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Cross-Lingual Public Opinion Tracing Based on Blockchain Technology

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Web Information Systems and Applications (WISA 2020)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 12432))

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Abstract

One of the important issues of public opinion governance in the internet age is to study the characteristics and laws of the generation, development and spread of public opinion on complex social networks and to set up an effective tracing model based on blockchain technology. As a decentralized shared database, blockchain technology is tamper-resistant and traceable. Because of this, it is an important tool for containing the spread of fabricated public opinion, maintaining national security and stability, and protecting corporate image and personal interests. Given the current cross-lingual tracing technology and the fact that blockchain is decentralized and immutable, this project aims for establishing a blockchain-based cross-lingual public opinion tracing system targeting at the characteristics and laws of the spread of public opinion in social network. This study focuses on four aspects: the architecture that is based on complex chain structure; the consensus-based safety and liveness of the system; the management of the system based on smart contracts; standards and rules of this blockchain-based tracing technology. Through the study, a commonly used multilingual tracing system is expected to be built by using the sophisticated blockchain technology.

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References

  1. Liang, Y., Xu, L., Huang, T: Sentiment tendency analysis of NPC & CPPCC event in German news. In: 2019 16th International Conference on Web Information Systems and Applications, pp. 298–308 (2019). https://doi.org/10.1145/2976749.2978341

  2. Gervais, A., Karame, G., Wüst, K., et al.: On the security and performance of proof of work blockchains. In: ACM SIGSAC Conference on Computer and Communications Security, vol. 2016, pp. 3–16 (2016). https://doi.org/10.1145/2976749.2978341

  3. Tosh, D., Shetty, S., Foytik, P., et al.: CloudPoS: a proof-of-stake consensus design for blockchain integrated cloud. In: 2018 IEEE 11th International Conference on Cloud Computing (CLOUD) (2018). https://doi.org/10.13140/rg.2.2.20169.44640

  4. Sousa, J., Bessani, A.: Separating the WHEAT from the chaff: an empirical design for geo-replicated state machines. In: 34th IEEE Symposium on Reliable Distributed Systems (SRDS), pp. 146–155 (2015). https://doi.org/10.1109/srds.2015.40

  5. Wood, G.: Ethereum: a secure decentralised generalised transaction ledger. Ethereum Project Yellow Paper (2014). https://doi.org/10.1017/CBO9781107415324.004

  6. Prusty, N.: Building Blockchain Projects. Packt Publishing Ltd., Birmingham (2017)

    Google Scholar 

  7. Poon, J., Dryja, T.: The bitcoin lightning network: scalable off-chain instant payments (2016). https://lightning.network/lightning-network-paper.pdf

  8. Zhu, Y.: SEBDB: semantics empowered blockchain database. In: IEEE 35th International Conference on Data Engineering (ICDE). IEEE (2019). https://doi.org/10.1109/icde.2019.00198

  9. Li, X., Jiang, P., Chen, T., et al.: A survey on the security of blockchain systems. Future Gener. Comput. Syst. (2019). https://doi.org/10.1016/j.future.2017.08.020

  10. Microsoft: The Coco framework technical overview. White paper (2017)

    Google Scholar 

  11. Ben-Sasson, E., Chiesa, A., Genkin, D., et al.: SNARKs for C: verifying program executions succinctly and in zero knowledge. In: Canetti, R., Garay, J.A. (eds.) CRYPTO 2013. LNCS, vol. 8043, pp. 90–108. Springer, Heidelberg (2013). https://doi.org/10.1007/978-3-642-40084-1_6

    Chapter  MATH  Google Scholar 

  12. Ben-Sasson, E., Chiesa, A., Tromer, E., et al.: Succinct non-interactive zero knowledge for a von neumann architecture. In: 23rd USENIX Security Symposium, pp.781–796 (2014)

    Google Scholar 

  13. Nguyen, B., Cachin, C., Yellick, J., et al: Multichannel consensus (2016). https://docs.google.com/document/d/1eRNxxQ0P8yp4Wh__Vi6ddaN_vhN2RQHP-IruHNUwyhc/edit

  14. Carlyle, J.: CORDA performance: to infinity & beyond (2018). https://www.r3.com/wp-content/uploads/2018/04/Corda-Performance-ENG.pdf

  15. Croman, K., Decker, C., Eyal, I., et al.: On scaling decentralized blockchains. In: Clark, J., Meiklejohn, S., Ryan, P.Y.A., Wallach, D., Brenner, M., Rohloff, K. (eds.) FC 2016. LNCS, vol. 9604, pp. 106–125. Springer, Heidelberg (2016). https://doi.org/10.1007/978-3-662-53357-4_8

    Chapter  Google Scholar 

  16. Angelis, S., Aniello, L., Baldoni, R., et al: PBFT vs proof-of-authority: applying the CAP theorem to permissioned blockchain. In: 2nd Italian Conference on Cyber Security, pp. 1–11 (2018)

    Google Scholar 

  17. Su, Y., Zhang, C., Li, J.: Cross-lingual entity query from large-scale knowledge graphs. In: Cai, R., Chen, K., Hong, L., Yang, X., Zhang, R., Zou, L. (eds.) APWeb 2015. LNCS, vol. 9461, pp. 139–150. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-28121-6_13

    Chapter  Google Scholar 

  18. Jin, H., Li, C., Zhang, J., et al.: XLORE2: large-scale cross-lingual knowledge graph construction and application. Data Intell. 1(1), 77–98 (2019). https://doi.org/10.1162/dint_a_00003

    Article  Google Scholar 

  19. Wang, Z., Li, Z., Li, J., et al.: Transfer learning based cross-lingual knowledge extraction for Wikipedia. In: ACL, pp. 641–650 (2013)

    Google Scholar 

  20. Milan, D., Julio, H., Markus, A., et al.: DBpedia NIF: open, large-scale and multilingual knowledge extraction corpus. Computing Research Repository abs/1812.10315 (2018)

    Google Scholar 

  21. Gottschalk, I., Demidova, E.: EventKG: a multilingual event-centric temporal knowledge graph. In: Gangemi, A. (ed.) ESWC 2018. LNCS, vol. 10843, pp. 272–287. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-93417-4_18

    Chapter  Google Scholar 

  22. Dagmar, G., Maria, M.: Body-Mind-Language: multilingual knowledge extraction based on embodied cognition. In: AIC, pp. 20–33 (2017)

    Google Scholar 

  23. Cabral, B.S., Glauber, R., Souza, M.: CrossOIE: cross-lingual classifier for open information extraction. In: Quaresma, P., Vieira, R., Aluísio, S., Moniz, H., Batista, F., Gonçalves, T. (eds.) PROPOR 2020. LNCS (LNAI), vol. 12037, pp. 368–378. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-41505-1_35

    Chapter  Google Scholar 

  24. Wang, Z., Li, J., Tang, J.: Boosting cross-lingual knowledge linking via concept annotation. In: International Joint Conference on Artificial Intelligence, pp. 2733–2739 (2013)

    Google Scholar 

  25. Chen, M., Tian, Y., Yang, M., et al: Multilingual knowledge graph embeddings for cross-lingual knowledge alignment. In: International Joint Conference on Artificial Intelligence, pp. 1511–1517 (2017). https://doi.org/10.24963/ijcai.2017/209

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Acknowledgement

This work was supported in part by the Social Science Foundation of China (No. 15CTQ028), and the First-class Disciplines Construction Foundation of Beijing Foreign Studies University (No. YY19SSK02, No. 2020SYLZDXM040).

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Authors and Affiliations

  1. Artificial Intelligence and Human Languages Lab, School of Information Science and Technology, Beijing Foreign Studies University, Beijing, China

    Ye Liang & Ying Qin

Authors
  1. Ye Liang
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  2. Ying Qin
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Corresponding author

Correspondence to Ye Liang .

Editor information

Editors and Affiliations

  1. Guangzhou University, Guangzhou, China

    Guojun Wang

  2. The University of New South Wales, Sydney, NSW, Australia

    Xuemin Lin

  3. Rensselaer Polytechnic Institute, Troy, NY, USA

    James Hendler

  4. Wuhan University, Wuhan, China

    Wei Song

  5. Hohai University, Nanjing, China

    Zhuoming Xu

  6. Fuzhou University, Fuzhou, China

    Genggeng Liu

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Liang, Y., Qin, Y. (2020). Cross-Lingual Public Opinion Tracing Based on Blockchain Technology. In: Wang, G., Lin, X., Hendler, J., Song, W., Xu, Z., Liu, G. (eds) Web Information Systems and Applications. WISA 2020. Lecture Notes in Computer Science(), vol 12432. Springer, Cham. https://doi.org/10.1007/978-3-030-60029-7_54

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  • DOI: https://doi.org/10.1007/978-3-030-60029-7_54

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-60028-0

  • Online ISBN: 978-3-030-60029-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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