Call for Papers

Web Mining and Content Analysis Track

We invite research contributions to the Web Mining and Content Analysis Track at the 31st edition of the Web Conference series (formerly known as WWW), to be held April 20-24, 2020 in Taipei (

The Web Mining and Content Analysis track welcomes submissions of original and high-quality research papers related to the extraction of information from the Web, the analysis of the Web text and social media content, recommendation, and mining of the Web usage data. We especially encourage submissions that propose novel and principled techniques or algorithms that can leverage the special characteristics of the Web, its social media, and user behaviors for such extraction and mining. In addition to new techniques and algorithms, we also seek insights gained from the mining process.

Topics include (but are not limited to):

Machine Learning and Data Science for the Web

  • Learning representation and features from Web data
  • Machine learning algorithms for large-scale content mining
  • Content mining of multimedia and multimodal Web data
  • Web data integration and cleaning
  • Visualization of Web data

Language Technologies and the Web

  • Human-machine dialogue and question answering
  • Bridging unstructured and structured data
  • Fact-checking and detection of misinformation and disinformation
  • Content mining of multilingual and cross-lingual Web data
  • Normalization, clustering, classification, and summarization of Web text
  • Extraction of entity, attributes, relations, and events
  • Topic discovery
  • Sentiment analysis and opinion mining
  • Content-based information diffusion
  • Other forms Web text and social media mining

Web Activities and Dynamics

  • Web traffic and log data analysis
  • Recommendation systems
  • Web measurements
  • Information diffusion on the Web
  • Models for Web evolution
  • Predictive analytics over Web datasets
  • Other novel applications

Track Chairs:

Min Zhang , Tsinghua University
Paul Bennett , Microsoft Research