This paper explores how the adoption of mobile and social computing technologies has impacted upon the way in which we coordinate social group-activities. We present a diary study of 36 individuals that provides an overview of how group coordination is currently performed as well as the challenges people face. Our findings highlight that people primarily use open-channel communication tools (e.g., text messaging, phone calls, email) to coordinate because the alternatives are seen as either disrupting or curbing to the natural conversational processes. Yet the use of open-channel tools often results in conversational overload and a significant disparity of work between coordinating individuals. This in turn often leads to a sense of frustration and confusion about coordination details. We discuss how the findings argue for a significant shift in our thinking about the design of coordination support systems.

Social computing applications are transforming the way we make new social ties, work, learn and play, thus becoming an essential part our social fabric. As a result, people and systems routinely make inferences about people's personal information based on their disclosed personal information. Despite the significance of this phenomenon the opportunity to make social inferences about users and how this process can be managed is poorly understood. In this paper we 1) outline why social inferences are important to study in the context of social computing applications, 2) how we can model, understand and predict social inference opportunities 3) highlight the need for social inference management systems, and 4) discuss the design space and associated research challenges. Collectively, this paper provides the first systematic overview for social inference research in the area of social computing.

Current cell phone designs are limited by the information a caller can provide to the receiver at the time of a call. As a result callers are handicapped in effectively negotiating interaction commitment from the receiver, and perhaps more importantly, receivers are unable to make informed call handling decisions. To examine the nature of this information gap we 1) developed Telling Calls, a mobile phone application which allows users to provide and receive information such as what the call is about and the circumstances of the caller under which it is being made, and 2) conducted a qualitative field study (36 users) and a quantitative field study (30 users) of Telling Calls use. Together these studies provide insights on how additional caller generated information shared at the time of call handling effectively improves the process of negotiating interaction commitment, and establishing common ground.

Call handling decisions are made based on explicit information such as caller ID and/or implicit knowledge inferred from previous interactions. Our previous work showed that people often answer calls to find out the reason behind the call. This suggests that the provision of explicit information regarding what a call is about or under what circumstances is it being made can be of value in call handling decisions. To explore this concept we developed Telling Calls a prototype application for cell phone users to provide and receive call related information. We present the design rationale and lessons learned from qualitative accounts of users' experience with the application in their daily life. Our findings confirm the utility of our design and suggest ways in which we can improve the design to support informed call handling decisions in mobile phones.

Social matching systems recommend people to other people. With the widespread adoption of smartphones, mobile social matching systems could potentially transform our social landscape. However, we have a limited understanding of what makes a good social match in the mobile context. We present a theoretical framework which outlines how a user's context and the rarity of different affinity measures in various contexts (match rarity) can be used to provide valuable social matches. We suggest that if a user attribute is very rare in a particular context, users will generally be more interested in an affinity match. We conducted a survey study to assess this framework with 117 respondents. We found that both context and match rarity significantly influence interest in a social match. These results validate the key aspects of the framework. We discuss the results in terms of implications for social matching system design.