In this chapter I review empirical studies directly testing the

Social media treats all users the same: trusted friend or total stranger, with little or nothing in between. In reality, relationships fall everywhere along this spectrum, a topic social science has investigated for decades under the theme of tie strength. Our work bridges this gap between theory and practice. In this paper, we present a predictive model that maps social media data to tie strength. The model builds on a dataset of over 2,000 social media ties and performs quite well, distinguishing between strong and weak ties with over 85 % accuracy. We complement these quantitative findings with interviews that unpack the relationships we could not predict. The paper concludes by illustrating how modeling tie strength can improve social media design elements, including privacy controls, message routing, friend introductions and information prioritization. Author Keywords Social media, social networks, relationship modeling, ties,

Abstract. The problem of determining whether a receiver may safely accept attributes (e.g., identity, credentials, location) of unknown senders in various online social protocols is a special instance of a more general problem of establishing trust in interactive protocols. We introduce the notion of interactive trust protocols to illustrate the usefulness of social collateral in reducing the inherent trust asymmetry in large classes of online user interactions. We define a social collateral model that allows receivers to accept attributes from unknown senders based on explicit recommendations received from social relations. We use social collateral as a measure of both social relations and “tie strength ” among individuals to provide different degrees of accountability when accepting attribute information from unknown senders. Our model is robust in the face of several specific attacks, such as impersonation and tiestrength-amplification attacks. Preliminary experiments with visualization of measured tie strength among users of a social network indicate that the model is usable by ordinary protocol participants. 1