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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.
Privacy issues are becoming more and more important, especially since the cyber and the real world are converging up to certain extent when using mobile devices. Means that really protect privacy are still missing. The problem is, as soon as a user provides data to a service provider the user looses control over her/his data. The simple solution is not to provide any data but then many useful services, e.g., navigation applications, cannot be used. The dissertation addresses two aspects of privacy protection. The first aspect regards not producing private information if possible. Such unnecessary information are traces of access controlled service uses. Hence, one approach in this dissertation enables k-anonymous authorization for services uses. It equips the users of the system with trusted pseudonymous certificates reflecting their respective authorizations. Analogous to anonymous e-cash, the certificates are issued by a trusted authority with knowledge of the actual authorizations of an identified user. The certificates can be verified by any service supported by the trusted authority but without knowledge of the user’s identity. Not even the issuing authority is able to reveal the users identity from the pseudonym of a certificate. Hence, service usage cannot be tracked, neither by the service nor by the authority. This protects the privacy of service usage behavior of users. The second aspect of privacy protection is to remain in control over private data released to others. Temporary release of private data is essential to context-sensitive services, which rely on these context data to provide or improve added value. Therefore, the dissertation designs a Privacy Guaranteeing Execution Container (PGEC), which enables applications to access private user data and guarantees that the user data is deleted as soon as the service or application is finished. Basically, the concept is that the application obtains access to the user data in a specially protected and certified environment, the PGEC. The PGEC also restricts the communication between the application and the service provider to what is explicitly allowed by the service user. In addition to those means, the PGEC also implements countermeasures against malicious attacks such as modified host systems and covert channel attacks, which might be misusing CPU load to signal data out of the PGEC. Thus, the PGEC guarantees a “one time use” of the provided private data.