Enhancing directed content sharing on the web
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Regroup: interactive machine learning for on-demand group creation in social networks
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
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The friend list of many social network users can be very large. This creates challenges when users seek to direct their social interactions to friends that share a particular interest. We present a self-organizing online tool that by incorporating ideas from user modeling and data visualization allows a person to quickly identify which friends best match a social query, enabling precise and efficient directed social interactions. To cover the different modalities in which our tool might be used, we introduce two different interactive visualizations. One view enables a human-in-the-loop approach for result analysis and verification, and, in a second view, location, social affiliations and "personality" data is incorporated, allowing the user to quickly consider different social and spatial factors when directing social queries. We report on a qualitative analysis, which indicates that transparency leads to an increased effectiveness of the system. This work contributes a novel method for exploring online friends.