Social context-aware trust paths finding for trustworthy service provider selection in social media

  • Junwen Lu
  • Guanfeng LiuEmail author
  • Bolong Zheng
  • Yan Zhao
  • Kai Zheng


Online Social Network (OSN) has been used to enhance service provision and service selection, where trust is one of the most important factors for the decision making of service consumers. Thus, a significant and challenging problem is how to effectively and efficiently find those social trust paths that can yield trustworthy trust evaluation results based on the requirements of a service consumer particularly in contextual OSNs which contains social contexts, like social relationships and social trust between participants, and social positions of participants. In this paper, we propose a new concept called Strong Social Graph (SSG), consisting of participants with strong social connections. We also propose an approach to identify SSGs, and propose a novel index method and a graph compression method for SSG. Then based on the compressed SSG and indices, we propose a new efficient and effective approximation algorithm, called SSG-MCBA by adopting the Monte Carlo method and our optimization search strategies. The experiments conducted onto two real social network datasets illustrate that SSG-MCBA greatly outperforms the state-of-the-art method in both efficiency and effectiveness.


Social network Trust Service provider selection 



  1. 1.
    Adler PS (2001) Market, hierarchy, and trust: The knowledge economy and the future of capitalism. Organ Sci 12(12):215–234CrossRefGoogle Scholar
  2. 2.
    Berger P, Luckmann T (1967) The social construction of reality: a treatise in the sociology of knowledge. The Social Construction of RealityGoogle Scholar
  3. 3.
    Biggs N, Lloyd E, Wilson R (1986) Graph Theory. Oxford University PressGoogle Scholar
  4. 4.
    Chard K, Bubendorfer K, Caton S, Rana OF (2012) Social cloud computing: A vision for socially motivated resource sharing. IEEE Trans Serv Comput 5(4):551–563CrossRefGoogle Scholar
  5. 5.
    Chua F, Lim E-P (2010) Trust network inference for online rating data using generative models. In: KDD’10, pp. 889–898Google Scholar
  6. 6.
    Dijkstra E (1959) A note on two problems in connexion with graphs. Numerische Mathematik, pp. 269–271Google Scholar
  7. 7.
    Fan W, Li J, Wang X, Wu Y (2012) Query preserving graph compression. In: SIGMOD’12, pp. 157–168Google Scholar
  8. 8.
    Fan W, Wang X, Wu Y (2014) Answering graph pattern queries using views. In: ICDE’14, pp. 184–195Google Scholar
  9. 9.
    Gentle J, Hardle W, Mori Y (2004) Handbook of Computational Statistics. SpringerGoogle Scholar
  10. 10.
    Golbeck J, Hendler J (2006) Inferring trust relationships in webbased social networks. ACM Trans Internet Technol 6(4):497–529CrossRefGoogle Scholar
  11. 11.
    Hang C, Wang Y, Singh M (2009) Operators for propagating trust and their evaluation in social networks. In: AAMAS’09, pp. 1025–1032Google Scholar
  12. 12.
    Korte RF (2003) Biases in decision making and implications for human resource development. Adv Dev Hum Resour 5(4):440–457CrossRefGoogle Scholar
  13. 13.
    Kuter U, Golbeck J (2007) Sunny: A new algorithm for trust inference in social networks using probabilistic confidence model. In: AAAI’07, pp. 1377–1382Google Scholar
  14. 14.
    Li J, Lu K, Huang Z, Zhu L, Shen HT (2018) Transfer independently together: a generalized framework for domain adaptation. In: IEEE TCYBGoogle Scholar
  15. 15.
    Li J, Wu Y, Zhao J, K L (2017) Low-rank Discriminant Embedding for Multiview Learning. IEEE TCYB 47(11):3516–3529Google Scholar
  16. 16.
    Lin C, Cao N, Liu S, Papadimitriou S, Sun J, Yan X (2009) Smallblue: Social network analysis for expertise search and collective intelligence,” In: ICDE’09, pp. 1483–1486Google Scholar
  17. 17.
    Liu G, Liu A, Wang Y, Li L (2014) An efficient multiple trust paths finding algorithm for trustworthy service provider selection in real-time online social network environments. In: ICWS’14Google Scholar
  18. 18.
    Liu G, Wang Y, Orgun MA (2010a) Optimal social trust path selection in complex social networks. In: AAAI’10, pp. 1397–1398Google Scholar
  19. 19.
    Liu G, Wang Y, Orgun MA (2010b) Quality of trust for social trust path selection in complex social networks. In: AAMAS’10, pp. 1575–1576Google Scholar
  20. 20.
    Liu G, Wang Y, Orgun MA (2011a) Finding k optimal social trust paths for the selection of trustworthy service providers in complex social networks. In: ICWS’11, pp. 41–48Google Scholar
  21. 21.
    Liu G, Wang Y, Orgun MA (2011b) Trust transitivity in complex social networks. In: AAAI’11, pp. 1222–1229Google Scholar
  22. 22.
    Liu G, Wang Y, Orgun M, Lim E-P (2010) A heuristic algorithm for trust-oriented service provider selection in complex social networks. In: SCC, pp. 130–137Google Scholar
  23. 23.
    Liu G, Wang Y, Orgun MA, Lim E-P (2013) Finding the optimal social trust path for the selection of trustworthy service providers in complex social networks. IEEE Transactions on Services Computing 152–167Google Scholar
  24. 24.
    Liu G, Wang Y, Wong D (2012) Multiple qot constrained social trust path selection in complex social networks. In: TrustCom’12Google Scholar
  25. 25.
    Liu L, Zhu L, Li Z (2017) Learning Robust Graph Hashing for Efficient Similarity Search. In: ADC2017, pp. 110–122Google Scholar
  26. 26.
    Lo D, Surian D, Zhang K, Lim E-P (2011) Mining direct antagonistic communities in explicit trust networks. in CIKM’11, pp. 1013–1018Google Scholar
  27. 27.
    Mccallum A, Wang X, Corrada-Emmanuel A (2007) Topic and role discovery in social networks with experiments on Enron and academic email. J Artif Intell Res 30(1):249–272CrossRefGoogle Scholar
  28. 28.
    Milgram S (1967) The small world problem. Psychol Today 2(60)Google Scholar
  29. 29.
    Miller R, Perlman D, Brehm S (2007) Intimate Relationships, 4th ed. McGraw-Hill CollegeGoogle Scholar
  30. 30.
    Mislove A, Marcon M, Gummadi K, Druschel P, Bhattacharjee B (2007) Measurement and analysis of online social networks. In: ACM IMC’07, pp. 29–42Google Scholar
  31. 31.
    Morton D, Popova E (2009) Monte-Carlo simulation for stochastic optimization. Encyclopedia of Optimization 2337–2345Google Scholar
  32. 32.
    Pool I, Kochen M (1978) Contacts and influence. Soc Networks 1:1–48MathSciNetCrossRefGoogle Scholar
  33. 33.
    Shin Y, Lim J, Park J (2012) Joint optimization of index freshness and coverage in real-time search engines. IEEE Trans Knowl Data Eng 24(12):2203–2217CrossRefGoogle Scholar
  34. 34.
    Sun Z, Wang H, Wang H, Shao B, Li J (2012) Efficient subgraph matching on billion node graphs. In: VLDB’12, pp. 788–799Google Scholar
  35. 35.
    Tang J, Gao H, Liu H, Sarma AD (2012) etrust: Understanding trust evolution in an online world. In: KDD’12, pp. 253–261Google Scholar
  36. 36.
    Tang J, Zhang J, Yan L, Li J, Zhang L, Su Z (2008) Arnetminer: Extraction and mining of academic social networks. In: KDD’08, pp. 990–998Google Scholar
  37. 37.
    Wang Y, Li L, Liu G (2013) Social context-aware trust inference for trust enhancement in social network based recommendations on service providers. World Wide Web JournalGoogle Scholar
  38. 38.
    Wang Y, Varadharajan V (2007) Role-based recommendation and trust evaluation. In: IEEE EEE’07, pp. 278–295Google Scholar
  39. 39.
    Wang G, Wu J (2011) Multi-dimensional evidence-based trust management with multi-trusted paths. Futur Gener Comput Syst 17:529–538CrossRefGoogle Scholar
  40. 40.
    Wang L, Zhu L, Dong X, Liu L, Sun J, Zhang H (2018) Joint Feature Selection and Graph Regularization for Modality-Dependent Cross-Modal Retrieval. J Vis Commun Image Represent 54:213–222CrossRefGoogle Scholar
  41. 41.
    Xie L, Zhu L, Chen G (2016) Unsupervised Multi-Graph Cross-Modal Hashing for Large-Scale Multimedia Retrieval. Journal of Multimedia Tools and Applications 75(15):9185–9204CrossRefGoogle Scholar
  42. 42.
    Yao Y, Tong H, Yan X, Xu F, Lu J (2013) Matri: A multi-aspect and transitive trust inference model. In: WWW’13, pp. 1467–1476Google Scholar
  43. 43.
    Zheng K, Zheng B, Xu J, Liu G, Liu A, Li Z (2017) Popularity-Aware Spatial Keyword Search on Activity Trajectories. WWWJ 20(4):749–773CrossRefGoogle Scholar
  44. 44.
    Zhu Y, Qin L, Xu JX, Cheng H (2012) Finding top-k similar graphs in graph databases. In: EDBT’12, pp. 456–467Google Scholar
  45. 45.
    Zhu L, Shen J, Jin H, Zheng R, Xie L (2015) Content-Based Visual Landmark Search via Multimodal Hypergraph Learning. IEEE TCYB 45(12):2756–2769Google Scholar
  46. 46.
    Zhu L, Shen J, Xie L, Cheng Z (2016) Unsupervised Topic Hypergraph Hashing for Efficient Mobile Image Retrieval. IEEE TCYB 47(11):3941–3954Google Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  • Junwen Lu
    • 1
  • Guanfeng Liu
    • 2
    Email author
  • Bolong Zheng
    • 3
  • Yan Zhao
    • 4
  • Kai Zheng
    • 5
  1. 1.Engineering Research Center for Software Testing and Evaluation of Fujian ProvinceXiamen University of TechnologyXiamenChina
  2. 2.Department of ComputingMacquarie UniversitySydneyAustralia
  3. 3.School of Computer Science and TechnologyHuazhong University of Science and TechnologyWuhanChina
  4. 4.School of Computer Science and TechnologySoochow UniversitySuzhouChina
  5. 5.School of Computer Science and Engineering and Big Data Research CenterUniversity of Electronic Science and Technology of ChinaChengduChina

Personalised recommendations