Ramen is More Photogenic than Chicken Wings: A Winter Break Externship Report

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GroupLens externs with some of their favorite foods.

 

Guest written by Maryam Hedayati, Steph Herbers, Sophia Maymudes, and Anna Meyer.

 

Christmas is almost here. Do you know what most people won’t be doing on December 25th? Writing online restaurant reviews. Let’s dive deeper into the world of online restaurant reviews to learn more about this and other interesting trends. (more…)

SqueezeBands: Hugging Through the Screen

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A woman raises her hand towards a webcam during a videochat with a friend. Her hand is encased in a cloth device with shape memory alloy springs.
Lucy and Jackie demonstrate using SqueezeBands to send a high five! The camera detects mutual gestures like this one and creates a sensation of touch by squeezing and heating each person’s hand band.

 

When I Skype with my family, I really wish that I could reach through the screen to give them a hug! Instead, we sometimes have to pretend—we lean forward “hugging” the monitor or bring our hands towards the camera to do a virtual “high five.” What if you could actually feel some of that touch instead of just having to imagine it?

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Your feelings of connecting to a group can predict your future behavior

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Maybe you’ve joined a group recently could be a Taekwondo group, a wine tasting club, a fantasy football league, or whatever. Do you know that how people felt “connected” to a group before they joined can predict their future behavior in the group? Social psychologists have identified two conceptually distinct ways a member can connect with a group — identity-based attachment (e.g., “I feel connected to the Taekwondo group because I started to learn Taekwondo when I was a kid!”) and bonds-based attachment (e.g., “I feel connected to the wine tasting club because my best friend Daniel is a club member!”) — and worked to understand their causes and consequences. What we have done is study how connections between a person and an online group can predict that person’s future behavior.

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The more they try, the more they are likely to come back!!

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Are you trying to launch an online site for customers? Do you know that on an average, 60% of users do not return after using the site once?

In this research, we discover factors that predict whether first-time users return to MovieLens, our movie recommendation site.  A model based on these factors successfully predicts 70% of returning users (and non-returning ones).  Notably, the best single predictor of user return is the diversity of features explored in the user’s first session!  Along the way, we develop a process and a metric for activity diversity — one that can be applied to any site or context. Interested in further details?

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How do People Ask for Recommendations?

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While your TV’s remote might already have a microphone in it for voice commands, it is no replacement for a video store clerk. The current generation of devices respond to a limited set of commands, offer mostly shallow integration with deeper personalization, and may not understand complicated recommendation-seeking questions. Our research aims to develop techniques that can bring together voice recognition technologies, personalization, and advanced search features to provide more natural ways for people to discover new digital content. (more…)