In this paper, we propose to improve time management in the enterprise by providing users interactive visualizations of how they are spending their time. Through an interview study (n=21) in a multi-national corporation, we were able to determine the data available for visualizations and the value of a number of general visualizations of employees' calendar data. We develop implications for design in improving personal time management.

We present the system design and rational for a novel social microcalendar called Timely. Our system has been inspired by previous research on calendaring and popular social network applications, in particular microblogging. Timely provides an open, social space for enterprise users to share their events, socialize, and discover what else is going on in their network and beyond. A detailed analysis of the events shared by users during the site's first 47 days reveals that users willingly share their time commitments despite an existing culture of restricted calendars.

Existing enterprise calendaring systems have suffered from problems like rigidity, lack of transparency, and poor integration with social networks. We present the system design and rationale for a novel social coordination mechanism, called "Suggestions," that addresses these issues. Our system integrates ideas drawn from designs of lightweight polling systems and one's social network into an open calendar tool, providing a space for users to coordinate, socialize around, or negotiate the "what" and the "when" of their events. Suggestions was released inside a large enterprise setting, where initial interviews revealed users' thoughts on transparent scheduling, reaching wider audiences and task appropriateness, and suggested ways to improve our design.

As online communities, such as social network sites, mature, they face challenges in sustaining user engagement. To address this, we designed and deployed a rating system to encourage a broad set of users to promote a diverse set of content on a social network site. By evaluating the impact of the promotions on the site's content and users over time, we found that the system successfully promotes more diverse content and encourages new social interactions between users.

Success and sustainability of social networking sites is highly dependent on user participation. To encourage contribution to an opt-in social networking site designed for employees, we have designed and implemented a feature that rewards contribution with points. In our evaluation of the impact of the system, we found that employees are initially motivated to add more content to the site. This paper presents the analysis and design of the point system, the results of our experiment, and our insights regarding future directions derived from our post-experiment user interviews.

Social networking sites support a variety of shared content types such as photos, videos, or music. More structured or form-based social content types are not mainstream but we have started seeing sites evolve that support them. This paper describes the design and use of structured lists in an enterprise social networking system. As a major feature of our shared lists, we introduced the ability to reuse someone else's list. We report the results on the use and reuse of shared lists based on three months of usage data from 285 users and interviews with 9 users. Our findings suggest that despite the structured nature of lists, our users socialize more around lists than photos, and use lists as a medium for self-representation.

This paper investigates using social tags for the purpose of making personalized content recommendations. Our tag-based recommender creates a personalized bookmark recommendation model for each user based on current and general interest tags, defined by different time intervals.

The introduction of a social networking site inside of a large enterprise enables a new method of communication between colleagues, encouraging both personal and professional sharing inside the protected walls of a company intranet. Our analysis of user behavior and interviews presents the case that professionals use internal social networking to build stronger bonds with their weak ties and to reach out to employees they do not know. Their motivations in doing this include connecting on a personal level with coworkers, advancing their career with the company, and campaigning for their projects.

User profiles on today's social networking sites support only a small set of predefined questions. We report on an alternative way for users to richly describe themselves, by entering not only responses, but their own questions as well. Data from 10 months of usage shows that users of a social networking site created thousands of diverse questions and reused existing questions from other users. Our findings suggest that those with highly diverse user profiles have a higher number of friends.

Knowledge workers perform many different activities daily. Each activity defines a distinct work context with different information needs. In this paper we leverage users' activity representations, stored in an activity management system, to automatically recommend resources to support knowledge workers in their current activity. We developed a collaborative activity predictor to both predict the current work activity and measure a resource's relevance to a specific activity. Relevant resources are then displayed in a contextual side bar on the desktop. We describe the system, our new activity-centric search algorithm, and experimental results based on the data from 50 real users.

Activity-centric collaboration environments help knowledge workers to manage the context of their shared work activities by providing a representation for an activity and its resources. Activity management systems provide more structure and organization than email to execute the shared activity but, as the number of shared activities increases, it becomes more and more difficult for users to focus on important activities that need their attention. This paper describes a personalized activity prioriti-zation approach implemented on top of the Lotus Connections Activities management system. Our prototype implementation allows each user to view activities ordered by her/his predicted priorities. The predictions are made using a ranking Support Vector Machine model trained with the user’s past interactions with the activities system. We describe the prioritization interface and the results of an offline experiment based on data from 13 users over 6-months. Our results show that our feature set derived from shared activity structures can significantly increase prediction accuracy compared to a recency baseline.

We describe the Dogear Game, which works with an enterprise social bookmarking system. The game is designed to accomplish individual, collaborative, and organization goals. Individual players receive entertainment and learn about their colleagues' bookmarks. The player's colleagues receive recommendations of websites and documents of potential interest to them. And the organization benefits from a richer knowledge-base of bookmarks as recommendations are accepted. The Dogear Game builds on von Ahn's "serious games," useful in motivating and distributing game-like entertaining "work" to a large group of game players. This note presents the design and implementation of a working prototype and some initial user feedback.

As the number of alerts generated by collaborative applications grows, users receive more unwanted alerts. FeedMe is a general alert management system based on XML feed protocols such as RSS and ATOM. In addition to traditional rule-based alert filtering, FeedMe uses techniques from machine-learning to infer alert preferences based on user feedback. In this paper, we present and evaluate a new collaborative naive Bayes filtering algorithm. Using FeedMe, we collected alert ratings from 33 users over 29 days. We used the data to design and verify the accuracy of the filtering algorithm and provide insights into alert prediction.

This paper describes a new collaboration technology that is based on the support of lightweight, informally structured, opportunistic activities featuring heterogeneous threads of shared items with dynamic membership. We introduce our design concepts, and we provide a detailed analysis of user behavior during a five month field study. We present the patterns of media use that we observed, using a variety of analytical methods including thread clustering and analysis. Major findings include four patterns of media use: communicating, exchanging mixed objects, coordinating, (e.g., of status reports), and semi-archival filing. We observed differential use of various media including highly variable use of chats and surprisingly informal uses of files. We discuss the implications for the design of mixed media collaborative tools to support the work activities of small to medium sized work teams.

Chat Spaces are rich persistent chats that provide light-weight shared workspaces for small to medium-scale group activities. Chat Spaces can accommodate brief, informal interactions (similar to Instant Messaging), and can also support longer-term complex threaded conversations including large numbers of people and shared resources. Our design maps a hierarchical thread representation onto a time-ordered two-column user interface. This mapping allows a user to follow the global dynamics of the entire thread in the chronological column on the left while being able to participate in a selected topical branch in a second column on the right. We also present a dynamic thread map that provides an overview of the entire conversation and supports quick navigation of topical branches in the thread.

This paper describes a new collaboration technology that is carefully poised between informal, ad hoc, easy-to-initiate collaborative tools, vs. more formal, structured, and high-overhead collaborative applications. Our approach focuses on the support of lightweight, informally structured, opportunistic activities featuring heterogeneous threads of shared objects with dynamic membership. We introduce our design concepts, and we provide a detailed first look at data from the first 100 days of usage by 20 researchers and 13 interns, who both confirmed our hypotheses and surprised us by reinventing the technology in several ways.

In this paper, we describe the rationale behind and architecture of a conversational agent capable of speech enabling multiple applications.

In this paper, we describe the user interface principles guiding the design of a conversational agent capable of speech enabling multiple applications, and provide a sample of its typical dialog.