Document Type

Dissertation

Rights

This item is available under a Creative Commons License for non-commercial use only

Disciplines

Computer Sciences

Publication Details

A dissertation submitted in partial fulfilment of the requirements of Dublin Institute of Technology for the degree of M.Sc. in Computing (Data Analytics) January, 2016

Abstract

Investment platforms and discussion platforms have come to change the face of finance. The stock market is open to both professional and non-professional investors via online financial channels. Information too comes via a shared domain as both professionals and non-professionals log onto online communication platforms to share, search and discuss market trends. Due to their growing role in finance, understanding online communities has become the focus of much stock market research. Determining who is influential in a network, how information spreads and what translates to buy or sell decision is potentially very lucrative. In this research paper a dataset from Stocktwits, a finance microblog, is analysed in order to determine a mechanism for identifying trustworthy and informative content in relation to Apple (AAPL) stock. Text analysis, user reputation classification and social network analysis are performed to generate features to measure correlations between the network and market changes.

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