Welcome to the Time Series workshop being offered at DH2019 by the Culture Analytics group! Much of the materials you will need for the workshop are available here, as will be notes, handouts, and possibly slides from the various talks. If you are viewing the GitHub pages version of the repository, you will want to browse to the repository itself to see everything as well as to make it easier to download or clone the contents of the repository.
If you enrolled in the workshop, please be sure to fill out the survey available on Google Drive so that we can prepare the best possible experience for everyone. Our goal is to expand the number of researchers who consider themselves to be working within the arena of culture analytics. The survey simply asks you to tell us about you: name, affiliation, research interest(s), and, if you have a link to a paper or a project description you would like others to know about.
If you are curious about some of the history of the culture analytics group, an included whitepaper offers some insight.
If you are in the workshop, then you know it is due to last much of the day, Tuesday, July 9 from 9:00 to 16:00. In order to make the day not feel long, however, we have scheduled a number of breaks as well as kept the talking to a minimum: we have tried to make the workshop as hands-on and focused on your work as possible.
|9:00||What is Culture Analytics? A talk designed to give a quick definition of the domain as we understand it and to highlight recent research by various individuals, many of whom are involved already with the group. John Laudun.|
|10:15||Measuring and Presenting time series of Astrophotography in Science, Public Discourse and (Virtual) Museums Exhibitions. Ekaterina Lapina-Kratasyuk & Leon Gurevitch.|
|10:30||Large Images Dataset over Time with PixPlot. Peter Leonard.|
|10:45||Time Series Clarisse Bardiot and Mila Oiva.|
|11:00||Automated Movement and Choreography Analysis of Video Data via Deep Learning Pose Detection. Peter Broadwell (Stanford University).|
|14:30||Time Series in Texts: From the Micro to the Macro. This hand-on tutorial offers participants a chance to explore how time series analysis can be used both to examine a single text and to examine a corpus. Examples include a short story, a novel, and a corpus of newspapers. Exercises include parsing texts in various ways and then deriving values through topics and sentiment and then understanding change over time through the Hurst exponent. Kristoffer Nielbo and Ross Deans Kristensen-McLachlan.|
|15:30||Workshop Wrap-up and Discussion|
Arnold: University of Richmond • Bardiot: Université de Valenciennes • Broadwell: Stanford University • Gurevitch: Victoria University of Wellington • Kristensen-McLachlan: Aarhus Universitet • Lapina-Kratasyuk: National Research University Higher School of Economics • Laudun: University of Louisiana • Leonard: Yale University • Nielbo: Aarhus Universitet • Oiva: Turun Yliopisto (University of Turku) •