NLP (Natural Language Processing, or computer-assisted text analysis) and CV (Computer Vision, or visual analysis) are two subfields within Artificial Intelligence. Both approaches provide computational methods to analyse human texts, discourses, and visual input such as images and videos. NLP and CV help to better understand how digital transformation affects cultural entrepreneurs in Africa and Asia.
On the one hand, as the name suggests, NLP uses a corpus of digital texts (such as newspapers, announcements, or social media) to analyse and understand human language. In the context of cultural entrepreneurship, NLP algorithms can be used to analyse sentiments from tweets on given topics, to identify thematic areas published in books and scientific journals, or to measure the similarity and novelty of documents.
On the other hand, CV deals with digital images such as films or videos to extract information. Digitization and the proliferation of visual texts have opened up new opportunities for visual research. For example, in the context of cultural entrepreneurship, CV-based algorithms can be used to classify emotions, to predict the profitability of products from microentrepreneurs, or to measure similarity between films. CV can thus help add to or even spur on the next wave of the “visual turn” in various fields of scholarship.