In this work of Master thesis, we target three platforms related to software development (StackOverflow, GitHub, and Twitter). One of the first contributions is the design and building of a database on these three platforms, as a result of a complex phase of crawling, extraction and matching of 58K user profiles and their respective interaction networks. By capitalising on this dataset, we characterise different types of user expertise within and across professional-oriented online platforms, and operationalise the notions of ubiquitous and specialist expertise. We investigate how personal and relational triggering stimuli impact on the within- and across-network expert activities; how the users’ reputation vary across networks; and how they tend to form communities in different networks. Results show the importance of identifying and analysing different types of expertise traits across social platforms, as a mean to better characterise expertise and its online manifestation.

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