2018-07-18: HyperText and Social Media (HT) Trip Report

Human Factors in Hypertext (HUMAN) Opinion Mining, Summarization and Diversification Narrative and Hypertext I attended the Opinion Mining, Summarization and Diversification workshop. The workshop started with a talk titled: "On Reviews, Ratings and Collaborative Filtering," presented by Dr. Oren Sar Shalom, principal data scientist at Intuit, Israel. Next, Ophélie Fraisier, a PhD student studying stance analysis on social media at Paul Sabatier University, France, presented: "Politics on Twitter: A Panorama," in which she surveyed methods of analyzing tweets to study and detect polarization and stances, as well as election prediction and political engagement. He showed how collective opinion mining can help capture the drivers behind opinions as opposed to individual opinion mining (or sentiment) which identifies single individual attitudes toward an item. I thank a million people! https://t.co/I3quPp6nw3 He also discussed a phenomenon in which people are likely to lie to pollsters (social desirability bias) but are honest to Google ("Digital Truth Serum") because Google incentivizes telling the truth. The paper sessions followed the keynote with two full papers and a short paper presentation. Google search data as "digital truth serum" - while reporting of child abuse go down at the recession time, Google search data indicates that real child abuse increases https://t.co/DQQoAotZqB However, it feels more like a research talk rather than a #keynote. Though still interesting, I'd rather hear about a #vision for this area of #research.