° These authors contributed equally to the paper and are listed alphabetically. Social computing has led to an explosion of research in understanding users, and has the potential to similarly revolutionize systems research. However, the number of papers designing and building new sociotechnical systems has not kept pace. In this paper we analyze the reasons for this disparity, ranging from misaligned methodological incentives, evaluation expectations and research relevance compared to industry. We suggest improvements for the community to consider and evolve so that we can chart the future of our field. General Terms Social computing, systems research, evaluation

Like many online communities, social network sites have a considerable participation inequality: a large percentage of users rarely contribute or log in. As a result, only a few of a user’s friends will actually contribute content – and those friends are not necessarily the ones the user wants to hear from. To populate information about less active users back into the network and to draw the users back into the site, we friendsource Facebook, enabling active contributors to participate on behalf of the less active users. We have developed a pair of applications to explore this concept: 1) Sociapedia is a collaboratively edited encyclopedia where friends can write articles about each other; 2) stat.us allows users to opt-in so that their friends can author status updates on their behalf. Sociapedia collects static information, while stat.us encourages ephemeral updates. A mixed-methods evaluation of the systems revealed that friends were willing to inject personality and humor into each others ’ profiles and status feeds. However, they were often conservative about what they wrote, not wanting to offend the profile owner. We explore issues of egocentric bias, privacy, and information novelty in the systems, and consider future applications of the social network friendsourcing concept. Author Keywords Facebook applications, friendsourcing, social computing, online participation ACM Classification Keywords H5.3. Information interfaces and presentation (e.g., HCI): Web-based interaction.

Social computing has led to an explosion of research in understanding users, and it has the potential to similarly revolutionize systems research. However, the number of papers designing and building new sociotechnical systems has not kept pace. We analyze challenges facing social computing systems research, ranging from misaligned methodological incentives, evaluation expectations, double standards, and relevance compared to industry. We suggest improvements for the community to consider so that we can chart the future of our field. ° These authors contributed equally to the paper and are listed alphabetically. Copyright is held by the author/owner(s).

This paper presents ReadWriter, a novel blogging interface that enables task automation and offers on-demand writing feedback. Bloggers can express any writing-related help requests in natural language inside double brackets. Read-Writer interprets a blogger’s requests and assigns them to a diverse group of contributors: software search agents, an anonymous crowd, the blogger’s social connections, and readers. The entire cycle of creating a request, checking status, reviewing results, and applying to a draft occurs inside the blogging interface. Design goals are to help writers maintain flow by automatically managing housekeeping tasks, and to engage readers earlier on in the writing process. Analysis of collected requests identified distinct categories of tasks people expect from the system. Five bloggers in the lab study found the tool easy to learn and use, and exhibited various usage patterns during a writing task. ACM Classification: H5.2 [Information interfaces and

My research combines computation with the intelligence of crowds—large groups of people connecting and coordinating online—to create hybrid human-computer systems. Combining machine and crowd intelligence opens up a broad new class of software systems that can solve problems neither could solve alone. However, while crowds are increasingly adept at straightforward parallel tasks, they struggle to accomplish many goals: participants vary in quality, well-intentioned contributions can introduce errors, and future participants amplify and propagate those errors. Moreover, crowds that can generate the necessary information might not even exist yet, or their knowledge might be distributed across the web. My work in human-computer interaction develops computational techniques to overcome these limits in crowdsourcing. These solutions adopt a broad view of how we might integrate crowds and computation: 1) embedding crowd work into interactive systems, 2) creating new crowds by designing social computing systems, and 3) mining crowd data for interactive applications. Crowd-Powered Systems I create systems that are powered by crowd intelligence: these systems advance crowdsourcing from a batch platform to one that is interactive and realtime. To embed crowds as first-order building blocks in software, we need to address problems in crowd work quality and latency. This research develops computational techniques that decompose complex tasks into simpler, verifiable steps, return results in seconds, and open up a new design space of interactive systems. To instantiate these ideas, I developed a crowd-powered word processor called Soylent that uses paid microcontributions to aid writing tasks such as text shortening and proofreading [1]. Using Soylent is like having an entire editorial staff available as you write. For example, crowds shorten the user’s writing by finding wordy text and offering alternatives that the user might not have considered. The user selects from these alternatives using a slider that specifies the desired text length (Figure 1). On average, Soylent can shorten text up to 85 % of its original length. By using tighter wording rather than wholesale cuts, the system shortens a ten-page draft by a page and a half in only a few minutes. Soylent also offers human-powered proofreading and natural-language macros.