The abundance of social media data and other information found on the web is changing the possibilities for social science research. Data found in blogs and other social media postings, users’ likes and dislikes, on-line behaviour and interaction patterns, network of contacts, and much more are readily available, which could potentially expand our knowledge. Do we have suitable methods for data collection, analysis, and visualisation, or appropriate means for interpreting what we find? Will the combination of multiple sources improve or distort the findings? What are the ethical and legal issues that need to be considered? These and many other questions require answers and have, in recent times, engaged scholarly investigations.
In line with others working on such issues, TACIT builds on the work that started in the project INCITE with the aim of bringing together multiple methods (such as topic modelling, altmetrics, bibliometrics, information fusion, user studies, and more) in order to identify and meaningfully interpret potential patterns and trends that may immerge from the analysis of web-based data.
As a use-case, initially, the focus will be placed on published material (including scholarly publications, blogs posts, EU produced documents, and some social media data) on the topic area of “Internet of Things”, but other areas may also be investigated as the project proceeds.