Behavioural Analysis of Multi-Source Social Network Data Using Object-Centric Behavioural Constraints and Data Mining Technique

摘要

Social media data or social data is the data generated by users of a social media platform. This significant amount of data produced by users shows their behavior on a particular platform, for example, Twitter, Facebook, and Instagram. Data mining techniques are prevalent in extracting knowledge from social data, but there is much scope in looking at the data from the process mining point of view. We have used a novel process mining technique called Object-Centric Behavioral Constraint modeling for analyzing live social data. Also, deviations from the actual model are analyzed using conformance checking. To bring both process mining and data mining together, we have also done lexicon-based sentiment analysis on the live data.