Social networks provide opportunities to overshare information in a secondhand nature as information passes from primary to secondary to tertiary sources. This information can be supplemented with geographical information to obtain the approximate location of the primary information source without the primary source's consent, presenting a potential breach of privacy. Messages regarding severe illness were obtained from the popular social media site Twitter to understand how sensitive information may propagate unregulated through secondhand information sharing. Results indicate that 59% of tweets concerning severe illness are Retweets distributed without explicit consent from the primary source. A majority of these Retweets were propagated by family and friends of the primary source.

Precise selection is one of the key difficulties of touch-based interaction. In some cases (such as interacting with a map-based interface), precise selection is crucial for the correct specification of information. This work investigates the difference in user input error and speed for line drawing tasks using touch and mouse-based interaction. A parameterized method of solving the nearest-point-on-a-curve problem was developed in order to obtain a quantifiable error difference between mouse and touch-based interaction for line drawing tasks. A user study was conducted and determined that mouse-based interaction occurs at a slower rate of speed and results in less error than touch-based interaction for line drawing tasks.

The objective is to develop a mobile human-robot interface that is optimized for multi-touch input. Our existing interface was designed for mouse and keyboard input and was later adopted for voice and touch interaction. A new multi-touch interface permits multi-touch gestures, for example zooming and panning a map, and robot task specific touch interactions. An initial user evaluation found that the multi-touch interface is preferred and yields superior performance.