A Framework for Longitudinal Influence Measurement between Communication Content and Social Networks

Wang, Shenghui; Groth, Paul

doi:10.5591/978-1-57735-516-8/IJCAI11-459

A Framework for Longitudinal Influence Measurement between Communication Content and Social Networks

Shenghui Wang, Paul Groth

Download BibTeX Cite

Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence. Pages 2758-2762.

https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-459

Abstract

Artificial intelligence has a long history of learning from domain problems ranging from chess to jeopardy. In this work, we look at a problem stemming from social science, namely, how do social relationships influence communication content and vice versa. The tools used to study communication content (content analysis) have rarely been combined with those used to study social relationships (social network analysis). Furthermore, there is even less work addressing the longitudinal characteristics of such a combination. This paper presents a general framework for measuring the dynamic bi-directional influence between communication content and social networks. The framework leverages the idea that knowledge about both kinds of networks can be represented using the same knowledge representation. In particular, through the use of Semantic Web standards, the extraction of networks is made easier. The framework is applied to two use-cases: online forum discussions and conference publications. The results provide a new perspective over the dynamics involving both social networks and communication content.

Shenghui Wang, and Paul Groth. 2011. A Framework for Longitudinal Influence Measurement between Communication Content and Social Networks. In Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence, IJCAI-11. IJCAI, 2758–2762. https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-459

@inproceedings{ijcai2011p459,
  title     = {A Framework for Longitudinal Influence Measurement between Communication Content and Social Networks},
  author    = {Wang, Shenghui and Groth, Paul},
  booktitle = {Proceedings of the Twenty-Second International Joint Conference on
               Artificial Intelligence, {IJCAI-11}},
  publisher = {AAAI Press/International Joint Conferences on Artificial Intelligence},
  editor    = {Toby Walsh},
  pages     = {2758--2762},
  year      = {2011},
  month     = {7},
  doi       = {10.5591/978-1-57735-516-8/IJCAI11-459},
  url       = {https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-459},
}

TY  - CPAPER
TI  - A Framework for Longitudinal Influence Measurement between Communication Content and Social Networks
AU  - Wang, Shenghui
AU  - Groth, Paul
T2  - Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence, IJCAI-11
PB  - AAAI Press/International Joint Conferences on Artificial Intelligence
PY  - 2011
SP  - 2758
EP  - 2762
DO  - 10.5591/978-1-57735-516-8/IJCAI11-459
UR  - https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-459
ER  -