/flirting. By comparing two large cities (Riyadh and Jeddah), we further show that hyperlocality leads to shifts in topic popularity between local communities. By evaluating votes (content appreciation) and replies (reactions), we show that the communities react differently to different topics; e.g., entertaining posts are much appreciated through votes, receiving the least replies, while beliefs & politics receive similarly few replies but are controversially voted.
Reviewing War: Unconventional User Reviews as a Side Channel to Circumvent Information Controls
(2023)
During the first days of the 2022 Russian invasion of Ukraine, Russia’s media regulator blocked access to many global social media
platforms and news sites, including Twitter, Facebook, and the
BBC. To bypass the information controls set by Russian authorities,
pro-Ukrainian groups explored unconventional ways to reach out
to the Russian population, such as posting war-related content in
the user reviews of Russian business available on Google Maps or
Tripadvisor. This paper provides a first analysis of this new phenomenon by analyzing the creative strategies to avoid state censorship.
Specifically, we analyze reviews posted on these platforms from
the beginning of the conflict to September 2022. We measure the
channeling of war messages through user reviews in Tripadvisor
and Google Maps, as well as in VK, a popular Russian social network.
Our analysis of the content posted on these services reveals
that users leveraged these platforms to seek and exchange humanitarian
and travel advice, but also to disseminate disinformation and
polarized messages. Finally, we analyze the response of platforms
in terms of content moderation and their impact.