How Much Can Social Media Improve Poll Forecasting? You’ll Be Surprised

How Much Can Social Media Improve Poll Forecasting? You’ll Be Surprised

Introduction

In a previous post[1], I discussed the difference between predicting and forecasting, the latter being what I am most interested in. I showed that by using Twitter as an additional source of data it was possible to forecast polls in the June 12 Ontario election 24-48 hours before they are available. The forecasts derived from the Twitter-based model accurately tracked the aggregate polls.

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Right Here, Right Now: How Social Media is Great at Forecasting Polls

Right Here, Right Now: How Social Media is Great at Forecasting Polls

Introduction

Back in June, Ontario held an election for its provincial government and by extension its premier (equivalent to a state governor). There were strong candidates from the three main parties: Kathleen Wynne, the Liberal incumbent; Tim Hudak, representing the Progressive Conservatives; and Andrea Horwath of the New Democatic Party (NDP). Election day was June 12 and the results were 38.7% for the Liberals, 31.2% for the Conservatives, and 23.7% for the NDP.
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Forget the Phone: Social Media is a More Accurate Way to Predict Vote Results

Forget the Phone: Social Media is a More Accurate Way to Predict Vote Results

Introduction

Previously I developed a model to predict who would get voted off American Idol based on what people were saying on Twitter[1].

To do this, I created a random “focus group” of American Idol fans who are active on Twitter. Each week I looked to see who this group was talking about. Since raw counts can sometime be misleading, I used a simple model for conversation as an exogenous variable for the autoregression. Essentially, it says that each week new people should be talking about successful contestants. So even if a contestant has a large number of mentions, if those mentions are coming from the same group of people, then the contestant is in danger of being voted off.

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Forget the Crystal Ball: Social Media Can Help Predict the Future

Forget the Crystal Ball: Social Media Can Help Predict the Future

Introduction

In previous articles, I have focused on what Twitter can tell us about people’s past behaviour. While this can be extremely useful, Twitter can also be used to predict future events. In most of these cases, researchers attempt to find a correlation between Twitter activity (such as mentions or sentiment) and some real world outcome. Correlation is a start, but it is not a predictive model.
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