Alumni Member
Hassan Saif (Alumni) 
Research Associate
Hassan Saif is a research associate at the Knowledge Media Institute. His research interests are in Sentiment Analysis, Machine Learning and Social Semantics.
Hassan has recently had a PhD degree at the Open University on semantic sentiment analysis of microblogs. He has extensive expertise in social media analysis and data mining, and has published in top semantic web conferences and journals.
Along his career in KMI, Hassan has been involved in several EU projects including, ROBUST and SENSE4US, where he developed various novel techniques of using Semantics in Sentiment Analysis.
Previously to joining KMi, Hassan worked as a research assistant at the University of Lincon, UK and as research engineer for NordicSense, Finland.
Keys: Social Semantic, Semantic Computing, Sentiment Analysis, Opinion Mining, Information Extraction, Machine Learning, Natural Language Processing, Semantic Web
Team: Harith Alani, , Miriam Fernandez
News
Publications
Burel, G., Saif, H. and Alani, H. (2017). Semantic Wide and Deep Learning for Detecting Crisis-Information Categories on Social Media. In: 16th International Semantic Web Conference, 21-25 Oct 2017, Vienna, Austria. https://oro.open.ac.uk/51726/.
Saif, H. (2017). Semantic Sentiment Analysis in Social Streams. Studies on the Semantic Web, 30. IOS Press. https://oro.open.ac.uk/51175/.
Saif, H., Fernández, M., Kastler, L. and Alani, H. (2016). A Linked Open Data Approach for Sentiment Lexicon Adaptation. In: The 4th International Workshop on Linked Data for Information Extraction, ISWC Conference, 18 Oct 2016. https://oro.open.ac.uk/51173/.
Saif, H., Fernández, M., Kastler, L. and Alani, H. (2017). Sentiment Lexicon Adaptation with Context and Semantics for the Social Web. Semantic Web Journal, 8(5), pp. 643–665. https://oro.open.ac.uk/51171/.
Saif, H., Dickinson, T., Kastler, L., Fernandez, M. and Alani, H. (2017). A Semantic Graph-Based Approach for Radicalisation Detection on Social Media. In: Proc. Int. Extended Semantic Web Conference (ESWC), 28 May - 01 Jun 2017, Portorož, Slovenia. https://oro.open.ac.uk/49640/.
Burel, G., Saif, H., Fernandez, M. and Alani, H. (2017). On Semantics and Deep Learning for Event Detection in Crisis Situations. In: Workshop on Semantic Deep Learning (SemDeep), at ESWC 2017, 29 May 2017, Portoroz, Slovenia. https://oro.open.ac.uk/49639/.
Saif, H., Bashevoy, M., Taylor, S., Fernández, M. and Alani, H. (2016). SentiCircles: A Platform for Contextual and Conceptual Sentiment Analysis. In: ESWC2016: European Semantic Web Conference, 29 May - 02 Jun 2016, Anissaras, Crete, Greece. https://oro.open.ac.uk/48480/.
Saif, H., Fernández, M., Rowe, M. and Alani, H. (2016). On the Role of Semantics for Detecting pro-ISIS Stances on Social Media. In: ISWC 2016, 19 Oct 2016, Kobe, Japan. https://oro.open.ac.uk/48478/.
Rowe, M. and Saif, H. (2016). Mining Pro-ISIS Radicalisation Signals from Social Media Users. In: ICWSM-16: 10th International AAAI Conference on Web and Social Media, 17-20 May 2016, Cologne, Germany. https://oro.open.ac.uk/48477/.
Cano, A.E., Saif, H., Alani, H. and Motta, E. (2016). Semantic Topic Compass – Classification Based on Unsupervised Feature Ambiguity Gradation. Lecture Notes in Computer Science, 9678 pp. 350–367. https://oro.open.ac.uk/48479/.
Saif, H., Ortega, F., Fernández, M. and Cantador, I. (2016). Sentiment Analysis in Social Streams. In: Tkalčič, Marko; De Carolis, Berardina; de Gemmis, Marco; Odić, Ante and Košir, Andrej eds. Emotions and Personality in Personalized Services: Models, Evaluation and Applications. Human-Computer Interaction Series. Springer, pp. 119–140. https://oro.open.ac.uk/45438/.
Uren, V., Wright, D., Scott, J., He, Y. and Saif, H. (2016). Social media and sentiment in bioenergy consultation. International Journal of Energy Sector Management, 10(1), pp. 87–98. https://oro.open.ac.uk/45439/.
Saif, H. (2015). Semantic Sentiment Analysis of Microblogs. [Thesis] https://oro.open.ac.uk/44063/.
Saif, H., He, Y., Fernández, M. and Alani, H. (2016). Contextual semantics for sentiment analysis of Twitter. Information Processing and Management, 52(1), pp. 5–19. https://oro.open.ac.uk/42471/.
Saif, H., He, Y., Fernández, M. and Alani, H. (2014). Adapting sentiment lexicons using contextual semantics for sentiment analysis of Twitter. In: Workshop 5: SemanticSentimentAnalysis2014: Semantic Web and Sentiment Analysis, 25-19 May 2014, Crete, Greece. https://oro.open.ac.uk/41401/.
Saif, H., Fernández, M. and Alani, H. (2014). Automatic stopword generation using contextual semantics for sentiment analysis of Twitter. In: 13th International Semantic Web Conference (ISWC 2014), 19-23 Oct 2014, Riva del Garda, Trentino, Italy. https://oro.open.ac.uk/41400/.
Saif, H., He, Y., Fernández, M. and Alani, H. (2014). Semantic patterns for sentiment analysis of Twitter. In: 13th International Semantic Web Conference (ISWC 2014), 19-23 Oct 2014, Riva del Garda, Trentino, Italy. https://oro.open.ac.uk/41399/.
Saif, H., Fernández, M., He, Y. and Alani, H. (2014). On stopwords, filtering and data sparsity for sentiment analysis of Twitter. In: LREC 2014, Ninth International Conference on Language Resources and Evaluation, 26-31 May 2014, Reykjavik, Iceland. https://oro.open.ac.uk/40666/.
Saif, H., Fernández, M., He, Y. and Alani, H. (2014). SentiCircles for contextual and conceptual semantic sentiment analysis of Twitter. In: 11th ESWC 2014, 25-29 May 2014, Crete, Greece. https://oro.open.ac.uk/40661/.
Saif, H., Fernández, M., He, Y. and Alani, H. (2013). Evaluation datasets for Twitter sentiment analysis: a survey and a new dataset, the STS-Gold. In: 1st Interantional Workshop on Emotion and Sentiment in Social and Expressive Media: Approaches and Perspectives from AI (ESSEM 2013), 3 Dec 2013, Turin, Italy. https://oro.open.ac.uk/40660/.
Tech Reports
Sentiment Analysis of Microblogs
Techreport ID: kmi-12-02
Date: 2012
Author(s): Hassan Saif
