Impact investing is gaining momentum as an investment practice that optimizes both financial and social outcomes. However, the market is still in its emerging stage, and there is ambiguity regarding the definition of players and practices. In this paper, we adopt an investor identity perspective and use a linguistic approach to explore how social impact venture capitalists (SIVCs) communicate their identities and actions to their external stakeholders. Through a text mining analysis of the websites of 195 investors worldwide, our results reveal four types of investors who differ in terms of their social linguistic positioning and linguistic distinctiveness. Finally, by training a tree boosting machine learning model, we assess the extent to which the use of different linguistic styles is associated with website traffic.
The identity of Social Impact Venture Capitalists: exploring social linguistic positioning and linguistic distinctiveness through text mining / Toschi, Laura; Ughetto, Elisa; FRONZETTI COLLADON, Andrea. - In: SMALL BUSINESS ECONOMICS. - ISSN 0921-898X. - 60:(2023), pp. 1249-1280. [10.1007/s11187-022-00655-0]
The identity of Social Impact Venture Capitalists: exploring social linguistic positioning and linguistic distinctiveness through text mining.
UGHETTO, ELISA;
2023
Abstract
Impact investing is gaining momentum as an investment practice that optimizes both financial and social outcomes. However, the market is still in its emerging stage, and there is ambiguity regarding the definition of players and practices. In this paper, we adopt an investor identity perspective and use a linguistic approach to explore how social impact venture capitalists (SIVCs) communicate their identities and actions to their external stakeholders. Through a text mining analysis of the websites of 195 investors worldwide, our results reveal four types of investors who differ in terms of their social linguistic positioning and linguistic distinctiveness. Finally, by training a tree boosting machine learning model, we assess the extent to which the use of different linguistic styles is associated with website traffic.File | Dimensione | Formato | |
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https://hdl.handle.net/11583/2971505