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Computational semantic analysis was applied for measurements of pessimistic sentiments from business news. Using semantic tree method, the number of pessimistic and optimistic news was estimated for the analysis of the bearish and bullish stock markets. It was found that the number of pessimistic and optimistic macroeconomic news is very sensitive to the sharp changes of the market indices at the extreme market conditions. A new sentiment indicator was constructed for quantitative measurementsdoi:10.5539/ibr.v7n5p103 fatcat:ybuduohytrfe7grywghkkoux5e