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In this work we use emotional data coming from Twitter as auxiliary variable in a small area model to estimate Italian households’ share of food consumption expenditure (the proportion of food consumption expenditure on the total consumption expenditure) at the provincial level. We show that the use of Twitter data has a potential in predicting our target variable, reducing the estimated mean squared
error with respect to what obtained by the same working model without the Twitter data.