Indianapolis, USA, Oct. 28th, 2016

Our world is networked: people are closer to each other through online social network services or mobile communication networks, while information is capable to be exchanged faster by World Wide Web or email networks. The network is a treasure trove of user experiences and knowledge that presents great opportunities to understand the fundamental science of our world. On the other hand, the network, with huge amount of data, and multiple types of entities (e.g., users, documents, organizations, etc.), user behaviors, and relations between entities, has become so large and complex that traditional methodologies are inadequate.

This workshop aims to provide a forum for presenting the most recent advances in mining big networks to unearth rich knowledge. It is related to information retrieval, Web mining, social network analysis, and computational advertising. In particular, topics of interest include but are not limited to:

1. Novel algorithms for handling large-scaled networking data;
2. Data integration from multiple networks;
3. Clustering and ranking methods for big networks;
4. Large-scaled link prediction algorithms;
5. User influence analysis algorithms or information diffusion models;
6. Community detection in big networks;
7. Event detection and evolution analysis;
8. Graph based recommendations for web marketing or advertising
9. Visualization for big network data;
10. Suspicious behavior detection;
11. Representation learning for big networks;
12. Applications and platforms for social network.

The anticipated outcome includes a fruitful discussion about the emerging challenges in this field, the development of novel theories for mining big networks, and motivating the interesting applications. The broader anticipated outcome includes: fostering future research directions, publishing high quality papers, attracting new researchers to this field, and concrete solutions to the existing problems. 

• Submission deadline: July 25th, 2016  August 2nd, 2016
• Notification of acceptance: August 22rd, 2016
• Final papers due: September 1st, 2016
• Conference date: October 28

This workshop accept both long paper and short paper. Long papers should have a maximum length of 10 pages, and short papers should have a maximum length of 4 pages. All papers must be prepared using the ACM camera-ready template http://www.acm.org/sigs/pubs/proceed/template.html. Authors are required to submit their papers electronically in PDF format. The submission website is: https://easychair.org/conferences/?conf=bna2016.

All submissions should clearly present the author information including the names of the authors, the affiliations and the emails.

Keke Cai, IBM, China Research Lab

Zhong Su, IBM, China Research Lab

Jie Tang, Tsinghua University, China, http://keg.cs.tsinghua.edu.cn/jietang/

Hanghang Tong, Arizona State University, http://www.cs.cmu.edu/~htong/

Michalis Vazirgiannis, Ecole Polytechnique, http://www.lix.polytechnique.fr/~mvazirg/

Yang Yang, Tsinghua University, China, http://yangy.org/

Personalized Community Detection in Scholarly Network 
Author(s): Zheng Gao, Bloomington; Xiaozhong Liuf, Bloomington

Efficient Web Search Diversification via Approximate Graph Coverage 
Author(s): Jared Niederhauser, ETH Zurich; Carsten Eickhoff, ETH Zurich; Aurelien Lucchi, ETH Zurich; Thomas Hofmann, ETH Zurich

Active Learning with Sparse Reconstruction 
Author(s): Hanyi Zhang, Zhejiang University; Hanqing Lu, Zhejiang University; Ming Kong, Zhejiang University; Hanyin Fang, Zhejiang University; Zhou Zhao, Zhejiang University

An Algorithm for Extracting Schemas from External Memory Graphs 
Author(s): Yoshiki Sekine, University of Tsukuba; Kosetsu Lkeda, Chiba University; Nobutaka Suzuki, University of Tsukuba

PatternTree: A Pattern Graph Correlation Framework for Accelerating Subgraph Isomorphism over Massive Graphs 
Author(s): Meizi Zhou, Chinese Academy of Sciences; Jing Yu, Chinese Academy of Sciences; Yanbing Liu, Chinese Academy of Sciences; Qiong Dai, Chinese Academy of Sciences; Li Guo, Chinese Academy of Sciences

Identifying Health-Violating Restaurants with Online Reviews 
Author(s): Mikel Joaristi, Boise State University; Edoardo Serra, Boise State University; Francesca Spezzano, Boise State University

Real-time Topic Detection and Tracking in Microblog: Towards A Comprehensive Tweet Recommendation System 
Author(s): Karankumar Sabhnani, University of Delaware; Ben Carterette, University of Delaware

Tactics and Tallies: A Study of the 2016 U.S. Presidential Campaign Using Twitter 'Likes' 
Author(s): Yu Wang, University of Rochester; Xiyang Zhang, Beijing Normal University; Jiebo Luo, University of Rochester

Matching Law Cases and Reference Law Provision with a Neural Attention Model 
Author(s): Guoyu Tang, IBM China Research Laboratory; Honglei Guo, IBM China Research Laboratory; Zhili Guo IBM China Research Laboratory; Song Xu, IBM China Research Laboratory

Fragkiskos Malliaros, Ecole Polytechnique

 

Huaiyu Wan, Beijing Jiaotong University

Evangelos Papalexakis, Carnegie Mellon University

Meng Jiang, University of Illinois at Urbana-Champaign

Zitao Liu, Pinterest

Sucheta Soundarajan, Syracuse University

Chenhao Tan, Cornell University

Shenghua Bao, IBM Watson Group

Wei Zhang, East China Normal University

Yuan Yao, Huawei Tech.

Jing Zhang, Renmin Universit