Positive and Negative Link Prediction Algorithm Based on Sentiment Analysis in Large Social Networks
Author:
Funder
Science and Engineering Research Board
Publisher
Springer Science and Business Media LLC
Subject
Electrical and Electronic Engineering,Computer Science Applications
Link
http://link.springer.com/article/10.1007/s11277-018-5499-6/fulltext.html
Reference37 articles.
1. Tang, J., Chang, S., Aggarwal, C., & Liu, H. (2015). Negative link prediction in social media. In Proceedings of the 8th ACM international conference on web search and data mining (pp. 87–96).
2. Tang, J., Chang, Y., & Liu, H. (2014). Mining social media with social theories: A survey. ACM SIGKDD Explorations Newsletter, 15(2), 20–29.
3. Tang, J., Chang, Y., Aggarwal, C., & Liu, H. (2016). A survey of signed network mining in social media. ACM Computing Surveys (CSUR), 49(3), 1–42.
4. Wen, S., Haghighi, M. S., Chen, C., Xiang, Y., Zhou, W., & Jia, W. (2015). A sword with two edges: Propagation studies on both positive and negative information in online social networks. IEEE Transactions on Computers, 64(3), 640–653.
5. Song, D., Meyer, D. A., & Tao, D. (2015). Efficient latent link recommendation in signed networks. In Proceedings of the 21th ACM SIGKDD international conference on knowledge discovery and data mining (pp. 1105–1114).
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