Abstract
The results of two Dutch elections are predicted by counting political party mentions from tweets. In an attempt to improve the predictions, gender and age information from the Twitter users is automatically derived and used to adapt the party counts to the demographics in the election turnout. The prediction improves only slightly in one of the elections where the correlation between election outcome and Twitter-based prediction was relatively lower to begin with (0.86 versus 0.97). The relatively inaccurate estimation of Twitter user age may hinder a larger improvement.
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Notes
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In this study we only studied gender and age because these are the two most basic demographic data and because these are the only two that are automatically retrievable to a certain extent.
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Acknowledgments
The authors would like to thank Dong Nguyen who provided the TweetGenie data, TNS-Nipo who provided the demographic data of the election turnout, Ruut Brandsma of allepeilingen.com for the polling information and Eline Pilaet, who did part of the demographic annotations of the political tweeters.
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Sanders, E., de Gier, M., van den Bosch, A. (2016). Using Demographics in Predicting Election Results with Twitter. In: Spiro, E., Ahn, YY. (eds) Social Informatics. SocInfo 2016. Lecture Notes in Computer Science(), vol 10047. Springer, Cham. https://doi.org/10.1007/978-3-319-47874-6_18
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