We introduce SentenTree, a novel technique for visualizing the content of unstructured social media text. SentenTree displays frequent sentence patterns abstracted from a corpus of social media posts. The technique employs design ideas from word clouds and the Word Tree, but overcomes a number of limitations of both those visualizations. SentenTree displays a node-link diagram where nodes are words and links indicate word co-occurrence within the same sentence. The spatial arrangement of nodes gives cues to the syntactic ordering of words while the size of nodes gives cues to their frequency of occurrence. SentenTree can help people gain a rapid understanding of key concepts and opinions in a large social media text collection. It is implemented as a lightweight application that runs in the browser.

Business ecosystems are characterized by large, complex, and global networks of firms, often from many different market segments, all collaborating, partnering, and competing to create and deliver new products and services. Given the rapidly increasing scale, complexity, and rate of change of business ecosystems, as well as economic and competitive pressures, analysts are faced with the formidable task of quickly understanding the fundamental characteristics of these interfirm networks. Existing tools, however, are predominantly query- or list-centric with limited interactive, exploratory capabilities. Guided by a field study of corporate analysts, we have designed and implemented dotlink360, an interactive visualization system that provides capabilities to gain systemic insight into the compositional, temporal, and connective characteristics of business ecosystems. dotlink360 consists of novel, multiple connected views enabling the analyst to explore, discover, and understand interfirm networks for a focal firm, specific market segments or countries, and the entire business ecosystem. System evaluation by a small group of prototypical users shows supporting evidence of the benefits of our approach. This design study contributes to the relatively unexplored, but promising area of exploratory information visualization in market research and business strategy.

After the news of Osama Bin Laden's death leaked through Twitter, many people wondered if Twitter would fundamentally change the way we produce, spread, and consume news. In this paper we provide an in-depth analysis of how the news broke and spread on Twitter. We confirm the claim that Twitter broke the news first, and find evidence that Twitter had convinced a large number of its audience before mainstream media confirmed the news. We also discover that attention on Twitter was highly concentrated on a small number of "opinion leaders" and identify three groups of opinion leaders who played key roles in spreading the news: individuals affiliated with media played a large part in breaking the news, mass media brought the news to a wider audience and provided eager Twitter users with content on external sites, and celebrities helped to spread the news and stimulate conversation. Our findings suggest Twitter has great potential as a news medium.