Economics at your fingertips  

Unveiling the intellectual origins of Social Media-based innovation: insights from a bibliometric approach

Francesco Appio (), Antonella Martini, Silvia Massa and Stefania Testa
Additional contact information
Antonella Martini: University of Pisa
Silvia Massa: University of Genova (DIME)
Stefania Testa: University of Genova (DIME)

Scientometrics, 2016, vol. 108, issue 1, No 20, 355-388

Abstract: Abstract This article uses a bundle of bibliometric and text-mining techniques to provide a systematic assessment of the intellectual core of the Social Media-based innovation research field. The goal of this study is to identify main research areas, understand the current state of development and suggest potential future directions by analysing co-citations from 155 papers published between 2003 and 2013 in the most influential academic journals. The main clusters have been identified, mapped, and labelled. Their most active areas on this topic and the most influential and co-cited papers have been identified and described. Also, intra- and inter-cluster knowledge base diversity has been assessed by using indicators stemming from the domains of Information Theory and Biology. A t test has been performed to assess the significance of the inter-cluster diversity. Five co-existing research streams shaping the research field under investigation have been identified and characterized.

Keywords: Social Media; Innovation; Bibliometric analysis; Content analysis; Diversity analysis; 91-02 (search for similar items in EconPapers)
JEL-codes: M15 O32 (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (11) Track citations by RSS feed

Downloads: (external link) 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:

Ordering information: This journal article can be ordered from

DOI: 10.1007/s11192-016-1955-9

Access Statistics for this article

Scientometrics is currently edited by Wolfgang Glänzel

More articles in Scientometrics from Springer, Akadémiai Kiadó
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

Page updated 2022-11-20
Handle: RePEc:spr:scient:v:108:y:2016:i:1:d:10.1007_s11192-016-1955-9