Using semiotics to analyze representational complexity in social media
Christine Abdalla Mikhaeil and
Richard Baskerville ()
Additional contact information
Christine Abdalla Mikhaeil: DRM - Dauphine Recherches en Management - Université Paris Dauphine-PSL - PSL - Université Paris Sciences et Lettres - CNRS - Centre National de la Recherche Scientifique, LEM - Lille économie management - UMR 9221 - UA - Université d'Artois - UCL - Université catholique de Lille - Université de Lille - CNRS - Centre National de la Recherche Scientifique
Richard Baskerville: Georgia State University - USG - University System of Georgia
Post-Print from HAL
Abstract:
Data from social media offer us multimedia data brimming with multiple layers of meanings. Social media enable rapid-fire digital communications. These communications are incredibly complex in content, form and meaning. This representational complexity is a stumbling block in data analysis that stands in the way of deeper explanations. These unstructured data, rich in social meanings, are as complex as the phenomena they represent. While it is possible to formulate an entire research methodology around semiotics, it is not always necessary. We can adapt semiotic analysis within existing methodologies. This paper offers and illustrates an analytical technique to address representational complexity that can be used in conjunction with other methodologies such as case study, ethnography, etc. This analytical technique espouses a critical realist philosophy to develop much needed, deeper explanations from qualitative data.
Keywords: Semiotics; Critical realism; Qualitative research; Data analysis; Representational complexity (search for similar items in EconPapers)
Date: 2019-12
Note: View the original document on HAL open archive server: https://hal.science/hal-02509212v1
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)
Published in Information and Organization, 2019, 29 (4), pp.100271. ⟨10.1016/j.infoandorg.2019.100271⟩
Downloads: (external link)
https://hal.science/hal-02509212v1/document (application/pdf)
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:hal:journl:hal-02509212
DOI: 10.1016/j.infoandorg.2019.100271
Access Statistics for this paper
More papers in Post-Print from HAL
Bibliographic data for series maintained by CCSD ().