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The power of prediction with social media

Autor(es) y otros:
Schoen, Harald; Gayo Avello, DanielAutoridad Uniovi; Metaxas, Panagiotis T.; Mustafaraj, Eni; Strohmaier, Markus; Gloor, Peter
Fecha de publicación:
2013
Editorial:

Emerald

Versión del editor:
http://dx.doi.org/10.1108/IntR-06-2013-0115
Citación:
Internet Research, 23(5), p. 528-543 (2013); doi:10.1108/IntR-06-2013-0115
Descripción física:
p. 528-543
Resumen:

Social media provide an impressive amount of data about users and their interactions, thereby offering computer and social scientists, economists, and statisticians – among others – new opportunities for research. Arguably, one of the most interesting lines of work is that of predicting future events and developments from social media data. However, current work is fragmented and lacks of widely accepted evaluation approaches. Moreover, since the first techniques emerged rather recently, little is known about their overall potential, limitations and general applicability to different domains. Therefore, better understanding the predictive power and limitations of social media is of utmost importance

Social media provide an impressive amount of data about users and their interactions, thereby offering computer and social scientists, economists, and statisticians – among others – new opportunities for research. Arguably, one of the most interesting lines of work is that of predicting future events and developments from social media data. However, current work is fragmented and lacks of widely accepted evaluation approaches. Moreover, since the first techniques emerged rather recently, little is known about their overall potential, limitations and general applicability to different domains. Therefore, better understanding the predictive power and limitations of social media is of utmost importance

URI:
http://hdl.handle.net/10651/24088
ISSN:
1066-2243
Identificador local:

20140990

DOI:
10.1108/IntR-06-2013-0115
Patrocinado por:

The work of P. Metaxas and E. Mustafaraj was supported by NSF grant CNS-117693.

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