Generating Cultural Personas from Social Data: A Perspective of Middle Eastern Users by Salminen, Joni, Sengun, Sercan, Kwak, Haewoon, Jansen, Bernard, An, Jisun, Jung, Soon-Gyo, Vieweg, Sarah, Harrell, D. Fox

“…First, we analyze millions of content interactions on YouTube to dynamically generate personas describing behavioral patterns of different demographic groups. …”
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Speech2Face: Learning the Face Behind a Voice by Oh, Taehyun, Dekel, Tali, Kim, Changil, Mosseri, Inbar, Freeman, William T, Rubinstein, Michael, Matusik, Wojciech

“…We design and train a deep neural network to perform this task using millions of natural Internet/Youtube videos of people speaking. During training, our model learns voice-face correlations that allow it to produce images that capture various physical attributes of the speakers such as age, gender and ethnicity. …”
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Data-driven interaction techniques for improving navigation of educational videos by Kim, Ju Ho, Guo, Philip J, Cai, Carrie Jun, Li, Shang-Wen (Daniel), Gajos, Krzysztof Z., Miller, Robert C.

“…With an unprecedented scale of learners watching educational videos on online platforms such as MOOCs and YouTube, there is an opportunity to incorporate data generated from their interactions into the design of novel video interaction techniques. …”
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Seeing the arrow of time by Pickup, Lyndsey C., Pan, Zheng, Wei, Donglai, Shih, YiChang, Zhang, Changshui, Zisserman, Andrew, Scholkopf, Bernhard, Freeman, William T.

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Whanau: A Sybil-Proof Distributed Hash Table by Kaashoek, M. Frans, Lesniewski-Laas, Christopher Tur

“…Simulation results, using social network graphs from LiveJournal, Flickr, YouTube, and DBLP, confirm the analytic results. Experimental results on PlanetLab confirm that the protocol can handle modest churn.…”
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Learnersourcing Subgoal Labels for How-to Videos by Weir, Sarah, Kim, Ju Ho, Miller, Robert C., Gajos, Krzysztof Z.

“…Websites like YouTube host millions of how-to videos, but the interfaces are not optimized for learning. …”
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Mahimahi: A Lightweight Toolkit for Reproducible Web Measurement by Winstein, Keith, Das, Somak, Goyal, Ameesh, Balakrishnan, Hari, Netravali, Ravi Arun, Sivaraman Kaushalram, Anirudh

“…A demo of Mahimahi recording and replaying a Web page over an emulated link can be found at http://youtu.be/vytwDKBA-8s. The source code and instructions to use Mahimahi are available at http://mahimahi.mit.edu/.…”
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Crowdsourcing step-by-step information extraction to enhance existing how-to videos by Nguyen, Phu Tran, Weir, Sarah, Guo, Philip J., Miller, Robert C., Gajos, Krzysztof Z., Kim, Ju Ho

“…We evaluated the workflow with Mechanical Turk, using 75 cooking, makeup, and Photoshop videos on YouTube. Results show that our workflow can extract steps with a quality comparable to that of trained annotators across all three domains with 77% precision and 81% recall.…”
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