Skip to main content
Disciplines
Automotive Business IT + Informatics Construction + Real Estate Electrical Engineering + Electronics Energy + Sustainability Insurance + Risk Finance + Banking Management + Leadership Marketing + Sales Mechanical Engineering + Materials
Events
DE
EN
Books
Journals
Topic Page
Marketing
Start single access now
Access for companies
EXTENDED SEARCH
Log in
Top
Published in:

2024 | OriginalPaper | Chapter

Leveraging Graph Embedding for Opinion Leader Detection in Dynamic Social Networks

Authors : Yunming Hui, Mel Chekol, Shihan Wang

Published in: Artificial Intelligence. ECAI 2023 International Workshops

Publisher: Springer Nature Switzerland

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

Detecting opinion leaders from dynamic social networks is an important and complex problem. The few methods in this field are poor in generalisation and cannot fully consider various dynamic features. In this paper, we propose a novel and generic method based on dynamic graph embedding and clustering. Inspired by the existing knowledge about dynamic opinion leader detection, the proposed method can exploit both the topological and temporal information of dynamic social networks comprehensively. It is also generalisable, as shown experimentally on three different dynamic social network datasets. The experimental results show that the proposed method runs faster than competitors.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

inform now
next chapter Post–mining on Association Rule Bases
Appendix
Available only for authorised users
Footnotes
Literature
1.
Aggarwal, C.C., Lin, S., Yu, P.S.: On influential node discovery in dynamic social networks. In: Proceedings of the 2012 SIAM International Conference on Data Mining, pp. 636–647. SIAM (2012)
2.
Arvapally, R.S., Liu, X., Jiang, W.: Identification of faction groups and leaders in web-based intelligent argumentation system for collaborative decision support. In: 2012 International Conference on Collaboration Technologies and Systems (CTS), pp. 509–516. IEEE (2012)
3.
Bamakan, S.M.H., Nurgaliev, I., Qu, Q.: Opinion leader detection: a methodological review. Expert Syst. Appl. 115, 200–222 (2019)CrossRef
4.
Barros, C.D., Mendonça, M.R., Vieira, A.B., Ziviani, A.: A survey on embedding dynamic graphs. ACM Comput. Surv. (CSUR) 55(1), 1–37 (2021)CrossRef
5.
Cai, H., Zheng, V.W., Chang, K.C.C.: A comprehensive survey of graph embedding: problems, techniques, and applications. IEEE Trans. Knowl. Data Eng. 30(9), 1616–1637 (2018)CrossRef
6.
Chan, K.K., Misra, S.: Characteristics of the opinion leader: a new dimension. J. Advert. 19(3), 53–60 (1990)CrossRef
7.
Chen, Y.C., Cheng, J.Y., Hsu, H.H.: A cluster-based opinion leader discovery in social network. In: 2016 Conference on Technologies and Applications of Artificial Intelligence (TAAI), pp. 78–83. IEEE (2016)
8.
Chen, Y.C., Hui, L., Wu, C.I., Liu, H.Y., Chen, S.C.: Opinion leaders discovery in dynamic social network. In: 2017 10th International Conference on Ubi-media Computing and Workshops (Ubi-Media), pp. 1–6. IEEE (2017)
9.
Cordeiro, M., Sarmento, R.P., Brazdil, P., Gama, J.: Evolving networks and social network analysis methods and techniques. In: Social Media and Journalism-Trends, Connections, Implications, pp. 101–134 (2018)
10.
Du, L., Wang, Y., Song, G., Lu, Z., Wang, J.: Dynamic network embedding: an extended approach for skip-gram based network embedding. In: IJCAI, vol. 2018, pp. 2086–2092 (2018)
11.
Duan, J., Zeng, J., Luo, B.: Identification of opinion leaders based on user clustering and sentiment analysis. In: 2014 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT), vol. 1, pp. 377–383. IEEE (2014)
12.
Gao, C., Wei, D., Hu, Y., Mahadevan, S., Deng, Y.: A modified evidential methodology of identifying influential nodes in weighted networks. Phys. A 392(21), 5490–5500 (2013)MathSciNetCrossRef
13.
Hafiene, N., Karoui, W., Romdhane, L.B.: Influential nodes detection in dynamic social networks: a survey. Expert Syst. Appl. 159, 113642 (2020)CrossRef
14.
Huang, B., Yu, G., Karimi, H.R., et al.: The finding and dynamic detection of opinion leaders in social network. Math. Prob. Eng. 2014, 7 (2014)
15.
Jain, L., Katarya, R., Sachdeva, S.: Opinion leaders for information diffusion using graph neural network in online social networks. ACM Trans. Web 17(2), 1–37 (2023)CrossRef
16.
Katz, E., Lazarsfeld, P.F.: Personal Influence: The Part Played by People in the Flow of Mass Communications. Routledge (2017)
17.
Li, Y., Chen, W., Wang, Y., Zhang, Z.L.: Influence diffusion dynamics and influence maximization in social networks with friend and foe relationships. In: Proceedings of the Sixth ACM International Conference on Web Search and Data Mining, pp. 657–666 (2013)
18.
Li, Y., Fan, J., Wang, Y., Tan, K.L.: Influence maximization on social graphs: a survey. IEEE Trans. Knowl. Data Eng. 30(10), 1852–1872 (2018)CrossRef
19.
20.
Lü, L., Zhang, Y.C., Yeung, C.H., Zhou, T.: Leaders in social networks, the delicious case. PLoS ONE 6(6), e21202 (2011)CrossRef
21.
Luo, J., Du, Y., Li, R., Cheng, F.: Identification of opinion leaders by using social network embedding. In: 2019 IEEE 5th International Conference on Computer and Communications (ICCC), pp. 1412–1416. IEEE (2019)
22.
Ma, Y., Guo, Z., Ren, Z., Tang, J., Yin, D.: Streaming graph neural networks. In: Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 719–728 (2020)
23.
Van der Maaten, L., Hinton, G.: Visualizing data using t-SNE. J. Mach. Learn. Res. 9(11), 2579–2605 (2008)
24.
Michalski, R., Jankowski, J., Bródka, P.: Effective influence spreading in temporal networks with sequential seeding. IEEE Access 8, 151208–151218 (2020)CrossRef
25.
Nguyen, G.H., Lee, J.B., Rossi, R.A., Ahmed, N.K., Koh, E., Kim, S.: Continuous-time dynamic network embeddings. In: Companion Proceedings of the the Web Conference 2018, pp. 969–976 (2018)
26.
27.
Oueslati, W., Arrami, S., Dhouioui, Z., Massaabi, M.: Opinion leaders’ detection in dynamic social networks. Concurrency Comput. Pract. Exp. 33(1), e5692 (2021)CrossRef
28.
Page, L., Brin, S., Motwani, R., Winograd, T.: The pagerank citation ranking: bringing order to the web. Tech. rep. Stanford InfoLab (1999)
29.
Panzarasa, P., Opsahl, T., Carley, K.M.: Patterns and dynamics of users’ behavior and interaction: network analysis of an online community. J. Am. Soc. Inform. Sci. Technol. 60(5), 911–932 (2009)CrossRef
30.
Risselada, H., Verhoef, P.C., Bijmolt, T.H.: Indicators of opinion leadership in customer networks: self-reports and degree centrality. Mark. Lett. 27(3), 449–460 (2016)CrossRef
31.
Rossi, E., Chamberlain, B., Frasca, F., Eynard, D., Monti, F., Bronstein, M.: Temporal graph networks for deep learning on dynamic graphs. arXiv preprint arXiv:​2006.​10637 (2020)
32.
Sankar, A., Wu, Y., Gou, L., Zhang, W., Yang, H.: DySAT: deep neural representation learning on dynamic graphs via self-attention networks. In: Proceedings of the 13th International Conference on Web Search and Data Mining, pp. 519–527 (2020)
33.
Sharma, K., Bajaj, M., et al.: A review on opinion leader detection and its applications. In: 2022 7th International Conference on Communication and Electronics Systems (ICCES), pp. 1645–1651. IEEE (2022)
34.
35.
Tang, J., Lou, T., Kleinberg, J.: Inferring social ties across heterogenous networks. In: Proceedings of the fifth ACM International Conference on Web Search and Data Mining, pp. 743–752 (2012)
36.
Trivedi, R., Farajtabar, M., Biswal, P., Zha, H.: DyRep: learning representations over dynamic graphs. In: International Conference on Learning Representations (2019)
37.
Valente, T.W., Pumpuang, P.: Identifying opinion leaders to promote behavior change. Health Educ. Behav. 34(6), 881–896 (2007)CrossRef
38.
Wu, L., Zhao, H., Li, Z., Huang, Z., Liu, Q., Chen, E.: Learning the explainable semantic relations via unified graph topic-disentangled neural networks. ACM Trans. Knowl. Discov. Data 17(8), 1–23 (2023)CrossRef
39.
Xue, G., Zhong, M., Li, J., Chen, J., Zhai, C., Kong, R.: Dynamic network embedding survey. Neurocomputing 472, 212–223 (2022)CrossRef
40.
Yang, L., Qiao, Y., Liu, Z., Ma, J., Li, X.: Identifying opinion leader nodes in online social networks with a new closeness evaluation algorithm. Soft. Comput. 22(2), 453–464 (2018)CrossRef
41.
Yang, X.H., et al.: Identifying influential spreaders in complex networks based on network embedding and node local centrality. Phys. A 573, 125971 (2021)CrossRef
42.
Yu, W., Cheng, W., Aggarwal, C.C., Zhang, K., Chen, H., Wang, W.: NetWalk: a flexible deep embedding approach for anomaly detection in dynamic networks. In: Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, pp. 2672–2681 (2018)
43.
Zhuang, H., Sun, Y., Tang, J., Zhang, J., Sun, X.: Influence maximization in dynamic social networks. In: 2013 IEEE 13th International Conference on Data Mining, pp. 1313–1318. IEEE (2013)
Metadata
Title
Leveraging Graph Embedding for Opinion Leader Detection in Dynamic Social Networks
Authors
Yunming Hui
Mel Chekol
Shihan Wang
Copyright Year
2024
Book
Artificial Intelligence. ECAI 2023 International Workshops

Print ISBN: 978-3-031-50484-6

Electronic ISBN: 978-3-031-50485-3

Copyright Year: 2024

DOI
https://doi.org/10.1007/978-3-031-50485-3_1

Premium Partner

    Image Credits