@phdthesis{Reelfs2023, author = {Reelfs, Jens Helge}, title = {Content \& user behavior in anonymous hyperlocal online platforms}, doi = {10.26127/BTUOpen-6375}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:co1-opus4-63754}, school = {BTU Cottbus - Senftenberg}, year = {2023}, abstract = {Nowadays day-to-day digital communication and social life has only fortified with the ongoing pandemic. People enjoy communication and information across various (direct) messaging platforms and accepted its ever-increasing impact on public discourse and society. While traditional platforms implement user profiles enabling social credit, the landscape also includes anonymity. Yet, a new type of application combining anonymity with a strong spatial focus, hyperlocality, emerged over recent years. To this point, platform implications of both uniquely combined design properties largely remain unknown. In this thesis, we provide a first data-driven holistic view on Jodel that combines both properties. We leverage unbiased complete ground truth information to dissect a plethora of communities across two different countries: Germany and the Kingdom of Saudi Arabia. This work follows a platform perspective identifying four major essentially important areas revolving around the individual. That is, we begin with a broad analysis of three User Adoption processes along three different applications. After discussing our measurements of the user base adoption of the German COVID-19 digital contact tracing application, we provide evidence of well-established platforms being re-purposed as a side channel to evade censorship in the ongoing Russo-Ukrainian hybrid war. We further showcase that the very same platform ingredients may yield vastly different outcomes on the messaging app Jodel. While any online platform builds upon User Interactions, we structurally characterize Jodel behavior across both countries. We discuss structural disparities and detail platform implications - solely induced by local user behavior. An in-depth look into the Saudi community landscape closes a research gap to platform usage in a different society, identifying differences. Further, we discuss User Content analyzing information diffusion. Taking content to the next level, we developed a multidimensional classification scheme for intents (why) and topics (what) of social media messages and provide details of a crowdsourced campaign for Saudi Arabian contents. With neural word embeddings as a tool for making text tangible and the prevalence of emoji in social media communication, we discuss quantitative and qualitative insights to word-emoji embeddings reflecting semantics. Additionally, we make such embeddings interpretable and provide evidence that our method is well in line with human judgement. In terms of User Management, we detail insights to distributed moderation processes and model the threat of abusive content. In the long term, platforms need to establish a sustainable, preferably growing, environment. That is, we next discuss user lifetime and possibly early churn factors, while modeling user lifetime from metadata. We finish with a blueprint of data-driven long-term quality of experience analyzes in a controlled massively multiplayer online game (MMOG) environment.}, subject = {Dissertation; Anonymity; Hyperlocality; Online social platforms; Human behavior; Anonymit{\"a}t; Hyperlokalit{\"a}t; Soziale Online-Plattformen; Menschliches Verhalten; Deutschland; Saudi-Arabien; Social Media; Kommunikation; Anonymit{\"a}t; Verhalten}, language = {en} }