Ontological Modelling of Rumors
- 388 Downloads
In this paper, we present on-going work pursued in the context of the Pheme project. There, the detection of rumors in social media is playing a central role in two use cases. In order to be able to store and to query for information on specific types of rumors that can be circulated in such media (but also in “classical” media), we started to build ontological models of rumors, disputed claims, misinformation and veracity. As rumors can be considered as unverified statements, which after a certain time can be classified as either erroneous information or as facts, there is a need to model also the temporal information associated with any statement. As we are dealing in first line with social media, our modelling work should also cover information diffusion networks and user online behavior, which can also help in classifying a statement as a rumor or a fact. We focus in this paper on the core of our rumor ontology.
KeywordsOntologies Rumors Social media
This work presented in this paper has been supported by the PHEME FP7 project (grant No. 611233).
- 1.Breslin, J.G., Bojārs, U., Passant, A., Fernández, S., Decker, S.: SIOC: content exchange and semantic interoperability between social networks. In: W3C Workshop on the Future of Social Networking (2009)Google Scholar
- 2.Damova, M., Kiryakov, A., Simov, K., Petrov, S.: Mapping the central LOD ontologies to PROTON upper-level ontology. In: Ontology Mapping Workshop at ISWC 2010, Shanghai, China (2010)Google Scholar
- 3.Declerck, T., Lendvai, P.: Towards the representation of hashtags in linguistic linked open data format. In: Vossen, P., Rigau, G., Osenova, P., Simov, K. (eds.) Proceedings of the Second Workshop on Natural Language Processing and Linked Open Data, Hissar, Bulgaria. INCOMA Ltd., Shoumen, September 2015Google Scholar
- 4.Derczynski, L., Bontcheva, K.: Pheme: veracity in digital social networks. In: Proceedings of the 10th Joint ACL – ISO Workshop on Interoperable Semantic Annotation (ISA) (2014)Google Scholar
- 5.Lukasik, M., Cohn, T., Bontcheva, K.: Point process modelling of rumour dynamics in social media. In: Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (ACL) (2015)Google Scholar
- 6.Lukasik, M., Cohn, T., Bontcheva, K.: Classifying tweet level judgments of rumours in social media. In: Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP) (2015)Google Scholar
- 7.Scerri, S., Cortis, K., Rivera, I., Handschuh, S.: Knowledge discovery in distributed social web sharing activities. In: Proceedings of the 2nd Workshop on Making Sense of Microposts (MSM) (2012)Google Scholar
- 8.Terziev, I., Kiryakov, A., Manov, D.: Base Upper-level Ontology (BULO) Guidance. Deliverable 1.8.1, SEKT project (2005)Google Scholar
- 9.Zubiaga, A., Liakata, M., Procter, R.N., Bontcheva, K., Tolmie, P.: Crowdsourcing the annotation of rumourous conversations in social media. In: World Wide Web Conference, Florence, Italy (2015)Google Scholar