Collective Action, Politics & Government

Political polarisation on social media: do birds of a feather flock together on Twitter?

by Anatoliy Gruzd 05/05/2015

Twitter’s connections tend to be less about strong social relationships and more about connecting with people for the purposes of commenting and information sharing.

by Anatoliy Gruzd 05/05/2015

Twitter has exploded in recent years, now boasting half a billion registered users. Like blogs and the world’s largest social networking platform, Facebook, Twitter has actively been used for political discourse during the past few elections in the US, Canada, and elsewhere but it differs from them in a number of significant ways. Twitter’s connections tend to be less about strong social relationships (such as those between close friends or family members), and more about connecting with people for the purposes of commenting and information sharing. Twitter also provides a steady torrent of updates and resources from individuals, celebrities, media outlets, and any other organisation seeking to inform the world as to its views and actions. This may well make Twitter particularly well suited to political debate and activity. Yet important questions emerge in terms of the patterns of conduct and engagement. Chief among them: are users mainly seeking to reinforce their own viewpoints and link with likeminded persons, or is there a basis for widening and thoughtful exposure to a variety of perspectives that may improve the collective intelligence of the citizenry as a result? Conflict and Polarisation Political polarisation often occurs in a so-called ‘echo chamber’ environment, in which individuals are exposed to only information and communities that support their own viewpoints, while ignoring opposing perspectives and insights. In such isolating and self-reinforcing conditions, ideas can become more engrained and extreme due to lack of contact with contradictory views and the exchanges that could ensue as a result. On the web, political polarisation has been found among political blogs, for instance. American researchers have found that liberal and conservative bloggers in the US tend to link to other bloggers who share their political ideology. For Kingwell, a prominent Canadian philosopher, the resulting dynamic is one that can be characterised by a decline in civility and a lessening ability for political compromise to take hold. He laments the emergence…

Education, Social Data Science

What are the limitations of learning at scale? Investigating information diffusion and network vulnerability in MOOCs

by Rebecca Eynon 21/10/2014

while a lot is known about the mechanics of group learning in smaller and traditionally organised online classrooms, fewer studies have examined participant interactions when learning “at scale.”

by Rebecca Eynon 21/10/2014

Millions of people worldwide are currently enrolled in courses provided on large-scale learning platforms (aka ‘MOOCs’), typically collaborating in online discussion forums with thousands of peers. Current learning theory emphasises the importance of this group interaction for cognition. However, while a lot is known about the mechanics of group learning in smaller and traditionally organised online classrooms, fewer studies have examined participant interactions when learning “at scale.” Some studies have used clickstream data to trace participant behaviour; even predicting dropouts based on their engagement patterns. However, many questions remain about the characteristics of group interactions in these courses, highlighting the need to understand whether—and how—MOOCs allow for deep and meaningful learning by facilitating significant interactions. But what constitutes a “significant” learning interaction? In large-scale MOOC forums, with socio-culturally diverse learners with different motivations for participating, this is a non-trivial problem. MOOCs are best defined as “non-formal” learning spaces, where learners pick and choose how (and if) they interact. This kind of group membership, together with the short-term nature of these courses, means that relatively weak inter-personal relationships are likely. Many of the tens of thousands of interactions in the forum may have little relevance to the learning process. So can we actually define the underlying network of significant interactions? Only once we have done this can we explore firstly how information flows through the forums, and secondly the robustness of those interaction networks: in short, the effectiveness of the platform design for supporting group learning at scale. To explore these questions, we analysed data from 167,000 students registered on two business MOOCs offered on the Coursera platform. Almost 8000 students contributed around 30,000 discussion posts over the six weeks of the courses; almost 30,000 students viewed at least one discussion thread, totalling 321,769 discussion thread views. We first modelled these communications as a social network, with nodes representing students who posted in the discussion forums, and edges (ie links) indicating…

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