Sensitivity Mining in Social Pulses to Address Cultural Heritage Competitive Intelligence

Abstract

The remarkable opportunities of discovering interesting knowledge from Big Data can be exploited in the Cultural Heritage CH domain, where Social Data Mining could advantage cultural organizations and operators with strategical elements for enjoying and attracting and enjoy visitors, as well as to support knowledge sharing and diffusion processes. A challenging and profitable direction may be combining Social Media Pulses Mining with Business Intelligence, to reveal the underlying key performance indicators, so leading to a 'competitive intelligence' whose application well fits with CH. The main contribution of the proposed research is the application of a Multidimensional Text Mining over multiple dimensions for social media pulses analysis. A set of exploratory studies were performed on textual messages Twitter to explore multiple kind of relations between terms, their compliance with CH, and finally estimating the Social Sensitivity Indicator to this domain and its polarity. Advanced technologies for Big Data processing were exploited.