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Factors Affecting the Success of Social Machines

The final speaker in this Web Science 2016 session is Clare Hooper, whose interest is in 'social machines' as defined by Tim Berners-Lee: systems were people do the creative work, and machines take care of the administration. Social machines will exist in the context of problems to be solved; they may be created by single stakeholders (as in the case of Galaxy Zoo), while others arise in a more emergent fashion (from online communities).

Modelling Convergent Social Tagging Processes

Next up at Web Science 2016 is Paul Seitlinger, whose interest is in social tagging practices. These provide a valuable insight into human cognition and offer an opportunity to validate lab-based models 'in the wild'. One key question in this is how semantic stabilisation, or consensual use of tags, comes into being. This is influenced by the interplay of both human and non-human actors.

Understanding Music Recommender Systems as Cultural Intermediaries

The next Web Science 2016 presenter is Jack Webster, who focusses on music recommender systems. Such recommender systems could generate filter bubbles, but that threat is nothing new; the cultural intermediaries described by Pierre Bourdieu fulfilled very similar roles and could have engendered very similar patterns.

Matching Diverse Web Taxonomies

The next session at Web Science 2016 starts with Natalia Boldyrev, whose focus is on Web taxonomies. There are a number of different approaches to taxonomies, from traditional librarian approaches to user-generated taxonomies, and from hierarchical catalogues of terms to unordered tag clouds. Such taxonomies are also culturally predicated: the taxonomy for football-related books in the German Amazon is much more detailed than it is in Amazon US, for instance.

Social Media from the Anthropologist's Perspective

The final day of Web Science 2016 starts with a keynote by Daniel Miller, who contributes an anthropologist's perspective to the conference. He notes that especially when it comes to the popular discussion of Web technologies such as social media, there are many spurious claims about how they change social interactions – and anthropologists are called upon to make sense of these claims. Anthropology, he notes, is in fact the study of people as social networks: we are all of us embedded in our social relations with others, and it is these relations that anthropology examines and analyses.

This enables a process of 'holistic contextualisation', which aims to examine comprehensively why people do what they do, online and offline. This studiously avoids any simplistic concentrations on online or offline activities, as people are almost always operating across both spaces. One core principle of this is the idea of 'polymedia', which builds on the fact that cost and access barriers to most media have decreased to the point that people no longer choose their media based on such factors, but instead on other – social and moral – considerations. (The moral judgment comes in as people assess others' uses of specific media: is it appropriate to break up a relationship via social media, for instance?)

How Facebook Uses Computational Processes to Police Its Ads

The final Web Science 2016 keynote for today is by Daniel Olmedilla, whose work at Facebook is to police the ads being posted on the site. Ads are the only part of Facebook where inherently unsolicited content is pushed to users, so the quality of those ads is crucial – users will want relevant and engaging content, while advertisers need to see a return on investment. Facebook itself must ensure that its business remains scalable and sustainable.

Key problem categories are legally prohibited content (e.g. ads for illegal drugs); shocking and scary content; sexually suggestive material; violent and confronting content; offensive before-and-after images; ads with inappropriate language; and images containing a large amount of text.

Explaining Viewing and Sharing Dynamics for YouTube Videos

Finally for this session at Web Science 2016 we move to Sebastian Stommel, who begins by considering what we mean by Web science in the first place. He suggests that 'big data' serve as a macroscope: a new way of looking at things at scale, and an opportunity to create generative models to explain digital traces.

Simulating Heterogeneous-Intent Cascades

The next speaker at Web Science 2016 is Onur Varol, who points out the wide variety of purposes for which people use social media, and notes that we change our online persona and usage styles according to different communicative contexts. Can we match language style and user intent, then?

The Influence of Students' Social Networks on Group Participation

The next speaker at Web Science 2016 is Jenna Mittelmeier, whose focus is on cross-cultural collaboration. Group work has always been difficult, and the majority of online contributions are from a small subset of all users; this free riding by non-participants is especially problematic in educational settings that require all users to participate equally.

Predicting Twitter-Based Information Cascades

The next session at Web Science 2016 starts with a paper by Jure Leskovec on information cascades. Such cascades emerge as users of social media platforms (re)share content through their networks, and the prediction of such processes is traditionally very difficult.

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