Abstract

In the global pursuit of sustainability, the role of private sector capital is pivotal, necessitating a shift in financial flows towards sustainable initiatives. However, the proliferation of greenwashing undermines trust among investors and consumers alike. The detection and mitigation of greenwashing demand robust automated systems. Nonetheless, this endeavor is challenging in absence of clear definitions, limited availability of high quality data, and the qualitative nature of sustainability claims. In contrast, the field of fake news detection, facing similar obstacles, has undergone substantial methodological evolution. Employing a sys- tematic mapping approach, we categorize existing concepts from the greenwash- ing and fake news domain, unveiling similarities and distinctions. Our findings contribute to the development of effective greenwashing detection methods by establishing the conceptual foundation to transfer methodological advancements from fake news detection to the realm of greenwashing. Furthermore, we offer promising research avenues in the domains of greenwashing, fake news and their intersection.

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