Quantifying spatiotemporal dynamics of twitter replies to news feeds

F. Biessmann, J. M. Papaioannou, A. Harth, M. L. Jugel, Klaus Muller, M. Braun

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Social network analysis can be used to assess the impact of information published on the web. The spatiotemporal impact of a certain web source on a social network can be of particular interest. We contribute a novel statistical learning algorithm for spatiotemporal impact analysis. To demonstrate our approach we analyze Twitter replies to individual news article along with their geospatial and temporal information. We then compute the multivariate spatiotemporal response pattern of all Twitter replies to information published on a given web source. This quantitative result can be interpreted with respect to a) how much impact a certain web source has on the Twitter-sphere b) where and c) when it reaches it maximal impact. We also show that the proposed approach predicts the dynamics of the social network activity better than classical trend detection methods.

Original languageEnglish
Title of host publicationIEEE International Workshop on Machine Learning for Signal Processing, MLSP
DOIs
Publication statusPublished - 2012 Dec 12
Event2012 22nd IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2012 - Santander, Spain
Duration: 2012 Sep 232012 Sep 26

Other

Other2012 22nd IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2012
CountrySpain
CitySantander
Period12/9/2312/9/26

Fingerprint

Electric network analysis
Learning algorithms

Keywords

  • canonical trends
  • Social network analysis
  • spatiotemporal dynamics
  • tkCCA

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Signal Processing

Cite this

Biessmann, F., Papaioannou, J. M., Harth, A., Jugel, M. L., Muller, K., & Braun, M. (2012). Quantifying spatiotemporal dynamics of twitter replies to news feeds. In IEEE International Workshop on Machine Learning for Signal Processing, MLSP [6349806] https://doi.org/10.1109/MLSP.2012.6349806

Quantifying spatiotemporal dynamics of twitter replies to news feeds. / Biessmann, F.; Papaioannou, J. M.; Harth, A.; Jugel, M. L.; Muller, Klaus; Braun, M.

IEEE International Workshop on Machine Learning for Signal Processing, MLSP. 2012. 6349806.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Biessmann, F, Papaioannou, JM, Harth, A, Jugel, ML, Muller, K & Braun, M 2012, Quantifying spatiotemporal dynamics of twitter replies to news feeds. in IEEE International Workshop on Machine Learning for Signal Processing, MLSP., 6349806, 2012 22nd IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2012, Santander, Spain, 12/9/23. https://doi.org/10.1109/MLSP.2012.6349806
Biessmann F, Papaioannou JM, Harth A, Jugel ML, Muller K, Braun M. Quantifying spatiotemporal dynamics of twitter replies to news feeds. In IEEE International Workshop on Machine Learning for Signal Processing, MLSP. 2012. 6349806 https://doi.org/10.1109/MLSP.2012.6349806
Biessmann, F. ; Papaioannou, J. M. ; Harth, A. ; Jugel, M. L. ; Muller, Klaus ; Braun, M. / Quantifying spatiotemporal dynamics of twitter replies to news feeds. IEEE International Workshop on Machine Learning for Signal Processing, MLSP. 2012.
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