“Having chatted with the director as well as the data scientists on the team, I found that they are very nice and open in terms of what I am interested in and what I want to do in this particular field,” said Liao. “So I was in.”
Liao’s role at The Washington Post was to leverage data-driven approaches to help the newsroom. Specifically, he worked on news timeline summarization, which automatically generates dated summaries for news events, such as the North Korea summit or the U.S.-China trade war.
His research helps journalists create these timelines, because generally a news event can range from months to years and involve thousands of news articles. The time and effort expended by the journalists can be saved with an auto-generation tool.
“My internship is more like problem-driven and exploring on different approaches, so it is hard to describe a day-to-day task,” said Liao.
As part of his internship duties, Liao built prediction models that helped the daily newspaper better understand which type of stories and content would be the most interesting to their readers. According to Liao, the process begins with a problem/issue that is of interest to The Washington Post.
With the help of journalists throughout the company, Liao explained, he and the data sciences team processed and analyzed the discussion and input of the journalist, to either improve existing methods for solutions or adapt to them for higher rates of efficiency. At the end, his team would produce a new prediction model for The Washington Post to build from.
“Through literature reviews, we would determine intended approaches, adapt them into our system, improve existed methods, and evaluate the solutions,” said Liao “Finally, we will deploy them to production and do iteration with feedbacks. It is very similar to conducting research at labs.”
Liao shared that the education he’s received from the College of IST prepared him with the necessary skills for tackling the complex projects at his internship. Reviewing past research and formulating new questions are two major components of his daily responsibilities at The Washington Post, and are also key aspects in the IST courses he takes.
Understanding mass user music consumption
Spotify, one of the world’s leading streaming music services, founded by the Swedish company Spotify Technology, is known for its vast music library. According to College of IST doctoral student Lu Liu, who served as a data scientist this past summer, innovative technology is a key part of the company's success.