Considering strength of weak ties (Granovetter 1973), the value of latent ties (boyd and Ellison 2007), and mechanisms by which social networks may seek to create desirable connection (McGaw 2012) it is important to consider the role of serendipity, the making of surprising but desirable discoveries.
Serendipity is anecdotally seen as a strong factor in the usefulness of social network sites but by nature, serendipity poses significant challenges to researchers seeking to isolate and understand learning triggered or facilitated by serendipitous happenstance. The value and difficulty of tracing the origins of useful information is well articulated in Greenhalgh and Peacock’s reflection on attempting to identify research sources for systematic review (Greenhalgh and Peacock 2005). Paul André and colleagues (André et al 2009), considering technical approaches to support and encourage serendipitous discovery, discuss the problems of understanding, defining and capturing moments of serendipity, particularly the insight or “sagacity” resulting from serendipitous discovery and the complexities of testing serendipity in laboratory conditions. They suggest approaches for facilitating serendipity, such as provision of “partially relevant” search results, personalisation and avoiding overloading the user (André et al 2009, pp. 4-6).
This idea that serendipitous discovery might be engineered by surfacing potentially interesting content, encouraging the searcher to divert from one path towards their own moment of discovery, has clear resonance with ZPD (Vygotsky 1978). The opportunities for serendipitous discovery proposed by André et al (2009), and those already emerging in the filtering of social network sites (e.g. McGaw 2012, Pariser 2011) and recommendation systems (e.g. Macmanus 2009) act as a form of scaffold for the user. Learning may not be the ultimate goal but the mechanisms, relationships and insight such systems enable have the potential to deliver serendipitous discovery and learning of more meaningful kinds.
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