Number of co-authors:11
Number of publications with 3 favourite co-authors:Bongwon Suh:3Lichan Hong:3Ed H. Chi:3
Sanjay Kairam's 3 most productive colleagues in number of publications:Peter Pirolli:46Ed H. Chi:29Jeffrey Heer:27
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Publications by Sanjay Kairam (bibliography)
Kairam, Sanjay, MacLean, Diana, Savva, Manolis and Heer, Jeffrey (2012): GraphPrism: compact visualization of network structure. In: Proceedings of the 2012 International Conference on Advanced Visual Interfaces 2012. pp. 498-505. Available online
Visual methods for supporting the characterization, comparison, and classification of large networks remain an open challenge. Ideally, such techniques should surface useful structural features -- such as effective diameter, small-world properties, and structural holes -- not always apparent from either summary statistics or typical network visualizations. In this paper, we present GraphPrism, a technique for visually summarizing arbitrarily large graphs through combinations of 'facets', each corresponding to a single node- or edge-specific metric (e.g., transitivity). We describe a generalized approach for constructing facets by calculating distributions of graph metrics over increasingly large local neighborhoods and representing these as a stacked multi-scale histogram. Evaluation with paper prototypes shows that, with minimal training, static GraphPrism diagrams can aid network analysis experts in performing basic analysis tasks with network data. Finally, we contribute the design of an interactive system using linked selection between GraphPrism overviews and node-link detail views. Using a case study of data from a co-authorship network, we illustrate how GraphPrism facilitates interactive exploration of network data.
© All rights reserved Kairam et al. and/or ACM Press
Convertino, Gregorio, Kairam, Sanjay, Hong, Lichan, Suh, Bongwon and Chi, Ed H. (2010): Designing a cross-channel information management tool for workers in enterprise task forces. In: Proceedings of the 2010 International Conference on Advanced Visual Interfaces 2010. pp. 103-110. Available online
This paper presents a research project on the design of a cross-channel information management tool for knowledge workers: we focus on IT services professionals in a large enterprise who work in multiple ad hoc task forces. Through three rounds of investigation, we characterized their work practices and needs, specified their requirements for a cross-channel information management tool, and designed and evaluated a prototype to address these needs. We found that these workers shared the problem of managing information across multiple channels, requiring better support for aggregating, filtering, and organizing this information. We report the requirements elicited and the prototypes built during the design process.
© All rights reserved Convertino et al. and/or their publisher
Hong, Lichan, Convertino, Gregorio, Suh, Bongwon, Chi, Ed H. and Kairam, Sanjay (2010): FeedWinnower: layering structures over collections of information streams. In: Proceedings of ACM CHI 2010 Conference on Human Factors in Computing Systems 2010. pp. 947-950. Available online
Information overload is a growing threat to the productivity of today's knowledge workers, who need to keep track of multiple streams of information from various sources. RSS feed readers are a popular choice for syndicating information streams, but current tools tend to contribute to the overload problem instead of solving it. We introduce FeedWinnower, an enhanced feed aggregator that helps readers to filter feed items by four facets (topic, people, source, and time), thus facilitating feed triage. The combination of the four facets provides a powerful way for users to slice and dice their personal feeds. In addition, we present a formative evaluation of the prototype conducted with 15 knowledge workers in two different organizations.
© All rights reserved Hong et al. and/or their publisher
Bernstein, Michael S., Suh, Bongwon, Hong, Lichan, Chen, Jilin, Kairam, Sanjay and Chi, Ed H. (2010): Eddi: interactive topic-based browsing of social status streams. In: Proceedings of the 2010 ACM Symposium on User Interface Software and Technology 2010. pp. 303-312. Available online
Twitter streams are on overload: active users receive hundreds of items per day, and existing interfaces force us to march through a chronologically-ordered morass to find tweets of interest. We present an approach to organizing a user's own feed into coherently clustered trending topics for more directed exploration. Our Twitter client, called Eddi, groups tweets in a user's feed into topics mentioned explicitly or implicitly, which users can then browse for items of interest. To implement this topic clustering, we have developed a novel algorithm for discovering topics in short status updates powered by linguistic syntactic transformation and callouts to a search engine. An algorithm evaluation reveals that search engine callouts outperform other approaches when they employ simple syntactic transformation and backoff strategies. Active Twitter users evaluated Eddi and found it to be a more efficient and enjoyable way to browse an overwhelming status update feed than the standard chronological interface.
© All rights reserved Bernstein et al. and/or their publisher
Evans, Brynn M., Kairam, Sanjay and Pirolli, Peter (2009): Exploring the cognitive consequences of social search. In: Proceedings of ACM CHI 2009 Conference on Human Factors in Computing Systems 2009. pp. 3377-3382. Available online
To what extent can social interactions augment people's natural search experiences? What factors influence the decision to turn to a friend for help? Our paper presents the preliminary results of a social sensemaking task that begin to address such questions by examining the cognitive consequences of social search.
© All rights reserved Evans et al. and/or ACM Press
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