  Various macroeconomic and institutional factors hinder FDI inflows, including
corruption, trade openness, access to finance, and political instability.
Existing research mostly focuses on country-level data, with limited
exploration of firm-level data, especially in developing countries. Recognizing
this gap, recent calls for research emphasize the need for qualitative data
analysis to delve into FDI determinants, particularly at the regional level.
This paper proposes a novel methodology, based on text mining and social
network analysis, to get information from more than 167,000 online news
articles to quantify regional-level (sub-national) attributes affecting FDI
ownership in African companies. Our analysis extends information on obstacles
to industrial development as mapped by the World Bank Enterprise Surveys.
Findings suggest that regional (sub-national) structural and institutional
characteristics can play an important role in determining foreign ownership.
