Online Social Networks (OSNs) have seen an exponential growth over the last decade, with Facebook having more than 1.49 billion monthly active users and Twitter having 135,000 new users signing up every day as of 2015. Users are sharing 70 million photos per day on the Instagram photo-sharing network. Yahoo Answers question-answering community has more than 1 billion posted answers. The meteoric rise in popularity has made OSNs important social platforms for computer-mediated communications and embedded themselves into society’s daily life, with direct consequences to the offline world and activities. OSNs are built on a foundation of trust, where users connect to other users with common interests or overlapping personal trajectories. They leverage real-world social relationships and/or common preferences, and enable users to communicate online by providing them with a variety of interaction mechanisms. This dissertation studies abuse and privacy in online social networks. More specifically, we look at two issues: (1) the content abusers in the community question answering (CQA) social network and, (2) the privacy risks that comes from the default permissive privacy settings of the OSNs. Abusive users have negative consequences for the community and its users, as they decrease the community’s cohesion, performance, and participation. We investigate the reporting of 10 million editorially curated abuse reports from 1.5 million users in Yahoo Answers, one of the oldest, largest, and most popular CQA platforms. We characterize the contribution and position of the content abusers in Yahoo Answers social networks. Based on our empirical observations, we build machine learning models to predict such users. Users not only face the risk of exposing themselves to abusive users or content, but also face leakage risks of their personal information due to weak and permissive default privacy policies. We study the relationship between users’ privacy concerns and their engagement in Yahoo Answers social networks. We find privacy-concerned users have higher qualitative and quantitative contributions, show higher retention, report more abuses, have higher perception on answer quality and have larger social circles. Next, we look at users’ privacy concerns, abusive behavior, and engagement through the lenses of national cultures and discover cross-cultural variations in CQA social networks. However, our study in Yahoo Answers reveals that the majority of users (about 87%) do not change the default privacy policies. Moreover, we find a similar story in a different type of social network (blogging): 92% bloggers’ do not change their default privacy settings. These results on default privacy are consistent with general-purpose social networks (such as Facebook) and warn about the importance of user-protecting default privacy settings. We model and implement default privacy as contextual integrity in OSNs. We present a privacy framework, Aegis, and provide a reference implementation. Aegis models expected privacy as contextual integrity using semantic web tools and focuses on defining default privacy policies. Finally, this dissertation presents a comprehensive overview of the privacy and security attacks in the online social networks projecting them in two directions: attacks that exploit users’ personal information and declared social relationships for unintended purposes; and attacks that are aimed at the OSN service provider itself, by threatening its core business.

Denna kvalitativa studie undersöker hur och varför användare av sociala medier sprider sin aktivitet över flera av dessa samtidigt. Fokus låg på de tre sociala medierna Facebook, Instagram och Snapchat. Studien genomfördes genom att hålla parintervjuer med användare av dessa medier för att sedan applicera det erhållna resultatet på ramverket kontextuell integritet. Resultatet av studien är intressant för de företag som utvecklar och använder sig av sociala medier och även för framtida forskning inom ämnet. Vår studie visade en skillnad i delandet av information över de tre sociala medierna. Den främsta orsaken till skillnaden identifierades som storleken på kontaktnäten hos medierna, och dess inverkan på vad som upplevdes vara ett intrång i den personliga integriteten när information delades. Förutom den ökade visibiliteten som kommer med ett större kontaktnät hade det även inverkan på den underliggande aktiviteten på mediet vilket kan ses som en orsak till ett minskande av aktivt användande. De slutsatser som drogs kring framtiden var att sociala medier, både dagens och framtida, måste ge användarna ett alternativ att dela in sitt kontaktnät  i grupper. Alternativt att de sociala medierna själva måste bli nischade för en specifik del av användarnas kontaktnät. Detta kommer tillåta användarna att dela accepterbar information i lämpliga kanaler. / This qualitative study examines how and why users of social media distribute their activity over several of these at the sametime. Focus was on the three social media sites of Facebook, Instagram and Snapchat. The study was carried through bykeeping paired interviews with users of these sites and then applying the results on the framework of contextual integrity .The result of the study is interesting both for companies developing and using social media sites, as well as for futureresearch in the field. The results showed a difference in the sharing of information across the three different sites. The foremost cause to thedifference was identified to be the size of the social networks on the sites, and the influence this had on what was perceivedas an intrusion in the privacy of the user when the information was shared. Aside from the increased visibility that comeswith a larger social network, it also affected the underlying activity of the social medium. Which can be seen as a reason fora decreasing active use. The conclusions about the future were that social media, today and in the future, have to give theusers an alternative to separate their social network on the sites into separate groups. Alternatively that the social media sitesthemselves has to become niched for a specific part of a user's social network. This will allow the users to share acceptableinformation in suitable channels.

Privacy is an essential concept in the field of healthcare. As healthcare is fast digitalizing and going through platformization, understanding how it is constructed has become important. Swedish digital healthcare platform 1177 is a unique case, that can be used to analyze how the different actors that are present in the platform environment like the platform owner, healthcare organizations, and patients take part in the construction of privacy in a platform environment and how for example national and international legislation affects on the societal norms of the platform. By using the context analysis method and operationalizing platform society – and contextual integrity theory to 1177, it was revealed that while there is a clear hierarchy between the actors, all of them participate in different ways into making sure that the data that flows within the platform is being processed securely and with privacy in mind. While the platforms are their own socio-technical environments, they are also affected by national and international legislative norms. Compliance with legislation like the GDPR and the Swedish national patient data law is important as non-compliance can cause issues for the platform. However, while the platform privacy construction would be strong, the development of data analysis methods and AI can pose a risk for the data transfer from the platform to other purposes, like for example in research.

Les approches habituelles pour la protection de la privacité s'attachent à définir un niveau de sensibilité pour chaque information. Cette information est soit publique, soit privée et sa circulation est restreinte à un groupe d'agents prédéfini. Dans cette thèse, nous nous appuyons sur la théorie de l'intégrité contextuelle, qui propose de redéfinir la notion de violation de privacité. Selon cette théorie, toute transmission peut déclencher une violation de privacité suivant le contexte dans lequel elle a lieu. Cette thèse utilise la théorie de l'intégrité contextuelle afin de proposer un modèle de protection de la privacité pour les systèmes multi-agents décentralisés: le modèle PrivaCIAS. Afin de contrôler les agents dans le système, le modèle PrivaCIAS fournit un ensemble de normes qui permet la mise en place d'un contrôle social basé sur la confiance. Le modèle donne le contrôle aux agents pour constater les violations (selon l'intégrité contextuelle), puis punir les contrevenants en les excluant du système sans avoir besoin de recourir à une autorité centrale. Ce modèle vise les réseaux sociaux décentralisés comme champ d'application. / Contextual Integrity has been proposed to define privacy in an unusual way. Most approaches take into account a sensitivity level or a ``privacy circle'': the information is said to be either private or public and to be constrained to a given group of agents, \textit{e.g.} ``my friends'', when private. In the opposite, Contextual Integrity states that any information transmitted can make this transmission a privacy violation depending on its context. In this thesis, we use this theory to develop a novel model that one can use in an open and decentralized virtual community to socially enforce privacy. This thesis defines the PrivaCIAS model, in which privacy constraints are formally described to be used to detect privacy violations according to the Contextual Integrity theory. The PrivaCIAS model provides norms to agents in order to make them implement social control. The model does not require a central authority, it gives control to the agents for detecting privacy violations (through Contextual Integrity) and excluding violating agents from the system through social exclusion. This model targets decentralized social networks as a main application domain.

Social network sites (SNSs) have become very popular, with more than 1.39 billion people using Facebook alone. The ability to share large amounts of personal information with these services, such as location traces, photos, and messages, has raised a number of privacy concerns. The popularity of these services has enabled new research directions, allowing researchers to collect large amounts of data from SNSs to gain insight into how people share information, and to identify and resolve issues with such services. There are challenges to conducting such research responsibly, ensuring studies are ethical and protect the privacy of participants, while ensuring research outputs are sustainable and can be reproduced in the future. These challenges motivate the application of a theoretical framework that can be used to understand, identify, and mitigate the privacy impacts of emerging SNSs, and the conduct of ethical SNS studies. In this thesis, we apply Nissenbaum's model of contextual integrity to the study of SNSs. We develop an architecture for conducting privacy-preserving and reproducible SNS studies that upholds the contextual integrity of participants. We apply the architecture to the study of informed consent to show that contextual integrity can be leveraged to improve the acquisition of consent in such studies. We then use contextual integrity to diagnose potential privacy violations in an emerging form of SNS.