Elizabeth Cano (Alumni)Research Associate
My research effort concentrates in the area of Social Computing, particularly in the analysis of social media based on the following topics:
- Data mining based on Bayesian modelling and NLP techniques
- Information retrieval methods based on semantic web technologies and graph-based algorithms
- Machine learning-based approaches
- Online algorithms
I'm particularly interested on the real-time analysis and detection of antisocial behaviour in social media. My previous work includes the development of methodologies for child-grooming detection in online chatrooms and the automatic detection of violence-related content in tweets.
I studied for a Ph.D. (2008-2012) under the supervision of Prof. Fabio Ciravegna at the University of Sheffield. My PhD thesis explored the application of semantic models and machine learning approaches for the mining of social media with a focus on entity profiling.
Currently I work on the MKSmart project at KMi, which focuses on the use of sensor data for Smart cities. Within this project I'm working on models that allows the combination of heterogeneous sensor-based data sources and social media for the creation of a so-called city observatory.
Keys: Social Computing, Machine Learning, Semantic Web
Cano, E., He, Y. and Alani, H. (2014) Stretching the Life of Twitter Classifiers with Time-Stamped Semantic Graphs, 13th International Semantic Web Conference (ISWC14), Riva del Garda, Trentino Italy
Cano, E., He, Y. and Alani, H. (2014) The Topics they are a-Changing - Characterising Topics with Time-Stamped Semantic Graphs, Poster at 13th International Semantic Web Conference (ISWC14), Riva del Garda, Trentino Italy
D., M., V., L., Cano, E. and F., C. (2014) Visualising Topical Sentiment and Influence in Social Media, Workshop: Social Media and Linked Data for Emergency Response (SMILE) Workshop at Extended Semantic Web Conference, ESWC 2013, Montpellier, France
Cano, E., D., M. and F., C. (2014) Social influence analysis in microblogging platforms - A topic-sensitive based approach, Semantic Web Journal, 5, 5, IOS
Cano, E., He, Y. and Xu, R. (2014) Automatic Labelling of Topic Models Learned from Twitter by Summarisation, The 51st Annual Meeting of the Association for Computational Linguistics (ACL), Baltimore, USA