Several authors have shown better results in forecasting economic variables by considering the sentiment values in their models. Few studies have focused on the identification of the causes which explain opinions and beliefs. In this paper, we propose a methodological framework based on Distributed Lag (DL) models in order to identify dynamic causal effects in the case of temporal aggregation of sentiment values.

Temporal sentiment analysis with distributed lag models

Michelangelo Misuraca;
2019

Abstract

Several authors have shown better results in forecasting economic variables by considering the sentiment values in their models. Few studies have focused on the identification of the causes which explain opinions and beliefs. In this paper, we propose a methodological framework based on Distributed Lag (DL) models in order to identify dynamic causal effects in the case of temporal aggregation of sentiment values.
9788891915108
semantic polarity, social media, causality, dynamic models, textual data
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11770/294156
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