There are lots of ways to display search results, and the familiar (if impoverished) ranked list of links with snippets is just one possibility. It doesn’t work particularly well for Twitter, for example because for many kinds of searches it’s hard to make sense of the tweets individually; instead, a more holistic approach is more appropriate.  I described in one such approach in Making Sense of Twitter Search (the position paper was co-authored with Miles Efron and was presented at a CHI 2010 workshop on microblogging) .

Paper.li is another approach to visualizing sets of Tweets. For a given topic or user, it identifies documents referred to by your followers and builds a two-column online newspaper-style layout out of those documents. It classifies documents by broad categories (media, education, technology, etc.) and prominent hashtags (e.g., #facebook), show the leading paragraphs or two of the document, and the person who tweeted it. Media such as YouTube videos are embedded directly into the layout. And, you can, of course, switch to a list view.

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Building effective search interfaces is hard, particularly when the goal is to support exploratory search rather than precision-oriented fact finding that the major search engines excel at. The challenge is to support a complex, evolving, information-rich task in a generalizable, understandable, and manageable way. We have some good ideas about how to make various components of information exploration interfaces; Marti Hearst’s book, for example, details much of the science and engineering that goes into good design for information seeking interfaces. None the less, the challenge of how to put these techniques into usable, effective and engaging interfaces that make it possible to do serious information seeking, remains.

A team of students at SIMS took a step in this direction with their Masters’ Thesis project called Migratory Words. The system allows people to search and browse a collection of news articles. Results are presented in a combination of visualizations and text lists that highlight terms, documents, and collections. The use terms and phrases that represent the ideas latent in the documents is a particularly welcome addition to traditional document-focused interfaces.

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