An analysis of interactions within and between extreme right communities in social media

Many extreme right groups have had an online presence for some time through the use of dedicated websites. This has been accompanied by increased activity in social media websites in recent years, which may enable the dissemination of extreme right content to a wider audience. In this paper, we present exploratory analysis of the activity of a selection of such groups on Twitter, using network representations based on reciprocal follower and mentions interactions. We find that stable communities of related users are present within individual country networks, where these communities are usually associated with variants of extreme right ideology. Furthermore, we also identify the presence of international relationships between certain groups across geopolitical boundaries

Social Bootstrapping: How Pinterest and Last.fm Social Communities Benefit by Borrowing Links from Facebook

How does one develop a new online community that is highly engaging to each user and promotes social interaction? A number of websites offer friend-finding features that help users bootstrap social networks on the website by copying links from an established network like Facebook or Twitter. This paper quantifies the extent to which such social bootstrapping is effective in enhancing a social experience of the website. First, we develop a stylised analytical model that suggests that copying tends to produce a giant connected component (i.e., a connected community) quickly and preserves properties such as reciprocity and clustering, up to a linear multiplicative factor. Second, we use data from two websites, Pinterest and Last.fm, to empirically compare the subgraph of links copied from Facebook to links created natively. We find that the copied subgraph has a giant component, higher reciprocity and clustering, and confirm that the copied connections see higher social interactions. However, the need for copying diminishes as users become more active and influential. Such users tend to create links natively on the website, to users who are more similar to them than their Facebook friends. Our findings give new insights into understanding how bootstrapping from established social networks can help engage new users by enhancing social interactivity.Comment: Proc. 23rd International World Wide Web Conference (WWW), 201

The fourth V, as in evolution: How evolutionary linguistics can contribute to data science

The paper explores the importance of closer interaction between data science and evolutionary linguistics, pointing to the potential benefits for both disciplines. In the context of big data, the microblogging social networking service – Twitter – can be treated as a source of empirical input for analyses in the field of language evolution. In an attempt to utilize this kind of disciplinary interplay, I propose a model, which constitutes an adaptation of the Iterated Learning framework, for investigating the glossogenetic evolution of sublanguages.

The fourth V, as in evolution: How evolutionary linguistics can contribute to data science

The paper explores the importance of closer interaction between data science and evolutionary linguistics, pointing to the potential benefits for both disciplines. In the context of big data, the microblogging social networking service – Twitter – can be treated as a source of empirical input for analyses in the field of language evolution. In an attempt to utilize this kind of disciplinary interplay, I propose a model, which constitutes an adaptation of the Iterated Learning framework, for investigating the glossogenetic evolution of sublanguages.