Integrating SNA and Text Mining: Business Intelligence Through the SBS BI App
Andrea Fronzetti Colladon, Francesca Grippa
Leveraging the power of big data represents an opportunity for researchers and managers to reveal patterns and trends in social behaviors and consumer perceptions. This workshop shows how to successfully integrate Text Mining with Social Network Analysis for business and research. It presents the Semantic Brand Score (SBS) and other powerful methods and tools for analyzing semantic networks, studying brand/semantic importance, and performing advanced NLP tasks. The workshop also describes the functionalities of the SBS Business Intelligence App (SBS BI), designed to produce a wide range of analytics and mine textual data. We discuss several case studies and show how these methods have been used, for example, to predict tourism trends, select advertising campaign testimonials, or make economic, financial, and political forecasts. SBS BI analytical power extends beyond “brands”, comprising applications to study: commercial brands (e.g., Pepsi vs. Coke); products (e.g., pasta vs. pizza); personal brands (e.g., name and image of political candidates); set of words representing values (e.g., a company’s core values) or concepts related to societal trends (e.g., terms used in media communication that impact consumers’ feeling about the state of the economy). Combining text analysis with network science can change how we make decisions and manage organizations in the era of big data.
More info about the workshop is available here: https://learn.semanticbrandscore.com