Lei Wang
Affiliations:- Beihang University, State Key Lab of Virtual Reality Technology and Systems, China
According to our database1,
Lei Wang
authored at least 16 papers
between 2014 and 2020.
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Bibliography
2020
SentiDiff: Combining Textual Information and Sentiment Diffusion Patterns for Twitter Sentiment Analysis.
IEEE Trans. Knowl. Data Eng., 2020
2019
GMA: An adult account identification algorithm on Sina Weibo using behavioral footprints.
Future Gener. Comput. Syst., 2019
The Silent Majority Speaks: Inferring Silent Users' Opinions in Online Social Networks.
Proceedings of the World Wide Web Conference, 2019
2018
SentiRelated: A cross-domain sentiment classification algorithm for short texts through sentiment related index.
J. Netw. Comput. Appl., 2018
Future Gener. Comput. Syst., 2018
Mining of marital distress from microblogging social networks: A case study on Sina Weibo.
Future Gener. Comput. Syst., 2018
Proceedings of the 2018 IEEE International Conference on Communications, 2018
2017
Logarithmic gravity centrality for identifying influential spreaders in dynamic large-scale social networks.
Proceedings of the IEEE International Conference on Communications, 2017
2016
FUIR: Fusing user and item information to deal with data sparsity by using side information in recommendation systems.
J. Netw. Comput. Appl., 2016
Structural properties and generative model of non-giant connected components in social networks.
Sci. China Inf. Sci., 2016
Proceedings of the 14th IEEE International Conference on Industrial Informatics, 2016
Proceedings of the 14th IEEE International Conference on Industrial Informatics, 2016
Proceedings of the 2016 IEEE Global Communications Conference, 2016
2015
Cross-Domain Sentiment Analysis of Product Reviews by Combining Lexicon-Based and Learn-Based Techniques.
Proceedings of the 17th IEEE International Conference on High Performance Computing and Communications, 2015
2014
Detecting collusive cheating in online shopping systems through characteristics of social networks.
Proceedings of the 2014 Proceedings IEEE INFOCOM Workshops, Toronto, ON, Canada, April 27, 2014
K-hop centrality metric for identifying influential spreaders in dynamic large-scale social networks.
Proceedings of the IEEE Global Communications Conference, 2014