A person seeking someone else's attention is normally able to quickly assess how interruptible they are. This assessment allows for behavior we perceive as natural, socially appropriate, or simply polite. On the other hand, today's computer systems are almost entirely oblivious to the human world they operate in, and typically have no way to take into account the interruptibility of the user. This paper presents a Wizard of Oz study exploring whether, and how, robust sensor-based predictions of interruptibility might be constructed, which sensors might be most useful to such predictions, and how simple such sensors might be. The study simulates a range of possible sensors through human coding of audio and video recordings. Experience sampling is used to simultaneously collect randomly distributed self-reports of interruptibility. Based on these simulated sensors, we construct statistical models predicting human interruptibility and compare their predictions with the collected self-report data. The results of these models, although covering a demographically limited sample, are very promising, with the overall accuracy of several models reaching about 78%. Additionally, a model tuned to avoiding unwanted interruptions does so for 90% of its predictions, while retaining 75% overall accuracy.

Instant Messaging (IM) is being widely adopted by teenagers. In a study of 16 teenage IM users, we explore IM as an emerging feature of teen life, focusing our questions on its support of interpersonal communication and its role and salience in everyday life. We qualitatively describe the teens' IM use interpersonally, as well as its place in the domestic ecology. We also identify technology adoption conditions and discuss behaviors around privacy management. In this initial investigation, we found differences in the nature of use between high school and college teens, differences we propose are accounted for by teens' degree of autonomy as a function of domestic and scholastic obligations, the development of independent work practices, Internet connectivity access, and even transportation access. Moreover, while teen IM use is in part characterized as an optimizing choice between multiple communications media, practice is also tied to concerns around peer pressure, peer group membership and creating additional opportunities to socialize.

It has been proposed that email clients could be improved if they presented messages grouped into conversations. An email conversation is the tree of related messages that arises from the use of the reply operation. We propose two models of conversation. The first model characterizes a conversation as a chronological sequence of messages; the second as a tree based on the reply relationship. We show how existing email clients and prior research projects implicitly support each model to a greater or lesser degree depending on their design, but none fully supports both models simultaneously. We present a mixed-model visualization that simultaneously presents sequence and reply relationships among the messages of a conversation, making both visible at a glance. We describe the integration of the visualization into a working prototype email client. A usability study indicates that the system meets our usability goals and verifies that the visualization fully conveys both types of relationships within the messages of an email conversation. Keywords Computer-mediated communication, asynchronous

We present a study of anonymized data capturing a month of high-level communication activities within the whole of the Microsoft Messenger instant-messaging system. We examine characteristics and patterns that emerge from the collective dynamics of large numbers of people, rather than the actions and characteristics of individuals. The dataset contains summary properties of 30 billion conversations among 240 million people. From the data, we construct a communication graph with 180 million nodes and 1.3 billion undirected edges, creating the largest social network constructed and analyzed to date. We report on multiple aspects of the dataset and synthesized graph. We find that the graph is well-connected and robust to node removal. We investigate on a planetary-scale the oft-cited report that people are separated by “six degrees of separation” and find that the average path length among Messenger users is 6.6. We also find that people tend to communicate more with each other when they have similar age, language, and location, and that cross-gender conversations are both more frequent and of longer duration than conversations with the same gender.

Pervasive personal communication technologies offer the potential for important social benefits for individual users, but also the potential for significant social difficulties and costs. In research on face-to-face social interaction, ambiguity is often identified as an important resource for resolving social difficulties. In this paper, we discuss two design cases of personal communication systems, one based on fieldwork of a commercial system and another based on an unrealized design concept. The cases illustrate how user behavior concerning a particular social difficulty, unexplained unresponsiveness, can be influenced by technological issues that result in interactional ambiguity. The cases also highlight the need to balance the utility of ambiguity against the utility of usability and communicative clarity.

There are a variety of digital tools for enabling people who are physically separated by time and space to communicate and collaborate. Widespread use of some of these tools, such as instant messaging and group chat, coupled with the increasingly availability of wireless Internet access, have created new opportunities for using these collaboration tools by people sharing physical spaces in real time. Such ‘digital backchannels ’ affect interactions and experiences in a variety of ways, depending on the spaces, the participants, and the relationships among them. We focus on the space of an academic conference, a physical space designed for voluntary participation by people with shared interests, seeking to share knowledge and connect with others. We present and analyze system logs and interview data from a recent conference, highlight some of the advantages and disadvantages experienced both by those who used the tools and by those who did not, and discuss implications and considerations for future use and research.

We present a study of anonymized data capturing high-level communication activities within the Microsoft Instant Messenger network. We analyze properties of the communication network defined by user interactions and demographics, as reported and as derived from one month of data collected in June 2006. The compressed dataset occupies 4.5 terabytes, composed from 1 billion conversations per day (150 gigabytes) over one month of logging. The dataset contains more than 30 billion conversations among 240 million people. We focus on analyses of high-level characteristics and patterns that emerge from the collective dynamics of 240 million people, rather than the actions and characteristics of individuals. Analyses center on numbers and durations of conversations; the content of communications was neither available nor pursued. From the data we construct a communication graph with 190 million nodes and 1.3 billion undirected edges. We find that the graph is well connected, with an effective diameter of 7.8, and is highly clustered, with a clustering coefficient decaying slowly with exponent −0.4. We also find strong influences of homophily in activities, where people with

“Typography that doesn’t stand still ” Kinetic Typography is found in fi lm titles, music videos, TV commercials and websites. It is emerging as a new form of expression due to its ability to convey emotions, personality and tone of voice. Despite its many applications it remains largely unexplored as a communication tool.

A basic premise behind the study of large networks is that interaction leads to complex collective behavior. In our work we found very interesting and counterintuitive patterns for time evolving networks, which change some of the basic assumptions that were made in the past. We then develop models that explain processes which govern the network evolution, fit such models to real networks, and use them to generate realistic graphs or give formal explanations about their properties. In addition, our work has a wide range of applications: it can help us spot anomalous graphs and outliers, forecast future graph structure and run simulations of network evolution. Another important aspect of our research is the study of “local ” patterns and structures of propagation in networks. We aim to identify building blocks of the networks and find the patterns of influence that these blocks have on information or virus propagation over the network. Our recent work included the study of the spread of influence in a large person-to-person

This paper presents an exploratory study of college-age students using twoway, push-to-talk cellular radios. We describe the observed and reported use of cellular radio by the participants, the activities and purposes for which they adopted it, and their responses. We then examine these empirical results using mediated communication theory. Cellular radios have a unique combination of affordances relative to other media used by this age group, including instant messaging (IM) and mobile phones; the results of our analysis do suggest explanations for some observed phenomena but also highlight the counter-intuitive nature of other phenomena. For example, although the radios have many important dissimilarities with IM from the viewpoint of mediated communication theory, the observed use patterns resembled those of IM to a surprising degree.