Abstract
Recent research in the field of computational social science have shown how data resulting from the widespread adoption and use of social media channels such as twitter can be used to predict outcomes such as movie revenues, election winners, localized moods, and epidemic outbreaks. Underlying assumptions for this research stream on predictive analytics are that social media actions such as tweeting, liking, commenting and rating are proxies for user/consumer’s attention to a particular object/product and that the shared digital artefact that is persistent can create social influence. In this paper, we demonstrate how social media data from twitter can be used to predict the sales of iPhones. Based on a conceptual model of social data consisting of social graph (actors, actions, activities, and artefacts) and social text (topics, keywords, pronouns, and sentiments), we develop and evaluate a linear regression model that transforms iPhone tweets into a prediction of the quarterly iPhone sales with an average error close to the established prediction models from investment banks. This strong correlation between iPhone tweets and iPhone sales becomes marginally stronger after incorporating sentiments of tweets. We discuss the findings and conclude with implications for predictive analytics with big social data.
Originalsprog | Engelsk |
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Titel | Proceedings. IEEE 18th International Enterprise Distributed Object Computing Conference, EDOC 2014 |
Redaktører | Manfred Reichert, Stefanie Rinderle-Ma, Georg Grossmann |
Antal sider | 10 |
Udgivelsessted | Los Alamitos, CA |
Forlag | IEEE |
Publikationsdato | 2014 |
Sider | 81-90 |
ISBN (Trykt) | 9781479954704 |
DOI | |
Status | Udgivet - 2014 |
Begivenhed | The 18th IEEE Enterprise Computing Conference. EDOC 2014: Utilizing Big Data for the Enterprise of the Future - Ulm, Tyskland Varighed: 1 sep. 2014 → 5 sep. 2014 Konferencens nummer: 18 http://www.edoc2014.org/ |
Konference
Konference | The 18th IEEE Enterprise Computing Conference. EDOC 2014 |
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Nummer | 18 |
Land/Område | Tyskland |
By | Ulm |
Periode | 01/09/2014 → 05/09/2014 |
Internetadresse |
Navn | International Enterprise Distributed Object Computing Conference. Proceedings |
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Vol/bind | 18 |
ISSN | 1541-7719 |
Emneord
- Data science
- Computational social science
- Social data analytics
- Predictive analytics
- iPhone sales
- iPhone tweets