Content Analysis

The Content Analysis track welcomes submissions of original, high-quality research papers related to the extraction of information from, and the analysis of, Web content that is wholly or partially expressed in natural-language format. The resulting information is broadly construed to include factual, subjective, scientific, social, behavioral, personal, historical, economic, and financial knowledge in natural language. The result of analysis includes any abstract, aggregate, or summarized knowledge such as clusters, topics, classifications, predictions, recommendations, and trends that are useful in the real world. We especially encourage submissions that propose novel and principled techniques or algorithms that can exploit the special characteristics of the Web and social media for the extraction and analysis of Web content. In addition to new techniques and algorithms, we also seek submissions that explore insights gained in the process.

Topics of interest include but are not limited to the following (listed in no particular order).

  • Language-analysis techniques
  • Normalization, clustering, classification, and summarization of Web text
  • Multi-lingual and cross-lingual analysis and mining
  • Information extraction
  • Event extraction and monitoring
  • Topic discovery
  • Sentiment analysis and opinion mining.
  • Social science research based on social media
  • Detecting deceptions, fakes and disinformation
  • Insights from natural-language analysis of social media
  • Content-based Information diffusion
  • Bridging ustructured and structured data
  • Statistical and machine learning for text
  • Novel applications

For questions related to this call, please email: research-contentanalysis@www2015.it

Area Chairs

  • Bing Liu, University of Illinois, Chicago
  • Heng Ji, Rensselaer Polytechnic Institute

Program Committee

  • Steven Bethard, University of Alabama at Birmingham
  • Yunbo Cao, Microsoft Research Asia
  • Taylor Cassidy, US Army Research Lab/IBM/CUNY
  • Wanxiang Che, Harbin Institute of Technology
  • Zhiyuan Chen, University of Illinois at Chicago
  • Hsin-Hsi Chen, National Taiwan University
  • Gao Cong, Nanyang Technological University
  • Eduard Dragut, Temple University
  • Koji Eguchi, Kobe University
  • Anthony Fader, University of Washington
  • Boi Faltings, EPFL
  • Radu Florian, IBM TJ Watson Research Center
  • Ralph Grishman, New York University
  • Ben Hachey, University of Sydney
  • Sanda Harabagiu, University of Texas at Dallas
  • Hongzhao Huang, Rensselaer Polytechnic Institute
  • Minlie Huang, Tsinghua university
  • Seung-Won Hwang, POSTECH
  • Jing Jiang, Singapore Management University
  • Dan Jurafsky, Stanford University
  • Wai Lam, The Chinese University of Hong Kong
  • Hang Li, Huawei Technologies
  • Fangtao Li, Google Research
  • Juanzi Li, Tsinghua University
  • Qi Li, Queens College and Graduate Center, CUNY
  • Sujian Li, Peking university
  • Hao Li, Rensselaer Polytechnic Institute
  • Ee-Peng Lim, Singapore Management University
  • Chin-Yew Lin, Microsoft Research Asia
  • Wei Liu, IBM Thomas J. Watson Research Center
  • Zhiyuan Liu, Tsinghua University
  • Kang Liu, Institute of Automation, Chinese Academy of Sciences
  • Ting Liu, Harbin Institute of Technology
  • David McClosky, IBM Research
  • Samaneh Moghaddam, Simon Fraser University
  • Alessandro Moschitti, University of Trento
  • Vincent Ng, University of Texas at Dallas
  • Sinno Jialin Pan, i2r, a*star, Singapore
  • Emily Pitler, Google
  • Tieyun Qian, Wuhan University
  • Delip Rao, Johns Hopkins University
  • Alan Ritter, University of Washington
  • Hinrich Sch├╝tze, University of Munich
  • Satoshi Sekine, New York University
  • Benoit Favre, Laboratoire d’Informatique Fondamentale de Marseille
  • Shuming Shi, Microsoft Research Asia
  • Kyuseok Shim, Seoul National University
  • Partha Talukdar, Indian Institute of Science
  • Yoshimasa Tsuruoka, The University of Tokyo
  • Benjamin Van Durme, Johns Hopkins University
  • V.G.Vinod Vydiswaran, University of Michigan
  • Xiaojun Wan, Peking University
  • Houfeng Wang, Peking University
  • Chi Wang, University of Illinois at Urbana-Champaign
  • Michael Wiegand, Saarland University
  • Kam-Fai Wong, The Chinese University of Hong Kong
  • Wei Xu, New York University
  • Nianwen Xue, Brandeis University
  • Xin Zhao, Peking University and Singapore Management University
  • Dongyan Zhao, Peking University
  • Jun Zhao, Institute of Automation, Chinese Academy of Sciences
  • Guodong Zhou, Soochow University
  • Xiaoyan Zhu, Tsinghua University
  • Imed Zitouni, Microsoft
  • Chengqing Zong, Institute of Automation, Chinese Academy of Sciences