No abstract

Real-time information from microblogs like Twitter is useful for different applications such as market research, opinion mining, and crisis management. For many of those messages, location information is required to derive useful insights. Today, however, only around 1% of all tweets are explicitly geotagged. We propose the first multi-indicator method for determining (1) the location where a tweet was created as well as (2) the location of the user's residence. Our method is based on various weighted indicators, including the names of places that appear in the text message, dedicated location entries, and additional information from the user profile. An evaluation shows that our method is capable of locating 92% of all tweets with a median accuracy of below 30km, as well as predicting the user's residence with a median accuracy of below 5.1km. With that level of accuracy, our approach significantly outperforms existing work.

No abstract

Bend, stiffen, resize (b) EarPut (inside) (c) Augmented Earphones (d) Augmented Glass (a) EarPut Wireless Sensor Arc-shaped Board (12 Touch Points) Wire Flexible form factor Figure 1: (a) EarPut is a novel interface concept and hardware prototype that instruments the ear as an interactive surface for touch-based interactions. (b) The flexible form factors allows users to bend and stiffen the earpiece to account for differently shaped ears. (c) EarPut serves as an interaction enabler for otherwise non-interactive devices such as ordinary earphones. (d) It complements interaction capabilities of head-worn devices, e.g. as an extension to Glass' touch-enabled frame.

No abstract