Anjie Fang

I'm a LKAS PhD candidate at The University of Glasgow in TerrierTeam, supervised by Prof. Iadh Ounis, Dr. Philip Habel and Dr. Craig Macdonald. I got my MSc degree in advanced computing from The University of Bristol in 2013. Before I came to Glasgow, I worked as a research assistant (intern) at National Institute of Informatics in Japan in 2014.
My current research is to generate valuable dynamic topics from social media network (e.g. Twitter) involving time stamp and community information. This work helps social scientist understand the information dynamics on social media network, such as when topics rise/fade, how topics change over time, how topics flow among communities, etc. As a preliminary, I've successfully improve the text classification on identifying users' political orientations by involving topics. Also, I examined the usefulness of existing topic coherence metrics for Twitter data and proposed more effective tweets topic coherence metrics.

Publications

NEWNews and Information Leadership in the Digital Age
[doi] [bibtex]
Philip Habel, Ruth Moon and Anjie Fang. Information, Communication and Society, 2017.

NEWExploring Time-Sensitive Variational Bayesian Inference LDA for Social Media DataBest Student Paper
[pdf] [bibtex] [github, ready soon]
Anjie Fang, Craig Macdonald, Iadh Ounis, Philip Habel and Xiao Yang. In Proceedings of the 39th European Conference on Information Retrieval, UK, 2017.

Examining the Coherence of the Top Ranked Tweet Topics
[pdf] [bibtex]
Anjie Fang, Craig Macdonald, Iadh Ounis and Philip Habel. In Proceedings of the 39th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, Italy, 2016.

Using Word Embedding to Evaluate the Coherence of Topics from Twitter Data
[pdf] [bibtex]
Anjie Fang, Craig Macdonald, Iadh Ounis and Philip Habel. In Proceedings of the 39th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, Italy, 2016.

Topics in Tweets: A User Study of Topic Coherence Metrics for Twitter Data Best Paper Honorable Mention
[pdf] [bibtex]
Anjie Fang, Craig Macdonald, Iadh Ounis and Philip Habel. In Proceedings of the 38th European Conference on Information Retrieval, Italy, 2016.

Topic-centric Classification of Twitter User's Political Orientation
[pdf] [bibtex] [demo]
Anjie Fang, Iadh Ounis, Craig Macdonald, Philip Habel and Nut Limsopatham. In Proceedings of the 38th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, Chile, 2015.

Topic-centric Classification of Twitter User's Political Orientation
[pdf]
Anjie Fang, Iadh Ounis, Craig Macdonald, Philip Habel and Nut Limsopatha. In Proceedings of the 6th Symposium on Future Directions in Information Access, Greece, 2015.

Accurate Household Occupant Behavior Modeling Based on Data Mining Techniques
[pdf] [bibtex]
Marcia Baptista, Anjie Fang, Helmut Prendinger, Rui Prada and Yohei Yamaguchi. In Proceedings of the 28th AAAI Conference on Artificial Intelligence, Canada, 2014.

Conference Presentations

On Classifying Twitter Users' Policy-Relevant Community Affiliations Using DBpedia
Anjie Fang, Philip Habel, Iadh Ounis, Craig Macdonald and Xiao Yang. International Conference on the Advances in Computational Analysis of Political Text, Croatia, 2016.

Social Networks, Big Data, and Intermedia Agenda Setting
Philip Habel, Ruth Moon and Anjie Fang. American Political Science Association, US, 2015.

Assessing Information Leadership and Intermedia Agenda Setting through Social Media
Philip Habel, Anjie Fang and Ruth Moon. International Conference on Computational Social Science, Finland, 2015.

Awards

The 2nd year poster winner, awarded by SCISA PhD Conference, 2016.

The 1st year poster winner, awarded by SCISA PhD Conference, 2015.

Lord Kelvin - Adam Smith PhD Scholarship, 2014 - Present.



F111, Sir Alwyn Williams Bldg
School of Computing Science
Glasgow, G12 8QQ, UK



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