BSMDMA-SocialNLP Workshop @ IEEE BigData 2017
|08:30~09:30||Opening (Location: Helicon Room - 7th Floor)
Keynote Talk: Computational Methods for Team Formation
by Prof. Evimaria Terzi, Boston University
Section I (Session Chair: Prof. Hsiao-Wei Hu)
(Location: Helicon Room - 7th Floor)
 Identifying emergency stages in Facebook posts of police departments with convolutional and recurrent neural networks and support vector machines. Nicolai Pogrebnyakov and Edgar Maldonado.
 Characterization of daily tourism behaviors based on place sequence analysis from photo sharing websites. Thomas-Joseph Loiseau, Sonia Djebali, Thomas Raimbault, Bérengère Branchet and Gaël Chareyron.
 Ticket-Purchase behavior under the Effects of Marketing Campaigns on Facebook Fan Pages. Hsiao-Wei Hu, Ching-Han Cheng, Yun-Chu Chung and Chia-Yu Lee.
 Outbound Behavior Analysis Through Social Network Data: a case study of Chinese people in Japan. TIANQI XIA, Xuan Song, Dou Huang, Satoshi Miyazawa, Zipei Fan, Renhe Jiang and Ryosuke Shibasaki.
 PSEISMIC: A Personalized Self-Exciting Point Process Model for Predicting Tweet Popularity. Hsin-Yu Chen and Cheng-Te Li.
Section II (Session Chair: Prof. Wei-Lun Chang)
(Location: Helicon Room - 7th Floor)
 Detection of Profile Injection Attacks in Social Recommender Systems Using Outlier Analysis. Anahita Davoudi and Mainak Chatterjee.
 Evaluating the Quality of Graph Embeddings via Topological Feature Reconstruction. Stephen Bonner, John Brennan, Ibad Kureshi, Georgios Theodoropoulos, Stephen McGough and Boguslaw Obara.
 Topic Life Cycle Extraction from Big Twitter Data based on Community Detection in Bipartite Networks. Takako Hashimoto, Hiroshi Okamoto, Tetsuji Kuboyama and Kilho Shin.
 Using Sentiment Analysis to Explore the Degree of Risk in Sharing Economy. Wei-Lun Chang.
 Big Social Data Analytics for Public Health: Comparative Methods Study and Performance Indicators of Health Care Content on Facebook. Nadiya Straton, Raghava Rao Mukkamala and Ravi Vatrapu.
 A Big Social Media Data Study of the 2017 German Federal Election based on Social Set Analysis of Political Party Facebook Pages with SoSeVi. Benjamin Flesch, Ravi Vatrapu and Raghava Rao Mukkamala.
 Digital Content Recommendation System Using Implicit Feedback Data. Saayan Mitra, Viswanathan Swaminathan, Ratnesh Kumar and Gang Wu.
Section III (Session Chair: Prof. Takako Hashimoto)
(Location: St. George C - 3rd Floor)
 Detecting Polarization in Ratings: An Automated Pipeline and a Preliminary Quantification on Several Benchmark Data Sets. Mahsa Badami, olfa Nasraoui, Wenlong Sun and Patrick Shafto.
 Language Identification in Multilingual, Short and Noisy Texts using Common N-Grams. Dijana Kosmajac and Vlado Keselj.
 Characterizing Online Community Practices with Orthographic Variation. Ian Stewart, Stevie Chancellor, Munmun De Choudhury and Jacob Eisenstein.
 Using an Asset Price Bubble Model in Tweet Analytics. K.M. George.
 An Entity Disambiguation Method Based on LeaderRank. Bingjing Jia, Bin Wu, Jinna Lv, Pengpeng Zhou, Yao Bu and Ying Xing.
 Improving Arabic Sentiment Analysis with Sentiment-Specific Embeddings. A. Aziz Altowayan and Ashraf Elnagar.
 Topic Modelling enriched LSTM Models for the Detection of Novel and Emerging Named Entities from Social Media. Patrick Jansson and Shuhua Liu.
 Differences in Emoji Sentiment Perception between Readers and Writers. Jose Berengueres and Dani Castro.
Call for Papers
The rich proliferation of many social media platforms is widely by used people on smartphone devices all over the world. At the same time, the incremental data of online social networks (e.g., Facebook), microblogs (e.g., Twitter), multi-media sites (e.g., YouTube, Instagram) and user review sites (e.g., Yelp) are imposing new challenges for the efficient data management and analysis query processing. On one hand, online social networks are undergoing rapid changes, not only on the dynamic graph structure, but also in the new information of updating user profiles, new hashtags in posters, as well as breakthrough events. On the other hand, the size of social media data is becoming bigger and bigger due to, e.g., the explosion of new posters and also the massive amount of users. Utilizing new technologies for efficient handling big social media data management is of urgent importance. However, numerous essential issues in this area have yet to be explored, including data crawling and modeling, storage, indexes, querying and mining, privacy, and so on.
The 2017 International Workshop on Big Social Media Data Management and Analysis (BSMDMA2017) aims to provide a forum for presenting the most recent advances in most recent advances in data management and mining on online social media, related to web search and information retrieval, social network analysis, visualization and summarization, and network science. The BSMDMA2017 will be in conjunction with 2017 IEEE International Conference on Big Data (IEEE Big Data 2017) on December 11-14, 2017, Boston, MA, USA. We are particularly interested in articles that address how to handle query processing on large-scale and dynamic social media data as well as their novel applications for social media platforms. Topics of interest include but are not limited to:
- Social networks crawling
- Community detection/search
- Large-scale complex network analysis
- Big graph management and mining
- Keyword/microblog search
- Text summarization
- Social media analysis
- Argumentation mining
- Privacy-aware computing in social network
- Social content processing
- Role identification and relation analysis in social network
- Querying and mining problems on location-based social networks
- Evolution patterns in dynamics networks/graph streaming
- Distributed graph query processing
The workshop accepts short (4-6 pages) and long papers (up to 10 pages). Paper submissions should be formatted according to the IEEE conference template. All submissions should clearly present the author information including the names of the authors, the affiliations and the emails. The review process is single-blinded. Papers must be submitted electronically as PDF files to BSMDMA2017 workshop at IEEE Big Data 2017 through CyberChair.
Submissions must be original (not previously published and not under review in other forums). Authors are advised to interpret these limitations strictly and to contact the organizers in case of doubt. Each accepted paper must be accompanied by at least one full registration, and an author is expected to present the paper at the conference, otherwise, the paper will be removed from the proceedings. All accepted papers will be EI-indexed.
- Hong Cheng, The Chinese University of Hong Kong, Hong Kong
- Jianxin Li, The University of Western Australia, Australia
- Rui Chen, Samsung Research, USA
- Xin Huang, Hong Kong Baptist University, Hong Kong
- Xuan Song, The University of Tokyo, Japan
- Bolei Zhou, MIT, USA
- Glenn Bevilacqua, University of British Columbia, Canada
- Hongyun Cai, Advanced Digital Sciences Center, Singapore
- Wei Cai, University of British Columbia, Canada
- Xin Cao, The University of New South Wales, Australia
- Lijun Chang, University of Sydney, Australia
- Yixiang Fang, Hong Kong University, Hong Kong
- Di Jin, Tianjing University, China
- Yunwen Lei, City University of Hong Kong, Hong Kong
- Sophie Li, Amazon, Canada
- Yafei Li, Zhengzhou University, China
- Jianquan Liu, NEC Cooperation, Japan
- Zheng Liu, Nanjing University of Posts and Telecommunications, China
- Wei Lu, Rupert Labs Inc, USA
- Lu Qin, University of Technology Sydney, Australia
- Yu Rong, Tencent, China
- Zechao Shang, University of Chicago, USA
- Yunya Song, Hong Kong Baptist University, Hong Kong
- Sharan Vaswani, University of British Columbia, Canada
- Yubao Wu, Georgia State University, USA
- Jilian Zhang, Jinan University, China
- Lei Zhang, Chongqing University, China
- Xiaofei Zhang, University of Waterloo, Canada
- Zhiwei Zhang, Hong Kong Baptist University, Hong Kong
BSMDMA2017 is co-located with IEEE Big Data 2017, which will share information in attending the conference. Please check following important links before you plan your itinerary.
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