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Twitter Mining for Discovery, Prediction and Causality: Applications and Methodologies

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  • Daniel E. O'Leary

Abstract

Twitter has found substantial use in a number of settings. For example, Twitter played a major role in the ‘Arab Spring’ and has been adopted by a large number of the Fortune 100. All of these and other events have led to a large database of Twitter tweets that has attracted the attention of a number of companies and researchers through what has become known as ‘Twitter mining’ (also known as ‘TwitterMining’). This paper analyses some of the approaches used to gather information and knowledge from Twitter for Twitter mining. In addition, this paper reviews a number of the applications that employ Twitter Mining, investigating Twitter information for prediction, discovery and as an informational basis of causation. Copyright © 2015 John Wiley & Sons, Ltd.

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  • Daniel E. O'Leary, 2015. "Twitter Mining for Discovery, Prediction and Causality: Applications and Methodologies," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 22(3), pages 227-247, July.
    • Handle: RePEc:wly:isacfm:v:22:y:2015:i:3:p:227-247
    DOI: 10.1002/isaf.1376
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    References listed on IDEAS

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    1. Bolo, Froilan & Caramat, Wendell & Decena, Ma. Carlota, 2022. "On the dynamic prediction of a president's net satisfaction survey: A test of Twitter accuracy," Chaos, Solitons & Fractals, Elsevier, vol. 157(C).

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