The Use of Twitter Activity as a Stock Market Predictor

Coyle , Robert (2014) The Use of Twitter Activity as a Stock Market Predictor. Diploma thesis, Dublin, National College of Ireland.

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This thesis investigates the possibility of predicting stock market movement using Twitter activity. The Analysis will use data mining applications, data analysis techniques, correlation and regression modelling.

The data mining of Twitter feeds was carried out. The process involved using Twitter API and Java code to search and download tweets with the words Apple, Microsoft and Tesla in them. These files were then processed using Amazon web service and Text Wrangler. An analysis was carried out using software such as R studio and Microsoft excel. Correlation models and Regression models were built along with the Granger Causality test in R studio. Visualisation techniques were carried out in Microsoft Excel and R studio showing some trends in the data.

A formula for stock market prediction for commercial use was created. Since the data set gathered from Twitter was not large enough and the actual information in the tweets was not specified towards the stock belonging to the companies, there is an issue of noisy data corrupting the analysis. A sentiment analysis was not carried out on the tweets.

Item Type: Thesis (Diploma)
Subjects: Q Science > QA Mathematics > Electronic computers. Computer science
T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science
Divisions: School of Computing > Higher Diploma in Science in Data Analytics
Date Deposited: 16 Dec 2014 14:54
Last Modified: 16 Dec 2014 14:54

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