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Hassan Saif Member status icon

PhD Research Student
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I joined KMI as a PhD student in April 2011. My research interests are in the areas of sentiment analysis, opinion mining, natural language processing, information extraction, and machine learning.

My current research project focuses on sentiment analysis of microblogs as apart of the EU FP7 integrated project “Robust” which aims to develop a highly scalable platform enabling trustworthy and timely information services in an ecosystem of online business communities. Robust involves academic and industrial partners including IBM and SAP.

Keys: Twitter Sentiment Analysis, Opinion Mining, Information Extraction, Machine Learning, Natural Language Processing.

Team: Harith Alani, Gregoire Burel, Miriam Fernandez





Saif, H., He, Y., Fernandez, M. and Alani, H. (2014) Semantic Patterns for Sentiment Analysis of Twitter, The 13th International Semantic Web Conference (ISWC), Riva del Garda - Trentino Italy

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Saif, H., Fernandez, M., He, Y. and Alani, H. (2014) On Stopwords, Filtering and Data Sparsity for Sentiment Analysis of Twitter, The 9th International Conference on Language Resources and Evaluation, Reykjavik, Iceland

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Saif, H., Fernandez, M., He, Y. and Alani, H. (2014) SentiCircles for Contextual and Conceptual Semantic Sentiment Analysis of Twitter, 11th Extended Semantic Web Conference, Crete, Greece


Saif, H., He, Y., Fernandez, M. and Alani, H. (2014) Adapting Sentiment Lexicons using Contextual Semantics for Sentiment Analysis of Twitter, Workshop: Semantic Sentiment Analysis, Crete, Greece

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Saif, H., Fernandez, M., He, Y. and Alani, H. (2013) Evaluation Datasets for Twitter Sentiment Analysis: A survey and a new dataset, the STS-Gold, Workshop: Emotion and Sentiment in Social and Expressive Media: approaches and perspectives from AI (ESSEM) at AI*IA Conference, Turin, Italy

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Tech Reports

View AbstractDownload PDF

Sentiment Analysis of Microblogs
Techreport ID: kmi-12-02
Date: 2012
Author(s): Hassan Saif


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Studentship applications are currently available in KMi, read more and learn how to apply.

Deadline for applications: 29 August 2014

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Knowledge Media Institute
The Open University
Walton Hall
Milton Keynes
United Kingdom

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