My Research and Publication Platforms

My Journal Platforms of Interest

Computational Social Networks

Focus on common principles, algorithms and tools that govern network structures/topologies, network functionalities, security and privacy, network behaviors, information diffusions and influence, social recommendation systems which are applicable to all types of social networks and social media. Topics include (but are not limited to) the following:

  • Social network design and architecture
  • Mathematical modeling and analysis
  • Real-world complex networks
  • Information retrieval in social contexts, political analysts
  • Network structure analysis
  • Network dynamics optimization
  • Complex network robustness and vulnerability
  • Information diffusion models and analysis
  • Security and privacy
  • Searching in complex networks
  • Efficient algorithms
  • Network behaviors
  • Trust and reputation
  • Social Influence
  • Social Recommendation
  • Social media analysis
  • Big data analysis on online social networks

Journal of Big Data

The journal examines the challenges facing big data today and going forward including, but not limited to: data capture and storage; search, sharing, and analytics; big data technologies; data visualization; architectures for massively parallel processing; data mining tools and techniques; machine learning algorithms for big data; cloud computing platforms; distributed file systems and databases; and scalable storage systems.

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Automatic Recognition of Product Mentions in Text Corpora

Kaggle Competition

Identify product mentions within a largely user-generated web-based corpus and disambiguate the mentions against a large product catalog.


  • to automatically identify all mentions of consumer products in a largely user-generated collection of web content, and to correctly identify the product(s) that each product mention refers to from a large catalog of products.


  • hundreds of thousands of text items, a product catalog with over fifteen million products, and hundreds of manually annotated product mentions supporting data-driven approaches.



1st Zhanpeng Fang

2nd: Olexandr Topchylo