Research and Prototype Implementation of Network Group Sentiment Analysis Based on Topic

Ya Hao He; Ya Ru Yang; Yu Zhong Qian; Jing Li

doi:10.4028/www.scientific.net/AMR.1042.218

Paper Titles

Design and Implementation of JMF-Based VOD System
p.197

Research and Implementation of Internet Topology Based on BRITE
p.203

Research and Implementation of Internet Topology Based on AB Model
p.207

Using FPGA to Accelerate Deduplication on High-Performance SSD
p.212

Research and Prototype Implementation of Network Group Sentiment Analysis Based on Topic
p.218

"The Last Kilometer" Network Optimization Research of E-Commerce
p.224

Optimization Study of Personalized Information Recommendation Model Based on Tensor Decomposition
p.228

A Modified Back Propagation Algorithm of Neural Network with Global Optimization
p.232

Study on the System Simulation Model of Personalized Information Recommendation
p.239

HomeAdvanced Materials ResearchAdvanced Materials Research Vol. 1042Research and Prototype Implementation of Network...

Research and Prototype Implementation of Network Group Sentiment Analysis Based on Topic

Abstract:

In the era of Web2.0, people in the social network make up a complex relationship called group by communicating with others, such as forward or comment. Such networks are typically abundant with valuable information which can be mined. We use data mining technology to analyze the network group structure based on different topics, divide the network group into multiple sub-communities, analyze sentiment tendency of different communities, views and frequent patterns, and present the overall characteristics of whole group visually to the users to help them make decisions.

You might also be interested in these eBooks

Materials Science and Intelligent Technologies Applications

View Preview

Info:

Periodical:

Advanced Materials Research (Volume 1042)

Pages:

218-223

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.1042.218

Citation:

Cite this paper

Online since:

October 2014

Authors:

Ya Hao He*, Ya Ru Yang, Yu Zhong Qian, Jing Li

Keywords:

Frequent Pattern, Network Group, Sentiment Analysis, System Integration, Topic

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

* - Corresponding Author

References

[1] Bollen J, Gonçalves B, Ruan G, et al. Happiness is assortative in online social networks[J]. Artificial life, 2011, 17(3): 237-251.

DOI: 10.1162/artl_a_00034

Google Scholar

[2] Qiu L, Zhang W, Hu C, et al. Selc: a self-supervised model for sentiment classification[C]/Proceedings of the 18th ACM conference on Information and knowledge management. ACM, 2009: 929-936.

DOI: 10.1145/1645953.1646072

Google Scholar

[3] Girvan M, Newman M E J. Community structure in social and biological networks[J]. Proceedings of the National Academy of Sciences, 2002, 99(12): 7821-7826.

DOI: 10.1073/pnas.122653799

Google Scholar

[4] Newman M E J. Detecting community structure in networks[J]. The European Physical Journal B-Condensed Matter and Complex Systems, 2004, 38(2): 321-330.

DOI: 10.1140/epjb/e2004-00124-y

Google Scholar

[5] Suykens J A K, Lukas L, Vandewalle J. Sparse least squares Support Vector Machine classifiers[C]/ESANN. 2000: 37-42.

Google Scholar

[6] Han J, Kamber M, Pei J. Data mining: concepts and techniques [M]. Morgan kaufmann, (2006).

Google Scholar