Modeling Information Diffusion over Social Networks for Temporal Dynamic Prediction
- Submitting institution
-
The University of Leicester
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 1418
- Type
- D - Journal article
- DOI
-
10.1109/TKDE.2017.2702162
- Title of journal
- IEEE Transactions on Knowledge and Data Engineering
- Article number
- -
- First page
- 1985
- Volume
- 29
- Issue
- 9
- ISSN
- 1041-4347
- Open access status
- Compliant
- Month of publication
- May
- Year of publication
- 2017
- URL
-
-
- Supplementary information
-
https://doi.org/10.1109/TKDE.2017.2702162
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
5
- Research group(s)
-
-
- Citation count
- 19
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- The rapid development of online social networks (e.g. Twitter) has led to significant interest in the study of information diffusion, where someone’s actions may be influenced by others. This paper introduces a novel game theory-based decision-making system for information diffusion prediction. The proposed technology has been used in a proof-of-concept preliminary study to support the research of recently awarded Medical Research Council Grant (MR/R011176/1). The proposed technology has been also used and followed by other researchers (e.g. Lu et al. IEEE TCOM, 2017; He et al. IEEE TKDE, 2018; Wan et al. IEEE TKDE, 2019).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -