The final speaker in this WebSci 2016 session is Ramine Tinati, whose focus is on citizen science platforms. Citizen science itself has been around for hundreds of years, but more recent developments in online crowdsourcing techniques have enabled even greater mass participation in such scientific activities; one early success in this was Zooniverse, which asks users for help in classifying galaxy types.
The platform studied by this paper is Eyewire, which asks users to complete puzzles that help in visually mapping the human brain. The platform also includes a real-time chat interface that connects players with each other …
The next paper in this WebSci 2016 session is presented by Mariana Arantes, whose interest is in the matching of video ads to YouTube videos. Such ads are displayed before some YouTube videos, and they can often be stopped after a set number of seconds. How do users consume these ads? How does their popularity change over time? What is the relationship between videos and ads, and does a better content match mean that ads are more likely to be watched all the way through?
It is difficult to investigate this given the poor range of data provided by the …
We start the first paper session at WebSci 2016 with a paper by Guanliang Chen that examines learner engagement with Massively Open Online Courses (MOOCs). These generate a great deal of data about learner engagement during the MOOC itself, but there's very little information about learners before and after this experience. Can we use external social Web data to identify and profile these learners, in order to better customise the learning experience for them?
The biggest challenge in this is to identify the learners across diverse social media platforms. There are some possible approaches: explicit matching based on public email …
Ricardo begins by pointing out that all data have a built-in bias; additional bias is added in the data processing and interpretation. For instance, some researchers working with Twitter data then extrapolate …
