Anjie Fang

I'm an applied scientist at Amazon in Seattle, US. I obtain my PhD in computing science from The University of Glasgow, where I was 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. I also interned as a research assistant at National Institute of Informatics in Japan in 2014.
My research interests include natural language processing and information retrieval. During my PhD study, I helped social scientists to understand political events (e.g. an election) by proposing a serise of computing science approaches for social media data. These approaches can effectively extarct discussed topics on Twitter and identify users' into ccommunities during a political event.

Publications

NewUsing Phoneme Representations to Build Predictive Models Robust to ASR Errors
[doi] [bibtex]
Anjie Fang, Simone Filice, Nut Limsopatham and Oleg Rokhlenko. n Proceedings of the 43th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, China, 2020.

Votes on Twitter: assessing candidate preferences and topics of discussion during the 2016 U.S. presidential election
[doi] [bibtex]
Anjie Fang, Philip Habel, Iadh Ounis and Craig Macdonald. SAGE Open, 2019.

Evaluating Similarity Metrics for Latent Twitter Topics
[doi] [bibtex]
Xi Wang, Anjie Fang, Iadh Ounis and Craig Macdonald. In Proceedings of the 41st European Conference on Information Retrieval, 2019.

An Effective Approach for Modelling Time Features for Classifying Bursty Topics on Twitter
[doi] [bibtex]
Anjie Fang, Iadh Ounis, Craig Macdonald, Philip Habel, Xiaoyu Xiong and Haitao Yu. In Proceedings of the 27th ACM International Conference on Information and Knowledge Management, 2018.

On Refining Twitter Lists as Ground Truth Data for Multi-Community User Classification
[doi] [bibtex]
Ting Su, Anjie Fang, Richard McCreadie, Craig Macdonald and Iadh Ounis. In Proceedings of the 40th European Conference on Information Retrieval, 2018.

On the Reproducibility and Generalisation of the Linear Transformation of Word Embeddings
[pdf] [bibtex]
Xiao Yang, Iadh Ounis, Anjie Fang, Richard Mccreadie and Craig Macdonald. In Proceedings of the 40th European Conference on Information Retrieval, 2018.

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

Exploring Time-Sensitive Variational Bayesian Inference LDA for Social Media DataBest Student Paper
[pdf] [bibtex] [github]
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] [github]
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] [github]
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.



440 Terry Ave N
Seattle, WA, US, 98109.



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