In 2015, Twitter introduced the hashtag #culturalheritage, thus giving an empirical evidence of the increasing interest of users towards cultural topics and events. In the last years, while an increasing number of studies and initiatives about tweets, in both the academic and business worlds, raised, a lack of quantitative studies devoted to assess their potential and effectiveness for organizations promoting Cultural Heritage was recorded. So, this work describes a quantitative analysis of tweets which combines NLP, semantic technologies, geo-referencing and temporal analysis. The initial set of measures aims to characterize people's interest and sensitivity into CH subjects, geographical density of CH resources, and temporal proximity to CH-related events. Furthermore, in order to evidence the relevance of the obtained results, they are compared to similar measures computed for different but more general topics - such as Medicine - while at the same time entail a certain specificity of interest, which cannot be confused with reactions to common mainstream, glamour or massive-impressive events (earthquakes, political elections, wars, amazing news). This kind of analysis was focused on huge datasets of tweets, issued in a long period of time from geographical areas of Italy having different densities of CH resources, The results encourage and sustain a Business-Intelligence approach which is suitable for both no-profit ad business oriented organizations, such as those involved in the DATABENC District.

What's the Matter with Cultural Heritage Tweets? An Ontology - Based Approach for CH Sensitivity Estimation in Social Network Activities

Marulli F.
Methodology
;
2016

Abstract

In 2015, Twitter introduced the hashtag #culturalheritage, thus giving an empirical evidence of the increasing interest of users towards cultural topics and events. In the last years, while an increasing number of studies and initiatives about tweets, in both the academic and business worlds, raised, a lack of quantitative studies devoted to assess their potential and effectiveness for organizations promoting Cultural Heritage was recorded. So, this work describes a quantitative analysis of tweets which combines NLP, semantic technologies, geo-referencing and temporal analysis. The initial set of measures aims to characterize people's interest and sensitivity into CH subjects, geographical density of CH resources, and temporal proximity to CH-related events. Furthermore, in order to evidence the relevance of the obtained results, they are compared to similar measures computed for different but more general topics - such as Medicine - while at the same time entail a certain specificity of interest, which cannot be confused with reactions to common mainstream, glamour or massive-impressive events (earthquakes, political elections, wars, amazing news). This kind of analysis was focused on huge datasets of tweets, issued in a long period of time from geographical areas of Italy having different densities of CH resources, The results encourage and sustain a Business-Intelligence approach which is suitable for both no-profit ad business oriented organizations, such as those involved in the DATABENC District.
2016
978-1-4673-9721-6
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11591/442614
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