Knowledge Gathering from Social Media to Improve Marketing in Agri-food Sector

Nowadays many small and medium companies are interested in entering into foreign markets to establish a brand presence, sell their products and beat the competitors. Before making such a marketing decision, marketing experts can be guided by the traditional analysis of reports but also by the Web, through the analysis of social networks, blogs, forums, etc. These sources can provide real-time information about the perception that users have of specific brands and products. As a result, there are several tools that can extract interesting information from these unstructured data. In this paper, we propose an innovative knowledge extraction architecture realized through the integration of some existing tools. The aim is to retrieve the more frequent concepts from unstructured sources, suggest other links of articles and images, with multi-language feature so that the research is language independent. The architecture provides a knowledge base of a specific domain, which is used to suggest concepts related to the research, and to filter the results obtained from the elaboration of the unstructured sources. We present a case of study related to marketing in agri-food sector, in order to illustrate how the software works, the results obtained, their interpretation and the managerial implications.