TY - GEN A1 - Fest, Jennifer A1 - Heilmann, Arndt A1 - Hohlfeld, Oliver A1 - Neumann, Stella A1 - Reelfs, Jens Helge A1 - Schmitt, Marco A1 - Vogelgesang, Alina T1 - Determining Response-generating Contexts on Microblogging Platforms T2 - Proceedings of the 15th Conference on Natural Language Processing (KONVENS), October 9–11, 2019, Erlangen Y1 - 2019 UR - https://corpora.linguistik.uni-erlangen.de/data/konvens/proceedings/ SP - 171 EP - 182 ER - TY - GEN A1 - Hohlfeld, Oliver A1 - Krude, Johannes A1 - Reelfs, Jens Helge A1 - Rüth, Jan A1 - Wehrle, Klaus T1 - Demystifying the Performance of XDP BPF T2 - IEEE Conference on Network Softwarization, 24-28 June 2019, Paris, France N2 - 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. Y1 - 2019 UR - https://netsoft2019.ieee-netsoft.org/ U6 - https://doi.org/10.1109/NETSOFT.2019.8806651 ER - TY - GEN A1 - Reelfs, Jens Helge A1 - Mohaupt, Timon A1 - Hohlfeld, Oliver A1 - Henckell, Niklas T1 - Hashtag Usage in a Geographically-Local Microblogging App T2 - Proceedings of the 2019 World Wide Web Conference (WWW '19 Companion), 9th International Workshop on Location and the Web (LocWeb '19), May 13–17, 2019, San Francisco, CA, USA Y1 - 2019 UR - https://arxiv.org/abs/1903.04272 SN - 978-1-4503-6675-5 U6 - https://doi.org/10.1145/3308560.3316537 SP - 919 EP - 927 PB - ACM CY - New York ER - TY - GEN A1 - Reelfs, Jens Helge A1 - Hohlfeld, Oliver A1 - Poese, Ingmar T1 - Corona-Warn-App: Tracing the Start of the Official COVID-19 Exposure Notification App for Germany N2 - 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. Y1 - 2020 UR - https://conferences.sigcomm.org/sigcomm/2020/ UR - https://arxiv.org/pdf/2008.07370.pdf U6 - https://doi.org/0.1145/3405837.3411378 ER - TY - GEN A1 - Reelfs, Jens Helge A1 - Hohlfeld, Oliver A1 - Strohmaier, Markus A1 - Henckell, Niklas T1 - Word-Emoji embeddings from large scale messaging data reflect real world semantic associations of expressive icons T2 - Conference: ICWSM Workshop on Emoji Understanding and Applications in Social Media 2020 N2 - 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. Y1 - 2020 UR - http://workshop-proceedings.icwsm.org/pdf/2020_02.pdf ER - TY - GEN A1 - Reelfs, Jens Helge A1 - Bergmann, Max A1 - Hohlfeld, Oliver A1 - Henckell, Niklas T1 - Understanding & Predicting User Lifetime with Machine Learning in an Anonymous Location-Based Social Network T2 - Companion Proceedings of the Web Conference 2021 N2 - 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 establishment of disjoint communities country-wide and enables for the first time the study of user lifetime in the case of a large set of disjoint communities. A user's lifetime is an important measurement for evaluating and steering customer bases as it can be leveraged to predict churn and possibly apply suitable methods to circumvent potential user losses. We train and test off the shelf machine learning techniques with 5-fold crossvalidation to predict user lifetime as a regression and classification problem; identifying the Random Forest to provide very strong results. Discussing model complexity and quality trade-offs, we also dive deep into a time-dependent feature subset analysis, which does not work very well; Easing up the classification problem into a binary decision (lifetime longer than timespan ) enables a practical lifetime predictor with very good performance. We identify implicit similarities across community models according to strong correlations in feature importance. A single countrywide model generalizes the problem and works equally well for any tested community; the overall model internally works similar to others also indicated by its feature importances. Y1 - 2021 UR - https://arxiv.org/abs/2103.01300 SN - 978-1-4503-8313-4 U6 - https://doi.org/10.1145/3442442.3451887 VL - 2021 PB - ACM CY - Ljubljana, Slovenia ER - TY - GEN A1 - Reelfs, Jens Helge A1 - Hohlfeld, Oliver A1 - Strohmaier, Markus A1 - Henckell, Niklas T1 - Characterizing the country-wide adoption and evolution of the Jodel messaging app in Saudi Arabia T2 - arXiv N2 - 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. Y1 - 2022 UR - https://arxiv.org/abs/2205.04544 U6 - https://doi.org/10.48550/arXiv.2205.04544 ER - TY - GEN A1 - Moreno, José Miguel A1 - Pastrana, Sergio A1 - Reelfs, Jens Helge A1 - Vallina, Pelayo A1 - Panchenko, Andriy A1 - Smaragdakis, Georgios A1 - Hohlfeld, Oliver A1 - Vallina-Rodriguez, Narseo A1 - Tapiador, Juan T1 - Reviewing War: Unconventional User Reviews as a Side Channel to Circumvent Information Controls N2 - 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. KW - Side Channels KW - Disinformation KW - Propaganda KW - User-Generated Content KW - Russia KW - Ukraine KW - Tripadvisor KW - Google Maps KW - VKontakte Y1 - 2023 UR - https://arxiv.org/abs/2302.00598 U6 - https://doi.org/10.48550/arXiv.2302.00598 ER - TY - GEN A1 - Reelfs, Jens Helge A1 - Hohlfeld, Oliver A1 - Henckell, Niklas T1 - Geographic Differences in Social Media Interactions Exist Between Western and Middle-East Countries T2 - Passive and Active Measurement Conference 2022 N2 - 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. Y1 - 2022 SN - 978-3-030-98785-5 SN - 978-3-030-98784-8 U6 - https://doi.org/10.1007/978-3-030-98785-5_18 SP - 411 EP - 425 PB - Springer CY - Cham ER - TY - GEN A1 - Reelfs, Jens Helge A1 - Mohaupt, Timon A1 - Sikdar, Sandipan A1 - Strohmaier, Markus A1 - Hohlfeld, Oliver T1 - Interpreting Emoji with Emoji: 🏖️ => ☀️😎🌊 T2 - 5th International Workshop on Emoji Understanding and Applications in Social Media 2022 N2 - 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. Y1 - 2022 UR - https://aiisc.ai/emoji2022/#section-agenda ER - TY - GEN A1 - Reelfs, Jens Helge A1 - Hohlfeld, Oliver A1 - Henckell, Niklas T1 - Anonymous Hyperlocal Communities: What do they talk about? T2 - 12th International Workshop on Location and the Web (LocWeb'22) N2 - 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. Y1 - 2022 UR - https://arxiv.org/abs/2203.05657 U6 - https://doi.org/10.48550/arXiv.2203.05657 ER -