Exploring the Antecedents of Consumer Confidence through Semantic Network Analysis of Online News
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This article studies the impact of online news on social and economic consumer perceptions through the application of semantic network analysis. Using almost 1.3 million online articles on Italian media covering a period of four years, we assessed the incremental predictive power of economic-related keywords on the Consumer Confidence Index. We transformed news into networks of co-occurring words and calculated the semantic importance of specific keywords, to see if words appearing in the articles could anticipate consumers' judgements about the economic situation. Results show that economic-related keywords have a stronger predictive power if we consider the current households and national situation, while their predictive power is less significant with regards to expectations about the future. Our indicator of semantic importance offers a complementary approach to estimate consumer confidence, lessening the limitations of traditional survey-based methods.
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