What Can Social Media Data Add to the Knowledge of Arts and Humanities? An Empirical Investigation on Twitter at Teatro Alla Scala
Deborah Agostino and
Michela Arnaboldi
Additional contact information
Deborah Agostino: Politecnico di Milano
Michela Arnaboldi: Politecnico di Milano
A chapter in Knowledge Management, Arts, and Humanities, 2019, pp 197-213 from Springer
Abstract:
Abstract Social media, considered as a representative example of big data with their high volumes, high velocity and high variety features, are continuously receiving attention in the arts and humanities literature. While studies on the potentialities of social media to enhance audience engagement, informal learning or marketing activities in arts and cultural organisations are growing, there is limited evidence on the opportunities provided by data extracted from social media to enhance knowledge management in the arts and humanities. Acknowledging this gap, this chapter aims at understanding if and how social media data can contribute to generating new knowledge in the arts and humanities with a specific investigation on Twitter at Teatro Alla Scala. The results of the analysis are twofold. First, this study proposes a methodology to approach social media, by detailing the phases for data understanding and extraction, and the methodological approach to enhance data reliability. Second, this study identifies a set of key performance indicators that can be computed starting from social media data; the proposed indicators are finalised to develop a better knowledge of the network of social media users connected with the investigated organisation.
Keywords: Social media; Arts; Culture; Knowledge management; Big data; Performance measurement (search for similar items in EconPapers)
Date: 2019
References: Add references at CitEc
Citations:
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:kmochp:978-3-030-10922-6_10
Ordering information: This item can be ordered from
http://www.springer.com/9783030109226
DOI: 10.1007/978-3-030-10922-6_10
Access Statistics for this chapter
More chapters in Knowledge Management and Organizational Learning from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().