Trusting the Social Web

The phenomenon of the Social Web (i.e., the Web of Social Media) has caught the attention of research communities in the last decade. Researchers from diverse disciplines ranging from social and behavioural sciences to computer science have started investigating the issues and challenges in the Social Web. Within computer science, researchers from established research areas such as language technologies and machine learning, and service and cloud computing have started to look into the computational and development challenges brought about by the Social Web. With the continued reports of breach of trust and hoax news spreading from social media to mainstream news, trusting the Social Web has become one of the major challenges that needs to be addressed.

DSS developed the interactions based trust model for social web, with the specific focus on trust propagation and influence. The unique feature of our trust model is that it considers not only the interaction network, but also the content (e.g., comments, feedback, etc.) of the interactions within the certain context. The proposed approach has been applied in two key applications:

  • Service web – in order to select the best services in the service ecosystems; in this area, the work has been carried out in collaboration with prominent researchers in web services and service oriented architecture.
  • Social networks – in order to select the influential nodes with the aim of understanding and maximising the influence; this work has been carried out in collaboration with Cecile Paris from Decision Sciences.

Note: DSS has significantly reduced its efforts in this area within Data61. In addition, Wanita Sherchan and Sanat Bista, two postdoctoral fellows working in this area, have left the group. The personnel hired as replacements have expertise in the new focus area outlined the science vision section earlier.


  • Collaboration with prominent web services and cloud computing researchers.
  • Research+ PostDoctoral Fellow grant to work on influence (with Cecile Paris and Ross Sparks from Decision Sciences).
  • Appointment of Dr Surya Nepal as Associate Editor of IEEE Trans. Service Computing in recognition of his work on trust.
  • This work is carried out in close collaboration with Cecile Paris. 
  • NextStep – social trust in online community (funded by Centerlink for three years).
  • TwitRipple/SocialTraits – influence propagation in social network (funded by Centerlink – continue).
  • Robertus Nugroho, Weiliang Zhao, Jian Yang, Cecile Paris, Surya Nepal:  Using time-sensitive interactions to improve topic derivation in twitter. World Wide Web 20(1): 61-87 (2017) [IF 1.4].
  • Athman Bouguettaya, Munindar P. Singh, Michael N. Huhns, Quan Z. Sheng, Hai Dong, Qi Yu, Azadeh Ghari Neiat, Sajib Mistry, Boualem Benatallah, Brahim Medjahed, Mourad Ouzzani, Fabio Casati, Xumin Liu, Hongbing Wang, Dimitrios Georgakopoulos, Liang Chen, Surya Nepal, Zaki Malik, Abdelkarim Erradi, Yan Wang, M. Brian Blake, Schahram Dustdar, Frank Leymann, Michael P. Papazoglou: A service computing manifesto: The next 10 years. Commun. ACM 60(4): 64-72 (2017) [IF 4.06].
  • Surya Nepal, Sanat Kumar Bista, Cecile Paris: Behavior-based propagation of trust in social networks with restricted and anonymous participation. Computational Intelligence 31(4): 642-668 (2015) [IF 0.9].