| Autor: |
Achini Adikari, Donna Burnett, Darshana Sedera, Daswin de Silva, Damminda Alahakoon |
| Jazyk: |
angličtina |
| Rok vydání: |
2021 |
| Předmět: |
|
| Zdroj: |
International Journal of Information Management Data Insights, Vol 1, Iss 2, Pp 100022- (2021) |
| Druh dokumentu: |
article |
| ISSN: |
2667-0968 |
| DOI: |
10.1016/j.jjimei.2021.100022 |
| Popis: |
Social media encapsulates one of the most prominent human information behaviours that has rapidly evolved to create a new data-driven paradigm that uses data-intensive digital environments to communicate, collaborate, express opinions and support decisions. This has established social media as a unique information asset for value co-creation as it empowers individuals to actively express opinions and sentiment on all facets of interactions with an external entity. Despite recent research on the theoretical underpinnings of social media in open service innovation, practical demonstrations of actionable insights are limited, mainly due to the voluminous and unstructured nature of social media data. We address this limitation by presenting an evidence-based study that uses machine learning algorithms to generate actionable insights of strategic value from this data-driven paradigm. These outcomes provide fresh perspectives and new thinking that advances social media as an emergent information asset for end-to-end open innovation and incremental value co-creation. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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