Social networks and citizen election forecasting: the more friends the better
Article
Leiter, D., Murr, A., Rascon Ramirez, E. and Stegmaier, M. 2018. Social networks and citizen election forecasting: the more friends the better. International Journal of Forecasting. 34 (2), pp. 235-248. https://doi.org/10.1016/j.ijforecast.2017.11.006
Type | Article |
---|---|
Title | Social networks and citizen election forecasting: the more friends the better |
Authors | Leiter, D., Murr, A., Rascon Ramirez, E. and Stegmaier, M. |
Abstract | Most citizens correctly forecast which party will win a given election, and such forecasts usually have a higher level of accuracy than voter intention polls. How do citizens do it? We argue that social networks are a big part of the answer: much of what we know as citizens comes from our interactions with others. Previous research has considered only indirect characteristics of social networks when analyzing why citizens are good forecasters. We use a unique German survey and consider direct measures of social networks in order to explore their role in election forecasting. We find that three network characteristics – size, political composition, and frequency of political discussion – are among the most important variables when predicting the accuracy of citizens’ election forecasts. |
Publisher | Elsevier |
Journal | International Journal of Forecasting |
ISSN | 0169-2070 |
Publication dates | |
Online | 02 Feb 2018 |
01 Apr 2018 | |
Publication process dates | |
Deposited | 16 Jul 2018 |
Accepted | 17 Nov 2017 |
Output status | Published |
Accepted author manuscript | License |
Accepted author manuscript | License |
Copyright Statement | Copyright: © 2017 International Institute of Forecasters. Published by Elsevier B.V. This author's accepted manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ |
Digital Object Identifier (DOI) | https://doi.org/10.1016/j.ijforecast.2017.11.006 |
Language | English |
https://repository.mdx.ac.uk/item/87w02
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