Nathan Hahn


Casual Microtasking

Nathan Hahn, Shamsi Iqbal, Jaime Teevan

We've been working on the concept of "casual microtasking", or giving people small tasks to work on while they're doing other activities. In this paper, we explored this with Facebook -- we inserted small writing tasks into users' Facebook news feed, and gathered some responses about their experience with it.



Joseph Chang, Nathan Hahn, Adam Peerer, Niki Kittur

SearchLens is a replacement search interface for exploratory searches, where users might have multiple categories or criteria they need to fulfil. By building up "lenses", users can easily structure what they want into a query, assign weights, and then see how results matched their preferences.


Bento Browser

Nathan Hahn, Joseph Chang, Niki Kittur

Bento Browser is a prototype iOS application that helps people organize their complex online searching tasks. By removing the typical tab based structure of the browser and replacing it with a task hierarchy, we let people seamlessly organize, suspend and resume their searching tasks. Check it out on the App Store!


Intentionally Uncertain Input

Joseph Chang, Nathan Hahn, Niki Kittur

Highlighting can be mentally taxing for learners who are often unsure about how much information they needed to include. We introduce the idea of intentionally uncertain input in the context of highlighting on mobile devices. We present a system that uses force touch and fuzzy bounding boxes to support saving information while users are uncertain about where to highlight.



Joseph Chang, Nathan Hahn, Niki Kittur

Many crowd clustering approaches have difficulties providing global context to workers in order to generate meaningful categories. Alloy uses a sample-and-search technique to provide global context, and combines the deep semantic knowledge from human computation and the scalability of machine learning models to create rich structures from unorganized documents with high quality and efficiency

CHI 2016Honorable MentionPDF

Knowledge Accelerator (KA)

Nathan Hahn, Joseph Chang, Ji Eun Kim, Niki Kittur

The Knowledge Accelerator (KA) uses crowdworkers to synthesize different information sources on the web in response to a query. We prototyped this system in order to explore crowdsourcing complex, high context tasks in a microtask enviornment. Our system performed quite well, checkout the answers it produced!

CHI 2016Honorable MentionPDF


Kurt Luther, Nathan Hahn, Steven Dow, Niki Kittur

Learning new topics online can often be difficult -- even though their might be a wealth of information, it's often structured differently and the terminology used can be different. We utilized crowdworkers to synthesize this diverse information into a cohesive outline that retains the diversity of the original sources, but has a consistent structure.