Ecoacoustics draws together computer scientists and ecologists to achieve an understanding of ecosystems and wildlife using acoustic recordings of the environment. Computer scientists are challenged to manage increasingly large datasets while developing analytic and visualisation tools. Ecologists struggle to find and use tools that answer highly heterogeneous research questions. These two fields are naturally drawn together at the tool interface, however, less attention has been paid to how their practices influence tool design and use. We interviewed and collected email correspondence from four computer scientists and eight ecologists to learn how their practices indicate opportunities for reconciling difference through design. We found that different temporal rhythms, relationships to data, and data-driven questions demand tool configuration, data integration, and standardisation. This research outlines interfacing opportunities for new ecological research utilising large acoustic datasets, and also contributes to evolving HCI approaches in areas making use of big data and human-in-the-loop processes.
Ideation is essential for creative writing. Many authors struggle to come up with ideas throughout the writing process, yet modern writing tools fail to provide on-the-spot assistance for writers when they get stuck. This paper introduces Heteroglossia, an add-on for Google Docs that allows writers to elicit story ideas from the online crowd using their text editors. Writers can share snippets of their working drafts and ask the crowd to provide follow-up story ideas based on it. Heteroglossia employs a strategy called "role play", where each worker is assigned a fictional character in a story and asked to brainstorm plot ideas from that character's perspective. Our deployment with two experienced story writers shows that Heteroglossia is easy to use and can generate interesting ideas. Heteroglossia allows us to gain insight into how future technologies can be developed to support ideation in creative writing.
Feedback from diverse audiences can vary in focus, differ in structure, and contradict each other, making it hard to interpret and act on. While prior work has explored generating quality feedback, our work helps a designer interpret that feedback. Through a formative study with professional designers (N=10), we discovered that the interpretation process includes categorizing feedback, identifying valuable feedback, and prioritizing which feedback to incorporate in a revision. We also found that designers leverage feedback topic and sentiment, and the status of the provider to aid interpretation. Based on the findings, we created a new tool (Decipher) that enables designers to visualize and navigate a collection of feedback using its topic and sentiment structure. In a preliminary evaluation (N=20), we found that Decipher helped users feel less overwhelmed during feedback interpretation tasks and better attend to critical issues and conflicting opinions compared to using a typical document-editing tool.
Online chat is an emerging channel for discussing community problems. It is common practice for communities to assign dedicated moderators to maintain a structured discussion and enhance the problem-solving experience. However, due to the synchronous nature of online chat, moderators face a high managerial overhead in tasks like discussion stage management, opinion summarization, and consensus-building support. To assist moderators with facilitating a structured discussion for community problem-solving, we introduce SolutionChat, a system that (1) visualizes discussion stages and featured opinions and (2) recommends contextually appropriate moderator messages. Results from a controlled lab study (n=55, 12 groups) suggest that participants' perceived discussion trackability was significantly higher with SolutionChat than without. Also, moderators provided better summarization with less effort and better managerial support using system-generated messages with SolutionChat than without. With SolutionChat, we envision untrained moderators to effectively facilitate chat-based discussions of important community matters.
Live streaming visual art such as drawing or using design software is gaining popularity. An important aspect of live streams is the direct and real-time communication between streamers and viewers. However, currently available text-based interaction limits the expressiveness of viewers as well as streamers, especially when they refer to specific moments or objects in the stream. To investigate the feasibility of using snapshots of streamed content as a way to enhance streamer-viewer interaction, we introduce Snapstream, a system that allows users to take snapshots of the live stream, annotate them, and share the annotated snapshots in the chat. Streamers can also verbally reference a specific snapshot during streaming to respond to viewers' questions or comments. Results from live deployments show that participants communicate more expressively and clearly with increased engagement using Snapstream. Participants used snapshots to reference part of the artwork, give suggestions on it, make fun images or memes, and log intermediate milestones. Our findings suggest that visual interaction enables richer experiences in live streaming.