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Social Network Analysis and Mining

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01.12.2020 | Original Article

Promoting social media analytics in capital raising: a design science-based approach

verfasst von: Maria Prokofieva, Shah J. Miah

Erschienen in: Social Network Analysis and Mining | Ausgabe 1/2020

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Abstract

The study develops an artifact for decision support in capital raising campaigns that employs the power of social media analytics (SMA) to allow a better matching between investors and companies. The paper uses the design science approach to propose an artifact which pioneers the investment landscape by providing a method to focus investors’ attention on a selected set of companies and identifying investors groups for targeted capital raising. The artifact is based on SMA that employs machine learning techniques to provide insights from unstructured social media data and textual data from capital raising campaigns. The study demonstrated the application of the artifact using data from CrowdCube to assist with decision-making during capital raising campaigns. The application of the artifact is further validated through the focus group evaluation. Unlike existing approaches, the proposed artifact views investors as heterogeneous groups with different preferences and needs identified through social media.

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The participants were senior managers enrolled into the MBA degree at an Australian university. The average experience in the industry was 6 years, and each participant had IT background and was involved in capital raising events at different stages in their career.

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Titel: Promoting social media analytics in capital raising: a design science-based approach
verfasst von: Maria Prokofieva
Shah J. Miah
Publikationsdatum: 01.12.2020
Verlag: Springer Vienna
Erschienen in: Social Network Analysis and Mining / Ausgabe 1/2020
Print ISSN: 1869-5450
Elektronische ISSN: 1869-5469
DOI: https://doi.org/10.1007/s13278-020-00652-9

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