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Forecasting election results by studying brand importance in online news

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  • Fronzetti Colladon, Andrea

Abstract

This study uses the semantic brand score, a novel measure of brand importance in big textual data, to forecast elections based on online news. About 35,000 online news articles were transformed into networks of co-occurring words and analyzed by combining methods and tools from social network analysis and text mining. Forecasts made for four voting events in Italy provided consistent results across different voting systems: a general election, a referendum, and a municipal election in two rounds. This work contributes to the research on electoral forecasting by focusing on predictions based on online big data; it offers new perspectives regarding the textual analysis of online news through a methodology which is relatively fast and easy to apply. This study also suggests the existence of a link between the brand importance of political candidates and parties and electoral results.

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  • Fronzetti Colladon, Andrea, 2020. "Forecasting election results by studying brand importance in online news," International Journal of Forecasting, Elsevier, vol. 36(2), pages 414-427.
    • Handle: RePEc:eee:intfor:v:36:y:2020:i:2:p:414-427
    DOI: 10.1016/j.ijforecast.2019.05.013
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    References listed on IDEAS

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    10. Andrea Fronzetti Colladon & Giacomo Scettri, 2019. "Look inside. Predicting stock prices by analysing an enterprise intranet social network and using word co-occurrence networks," International Journal of Entrepreneurship and Small Business, Inderscience Enterprises Ltd, vol. 36(4), pages 378-391.
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    Cited by:

    1. A. Fronzetti Colladon & F. Grippa & B. Guardabascio & G. Costante & F. Ravazzolo, 2021. "Forecasting consumer confidence through semantic network analysis of online news," Papers 2105.04900, arXiv.org, revised Jul 2023.
    2. Rovelli, Paola & Benedetti, Carlotta & Fronzetti Colladon, Andrea & De Massis, Alfredo, 2022. "As long as you talk about me: The importance of family firm brands and the contingent role of family-firm identity," Journal of Business Research, Elsevier, vol. 139(C), pages 692-700.
    3. A. Fronzetti Colladon & S. Grassi & F. Ravazzolo & F. Violante, 2020. "Forecasting financial markets with semantic network analysis in the COVID-19 crisis," Papers 2009.04975, arXiv.org, revised Jul 2023.
    4. Zhang, Fang & Xia, Yan, 2022. "Carbon price prediction models based on online news information analytics," Finance Research Letters, Elsevier, vol. 46(PA).
    5. Piselli, C. & Fronzetti Colladon, A. & Segneri, L. & Pisello, A.L., 2022. "Evaluating and improving social awareness of energy communities through semantic network analysis of online news," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
    6. Andrea Fronzetti Colladon & Stefano Grassi & Francesco Ravazzolo & Francesco Violante, 2023. "Forecasting financial markets with semantic network analysis in the COVID‐19 crisis," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(5), pages 1187-1204, August.
    7. P. Rovelli & C. Benedetti & A. Fronzetti Colladon & A. De Massis, 2021. "As long as you talk about me: The importance of family firm brands and the contingent role of family-firm identity," Papers 2110.13815, arXiv.org.

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