Predicting Amazon’s Choice of HQ2 From Social Media: Evidence From the Tweets of Informed Sources

Joseph, K and Mandal, A and Singha, S (2020) Predicting Amazon’s Choice of HQ2 From Social Media: Evidence From the Tweets of Informed Sources. Journal of Applied Business and Economics, 22 (10). ISSN 1499-691X

Full text not available from this repository. (Request a copy)

Abstract

Social media chatter, and in particular, Twitter, is increasingly gaining popularity to generate forecasts in a wide variety of domains. We build on this body of work and set out to predict Amazon’s HQ2 choice by analyzing the tweets of officials at the 20 finalist cities. Consistent with the affect infusion model (AIM) from the psychology literature, we conceptualize that the positive affect generated in successful ongoing negotiations will lead to a congruent positive spill over even in unrelated tweets. Analyzing tweet series that include a corpus of 50,238 tweets and incorporating dynamic time warping measures, our forecasting method correctly predicts Northern Virginia, favors it over two proximal cities, Washington D.C. and Baltimore, and ranks New York City 11 th out of 20 cities. These forecasts match those of the betting markets. Our research thus offers an alternate and novel approach to extracting the signal from the noise in social media.

Item Type: Article
Subjects: Information Systems
Date Deposited: 28 Nov 2023 09:18
Last Modified: 28 Nov 2023 09:18
URI: https://eprints.exchange.isb.edu/id/eprint/2248

Actions (login required)

View Item
View Item