Electoral Forecasting Using a Novel Temporal Attenuation Model: Predicting the US Presidential Elections

by   Alexandru Topirceanu, et al.

Electoral forecasting is an ongoing scientific challenge with high social impact, as current data-driven methods try to efficiently combine statistics with economic indices and machine learning. However, recent studies in network science pinpoint towards the importance of temporal characteristics in the diffusion of opinion. As such, we combine concepts of micro-scale opinion dynamics and temporal epidemics, and develop a novel macro-scale temporal attenuation (TA) model, which uses pre-election poll data to improve forecasting accuracy. Our hypothesis is that the timing of publicizing opinion polls plays a significant role in how opinion oscillates, especially right before elections. Thus, we define the momentum of opinion as a temporal function which bounces up when opinion is injected in a multi-opinion system of voters, and dampens during states of relaxation. We validate TA on survey data from the US Presidential Elections between 1968-2016, and TA outperforms statistical methods, as well the best pollsters at their time, in 10 out of 13 presidential elections. We present two different implementations of the TA model, which accumulate an average forecasting error of 2.8-3.28 points over the 48-year period. Conversely, statistical methods accumulate 7.48 points error, and the best pollsters accumulate 3.64 points. Overall, TA offers increases of 23-37 art. We show that the effectiveness of TA does not drop when relatively few polls are available; moreover, with increasing availability of pre-election surveys, we believe that our TA model will become a reference alongside other modern election forecasting techniques.


page 1

page 2

page 3

page 4


Econometrics of Machine Learning Methods in Economic Forecasting

This paper surveys the recent advances in machine learning method for ec...

Validating argument-based opinion dynamics with survey experiments

The empirical validation of models remains one of the most important cha...

Extremism definitions in opinion dynamics models

There are several opinion dynamics models where extremism is defined as ...

Demarcating Endogenous and Exogenous Opinion Dynamics: An Experimental Design Approach

The networked opinion diffusion in online social networks (OSN) is often...

Blending search queries with social media data to improve forecasts of economic indicators

The forecasting of political, economic, and public health indicators usi...

Towards Accurate Deceptive Opinion Spam Detection based on Word Order-preserving CNN

As a mainly network of Internet naval activities, the deceptive opinion ...

Disappearing errors in a conversion model

The same basic differential equation model has been adapted for time-dep...

Please sign up or login with your details

Forgot password? Click here to reset