Missing value or behaviour: how to increase the signal of social media data

Paolo Mariani () and Andrea Marletta ()
Additional contact information
Paolo Mariani: University of Milano-Bicocca
Andrea Marletta: University of Milano-Bicocca

METRON, 2022, vol. 80, issue 2, No 1, 139-151

Abstract: Abstract Social media has become a widespread element of people’s everyday life, which is used to communicate and generate contents. Among the several ways to express a reaction to social media contents, the “Likes” are critical. Indeed, they convey preferences, which drive existing markets or allow the creation of new ones. Nevertheless, the appreciation indicators have some complex features, as for example the interpretation of the absence of “Likes”. In this case, the lack of approval may be considered as a specific behaviour. The present study aimed to define whether the absence of Likes may indicate the presence of a specific behaviour through the contextualization of the treatment of missing data applied to real cases. We provided a practical strategy for extracting more knowledge from social media data, whose synthesis raises several measurement problems. We proposed an approach based on the disambiguation of missing data in two modalities: “Dislike” and “Nothing”. Finally, a data pre-processing technique was suggested to increase the signal of social media data.

Keywords: Social media; Like; Missing data; Celebrities’ pages (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s40300-021-00216-7 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

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:metron:v:80:y:2022:i:2:d:10.1007_s40300-021-00216-7

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/40300

DOI: 10.1007/s40300-021-00216-7

Access Statistics for this article

METRON is currently edited by Marco Alfo'

More articles in METRON from Springer, Sapienza Università di Roma
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().