I research, design and code technologies that can improve how we perceive and produce information. I design incentives to encourage positive user behavior through the user interface and diverse modalities to communicate information. My work focuses on news reporting, better engagement with information from news and search results, crowdsourcing journalism and remote reporting.
I am visiting Microsoft Research Fuse Labs to work on technologies for local communities, crowdsourcing local news and supporting local bloggers.
I finished my Master in Computer Science with a focus on Human Computer Interaction at the School of Engineering and Applied Science at Harvard. My past research focused on designing interfaces in information retrieval to encourage better queries and discovery of search results. I researched how users perceive opinions online. I used different ways of organizing information, analyzing user affect, and online user profiles to analyze how information is perceived. I also experimented with crowdsourcing, social network analysis, persuasive technologies, mobile computing and mining big data from the blogosphere.
May '13 This summer I will be interning at JPL/NASA working on interactive data visualization tools.
Apr'13 SIGIR 2013 paper accepted: "Looking Ahead: Query Preview in Exploratory Search", Pernilla Qvarfordt, Gene Golovchinsky, Tony Dunnigan, Elena Agapie
We explore a novel approach for producing news reports of geographic-specific events using locative crowdsourcing. We worked with local bloggers to identify people's needs and abilities to produce local stories. This work explores: the identification of basic templates for event reports, the task decomposition involved in creating them, the design of a system that automates the coordination of on-demand workforce to execute and produce said event reports. We evaluate the system by reporting on several events in different U.S. metropolitan areas.
This research analyzes how images are used to describe events. It particularly focuses on the memes that get generated throughout an event, the sources they come from and the threads of discussion they reflect.