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Measuring and Predicting Human Behaviour Using Online Data

A session at Sentiment Analysis in Finance Conference, Singapore, 10 – 11 March, 2016

Tobias Preis, Warwick Business School

In this talk, I will outline some recent highlights of our research, addressing two questions. Firstly, can big data resources provide insights into crises in financial markets? By analysing Google query volumes for search terms related to finance and views of Wikipedia articles, we find patterns which may be interpreted as early warning signs of stock market moves. Secondly, can we provide insight into international differences in economic well being by comparing patterns of interaction with the Internet? To answer this question, we introduce a future orientation index to quantify the degree to which Internet users seek more information about years in the future than years in the past. We analyse Google logs and find a striking correlation between the country's GDP and the predisposition of its inhabitants to look forward. Our results illustrate the potential that combining extensive behavioural data sets offers for a better understanding of large scale human economic behaviour.

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When

Date Thu 10th March 2016

Session Hash Tag

#UNICOMSA

Short URL

lanyrd.com/sdxtdx

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