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And the final paper in this Web Science 2016 session is by Katrin Weller and me. Below are our slides and abstract, and a link to the full paper:

Twitter as a First Draft of the Present – and the Challenges of Preserving It for the Future from Axel Bruns

This paper provides a framework for understanding Twitter as a historical source. We address digital humanities scholars to enable the transfer of concepts from traditional source criticism to new media formats, and to encourage the preservation of Twitter as a cultural artefact. Twitter has established itself as a key social …

The third presenter in this Web Science 2016 session is Tu Ngoc Nguyen, who reintroduces us to the Internet Archive's Wayback Machine. This is a useful service, but searching it is not necessarily straightforward. Is it possible to draw on the non-content features to improve search results?

The project drew on the full archive for the German Web, and utilised a number of assessment techniques to assess and rank documents based on twenty non-content features. I'm frankly unable to understand the numerical data presented in the tables here, but from what I do understand the use of these additional …

The next WebSci 2016 presenters are Katharina Kinder-Kurlanda and Katrin Weller, who argue that it is necessary to address the digital divides in data accessibility in social media research. They interviewed a large number of social media researchers, and what emerges from this work is that much data sharing is already taking place, but under varying circumstances.

From a methodological point of view, how can we document such sharing to ensure reproducibility? Legally, how can we make such sharing practices sustainable and non-infringing? Ethically, how can we ensure that such data sharing does no harm and lives up to the …

The next WebSci 2016 paper session starts with a presentation by Pei Zhang, which introduces what she calls the Content-Linking-Context model, or CLC. The context for this is legislation such as the Digital Millennium Copyright Act (DMCA) and the European e-Commerce Directive, as well as various national legislation in the EU.

The DMCA requires services providers to take down content on request expeditiously, even without verification of copyright infringement claims, and providers such as Google and Dailymotion are known to act on such requests, but there is little information about the criteria they use to vet requests. Can automated systems …

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 …

It's a cool morning in Germany, and I'm in Hannover for the opening of the 2016 Web Science conference, where later today my colleague Katrin Weller and I will present our paper calling for more efforts to preserve social media content as a first draft of the present. But we start with an opening keynote by Yahoo!'s Ricardo Baeza-Yates, on Data and Algorithmic Bias in the Web.

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 …