Understanding the Predictive Power of Social Media This is a pre-print version of the following article: Evangelos Kalampokis, Efthimios Tambouris and Konstantinos Tarabanis (2013) Understanding the Predictive Power of Social Media. Internet Research, Vol.23, No.5. pp. 544-559 http://dx.doi.org/10.1108/IntR-06-2012-0114 Available from http://kalampok.is Author Details: Author 1 Name: Evangelos Kalampokis Department: Information Systems Laboratory University/Institution: University of Macedonia Town/City: Thessaloniki Country: Greece Department: Information Technologies Institute University/Institution: Centre for Research & Technology - Hellas Town/City: Thessaloniki Country: Greece Author 2 Name: Efthimios Tambouris Department: Department of Technology and Management University/Institution: University of Macedonia Town/City: Naousa Country: Greece Department: Information Technologies Institute University/Institution: Centre for Research & Technology - Hellas Town/City: Thessaloniki Country: Greece Author 3 Name: Konstantinos Tarabanis Department: Department of Business Administration University/Institution: University of Macedonia Town/City: Thessaloniki Country: Greece Department: Information Technologies Institute University/Institution: Centre for Research & Technology - Hellas Town/City: Thessaloniki Country: Greece Corresponding author: Evangelos Kalampokis Corresponding Author’s Email: [email protected]Please check this box if you do not wish your email address to be published Acknowledgments: The authors would like to thank the anonymous reviewers for their valuable comments that have enabled the improvement of manuscript’s quality. The authors would also like to acknowledge that the work presented in this paper has been partially funded by the European Union through the “Linked2Media - An Open Linked Data Platform for Semantically-Interconnecting Online, Social Media Leveraging Corporate Brand and Market Sector Reputation Analysis, FP7-SME-2011 No 286714” project.
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Title: Understanding the Predictive Power of Social Media · Title: Understanding the Predictive Power of Social Media Purpose: The purpose of this article is to consolidate existing
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Understanding the Predictive Power of Social Media
This is a pre-print version of the following article: Evangelos Kalampokis, Efthimios Tambouris and Konstantinos Tarabanis (2013) Understanding the Predictive Power of Social Media. Internet Research, Vol.23, No.5. pp. 544-559 http://dx.doi.org/10.1108/IntR-06-2012-0114 Available from http://kalampok.is Author Details: Author 1 Name: Evangelos Kalampokis Department: Information Systems Laboratory University/Institution: University of Macedonia Town/City: Thessaloniki Country: Greece Department: Information Technologies Institute University/Institution: Centre for Research & Technology - Hellas Town/City: Thessaloniki Country: Greece Author 2 Name: Efthimios Tambouris Department: Department of Technology and Management University/Institution: University of Macedonia Town/City: Naousa Country: Greece Department: Information Technologies Institute University/Institution: Centre for Research & Technology - Hellas Town/City: Thessaloniki Country: Greece Author 3 Name: Konstantinos Tarabanis Department: Department of Business Administration University/Institution: University of Macedonia Town/City: Thessaloniki Country: Greece Department: Information Technologies Institute University/Institution: Centre for Research & Technology - Hellas Town/City: Thessaloniki Country: Greece Corresponding author: Evangelos Kalampokis
Please check this box if you do not wish your email address to be published
Acknowledgments: The authors would like to thank the anonymous reviewers for their valuable comments that have enabled the improvement of manuscript’s quality. The authors would also like to acknowledge that the work presented in this paper has been partially funded by the European Union through the “Linked2Media - An Open Linked Data Platform for Semantically-Interconnecting Online, Social Media Leveraging Corporate Brand and Market Sector Reputation Analysis, FP7-SME-2011 No 286714” project.
Biographical Details: Evangelos Kalampokis is a PhD student at the Information Systems Laboratory at the University of Macedonia, Greece. He is also a research assistant with the Information Technologies Institute of the Centre for Research & Technology - Hellas (CERTH/ITI) in Thessaloniki, Greece, while from October 2010 until November 2011 he was a research intern at the Digital Enterprise Research Institute (DERI) of the National University of Ireland, Galway (NUIG). His main research interests include Open and Linked Data, Social Media, eGovernment and Data Mining. Efthimios Tambouris is an Assistant Professor of Information Systems at the Technology Management Department at the University of Macedonia, Thessaloniki, Greece. Before that, he served as a Researcher Grade D at the research center CERTH/ITI and at research center NCSR “Demokritos”. He was also founder and manager of the eGovernment Unit at Archetypon SA, an international IT company. He holds a Diploma in Electrical Engineering from the National Technical University of Athens, Greece, and an MSc and PhD from Brunel University, UK. During the past years he has initiated and managed several research projects (e.g., IST EURO-CITI, IST eGOV, eContent eMate). He has also participated in numerous research projects (FP6/IST, e.g., OneStopGov, DEMO-net, FP5/IST, TAP, ACTS, ESPRIT, SPRITE-S2, etc.), service contracts (e.g. MODINIS Interoperability Study, European eParticipation Study) and standardisation activities (CEN/ISSS project on eGovernment metadata, CEN/ISSS eGovernment Focus Group). He has more than 120 publications in eGovernment, eParticipation, eLearning and eHealth. Konstantinos Tarabanis is a Professor at the Department of Business Administration of the University of Macedonia, Greece, and the Director of the Information Systems Laboratory at the same university. He received an Engineering Diploma in Mechanical Engineering from the National Technical University of Athens (1983), an MS in both Mechanical Engineering and Computer Science (1984 and 1988, respectively), and a PhD in Computer Science (1991), at Columbia University, New York, NY. He was a research staff member at the IBM T.J. Watson Research Centre, 1991–1994, and was employed by the IBM Corporation as a whole during 1984–1994. In recognition of his research, he was the recipient of the Anton Philips Best Paper Award at the 1991 IEEE International Conference on Robotics and Automation. He has about 200 research publications in the areas of software modeling and development for the domains of eGovernment, eBusiness, eLearning, eManufacturing etc. Structured Abstract: Purpose The purpose of this article is to consolidate existing knowledge and provide a deeper understanding of the use of Social Media (SM) data for predictions in various areas, such as disease outbreaks, product sales, stock market volatility, and elections outcome predictions. Design/methodology/approach The scientific literature was systematically reviewed to identify relevant empirical studies. These studies were analyzed and synthesized in the form of a proposed conceptual framework, which was thereafter applied to further analyze this literature, hence gaining new insights into the field. Findings The proposed framework reveals that all relevant studies can be decomposed into a small number of steps, and different approaches can be followed in each step. The application of the framework resulted in interesting findings. For example, most studies support SM predictive power, however more than one-third of these studies infer predictive power without employing predictive analytics. In addition, analysis suggests that there is a clear need for more advanced sentiment analysis methods as well as methods for identifying search terms for collection and filtering of raw SM data. Value The proposed framework enables researchers to classify and evaluate existing studies, to design scientifically rigorous new studies, and to identify the field’s weaknesses, hence proposing future research directions. Keywords: Social Networks; World Wide Web; Data Analysis; Open data. Article Classification: Research paper
Title: Understanding the Predictive Power of Social Media
Purpose: The purpose of this article is to consolidate existing knowledge and provide
a deeper understanding of the use of Social Media (SM) data for predictions in
various areas, such as disease outbreaks, product sales, stock market volatility, and
elections outcome predictions.
Design/methodology/approach: The scientific literature was systematically
reviewed to identify relevant empirical studies. These studies were analyzed and
synthesized in the form of a proposed conceptual framework, which was thereafter
applied to further analyze this literature, hence gaining new insights into the field.
Findings: The proposed framework reveals that all relevant studies can be
decomposed into a small number of steps, and different approaches can be followed
in each step. The application of the framework resulted in interesting findings. For
example, most studies support SM predictive power, however more than one-third of
these studies infer predictive power without employing predictive analytics. In
addition, analysis suggests that there is a clear need for more advanced sentiment
analysis methods as well as methods for identifying search terms for collection and
filtering of raw SM data.
Value: The proposed framework enables researchers to classify and evaluate existing
studies, to design scientifically rigorous new studies, and to identify the field’s
weaknesses, hence proposing future research directions.
Keywords: Social Networks; World Wide Web; Data Analysis; Open data.
This is a pre-print version of the following article: E. Kalampokis, E. Tambouris and K. Tarabanis (2013) Understanding the Predictive Power of Social Media. Internet Research, Vol.23, No.5, pp.544-559 http://dx.doi.org/10.1108/IntR-06-2012-0114
This is a pre-print version of the following article: E. Kalampokis, E. Tambouris and K. Tarabanis (2013) Understanding the Predictive Power of Social Media. Internet Research, Vol.23, No.5, pp.544-559 http://dx.doi.org/10.1108/IntR-06-2012-0114
This is a pre-print version of the following article: E. Kalampokis, E. Tambouris and K. Tarabanis (2013) Understanding the Predictive Power of Social Media. Internet Research, Vol.23, No.5, pp.544-559 http://dx.doi.org/10.1108/IntR-06-2012-0114
This is a pre-print version of the following article: E. Kalampokis, E. Tambouris and K. Tarabanis (2013) Understanding the Predictive Power of Social Media. Internet Research, Vol.23, No.5, pp.544-559 http://dx.doi.org/10.1108/IntR-06-2012-0114
This is a pre-print version of the following article: E. Kalampokis, E. Tambouris and K. Tarabanis (2013) Understanding the Predictive Power of Social Media. Internet Research, Vol.23, No.5, pp.544-559 http://dx.doi.org/10.1108/IntR-06-2012-0114
This is a pre-print version of the following article: E. Kalampokis, E. Tambouris and K. Tarabanis (2013) Understanding the Predictive Power of Social Media. Internet Research, Vol.23, No.5, pp.544-559 http://dx.doi.org/10.1108/IntR-06-2012-0114
This is a pre-print version of the following article: E. Kalampokis, E. Tambouris and K. Tarabanis (2013) Understanding the Predictive Power of Social Media. Internet Research, Vol.23, No.5, pp.544-559 http://dx.doi.org/10.1108/IntR-06-2012-0114
This is a pre-print version of the following article: E. Kalampokis, E. Tambouris and K. Tarabanis (2013) Understanding the Predictive Power of Social Media. Internet Research, Vol.23, No.5, pp.544-559 http://dx.doi.org/10.1108/IntR-06-2012-0114
This is a pre-print version of the following article: E. Kalampokis, E. Tambouris and K. Tarabanis (2013) Understanding the Predictive Power of Social Media. Internet Research, Vol.23, No.5, pp.544-559 http://dx.doi.org/10.1108/IntR-06-2012-0114
This is a pre-print version of the following article: E. Kalampokis, E. Tambouris and K. Tarabanis (2013) Understanding the Predictive Power of Social Media. Internet Research, Vol.23, No.5, pp.544-559 http://dx.doi.org/10.1108/IntR-06-2012-0114
This is a pre-print version of the following article: E. Kalampokis, E. Tambouris and K. Tarabanis (2013) Understanding the Predictive Power of Social Media. Internet Research, Vol.23, No.5, pp.544-559 http://dx.doi.org/10.1108/IntR-06-2012-0114
This is a pre-print version of the following article: E. Kalampokis, E. Tambouris and K. Tarabanis (2013) Understanding the Predictive Power of Social Media. Internet Research, Vol.23, No.5, pp.544-559 http://dx.doi.org/10.1108/IntR-06-2012-0114
This is a pre-print version of the following article: E. Kalampokis, E. Tambouris and K. Tarabanis (2013) Understanding the Predictive Power of Social Media. Internet Research, Vol.23, No.5, pp.544-559 http://dx.doi.org/10.1108/IntR-06-2012-0114
This is a pre-print version of the following article: E. Kalampokis, E. Tambouris and K. Tarabanis (2013) Understanding the Predictive Power of Social Media. Internet Research, Vol.23, No.5, pp.544-559 http://dx.doi.org/10.1108/IntR-06-2012-0114
This is a pre-print version of the following article: E. Kalampokis, E. Tambouris and K. Tarabanis (2013) Understanding the Predictive Power of Social Media. Internet Research, Vol.23, No.5, pp.544-559 http://dx.doi.org/10.1108/IntR-06-2012-0114
This is a pre-print version of the following article: E. Kalampokis, E. Tambouris and K. Tarabanis (2013) Understanding the Predictive Power of Social Media. Internet Research, Vol.23, No.5, pp.544-559 http://dx.doi.org/10.1108/IntR-06-2012-0114
This is a pre-print version of the following article: E. Kalampokis, E. Tambouris and K. Tarabanis (2013) Understanding the Predictive Power of Social Media. Internet Research, Vol.23, No.5, pp.544-559 http://dx.doi.org/10.1108/IntR-06-2012-0114
This is a pre-print version of the following article: E. Kalampokis, E. Tambouris and K. Tarabanis (2013) Understanding the Predictive Power of Social Media. Internet Research, Vol.23, No.5, pp.544-559 http://dx.doi.org/10.1108/IntR-06-2012-0114
This is a pre-print version of the following article: E. Kalampokis, E. Tambouris and K. Tarabanis (2013) Understanding the Predictive Power of Social Media. Internet Research, Vol.23, No.5, pp.544-559 http://dx.doi.org/10.1108/IntR-06-2012-0114
This is a pre-print version of the following article: E. Kalampokis, E. Tambouris and K. Tarabanis (2013) Understanding the Predictive Power of Social Media. Internet Research, Vol.23, No.5, pp.544-559 http://dx.doi.org/10.1108/IntR-06-2012-0114
This is a pre-print version of the following article: E. Kalampokis, E. Tambouris and K. Tarabanis (2013) Understanding the Predictive Power of Social Media. Internet Research, Vol.23, No.5, pp.544-559 http://dx.doi.org/10.1108/IntR-06-2012-0114
This is a pre-print version of the following article: E. Kalampokis, E. Tambouris and K. Tarabanis (2013) Understanding the Predictive Power of Social Media. Internet Research, Vol.23, No.5, pp.544-559 http://dx.doi.org/10.1108/IntR-06-2012-0114
This is a pre-print version of the following article: E. Kalampokis, E. Tambouris and K. Tarabanis (2013) Understanding the Predictive Power of Social Media. Internet Research, Vol.23, No.5, pp.544-559 http://dx.doi.org/10.1108/IntR-06-2012-0114
This is a pre-print version of the following article: E. Kalampokis, E. Tambouris and K. Tarabanis (2013) Understanding the Predictive Power of Social Media. Internet Research, Vol.23, No.5, pp.544-559 http://dx.doi.org/10.1108/IntR-06-2012-0114
This is a pre-print version of the following article: E. Kalampokis, E. Tambouris and K. Tarabanis (2013) Understanding the Predictive Power of Social Media. Internet Research, Vol.23, No.5, pp.544-559 http://dx.doi.org/10.1108/IntR-06-2012-0114
This is a pre-print version of the following article: E. Kalampokis, E. Tambouris and K. Tarabanis (2013) Understanding the Predictive Power of Social Media. Internet Research, Vol.23, No.5, pp.544-559 http://dx.doi.org/10.1108/IntR-06-2012-0114
This is a pre-print version of the following article: E. Kalampokis, E. Tambouris and K. Tarabanis (2013) Understanding the Predictive Power of Social Media. Internet Research, Vol.23, No.5, pp.544-559 http://dx.doi.org/10.1108/IntR-06-2012-0114
This is a pre-print version of the following article: E. Kalampokis, E. Tambouris and K. Tarabanis (2013) Understanding the Predictive Power of Social Media. Internet Research, Vol.23, No.5, pp.544-559 http://dx.doi.org/10.1108/IntR-06-2012-0114