ABSTRACT
Online social networks have changed the way people communicate, create content and share it via online social actions. In order for users to engage in a social network application, they need mechanisms that will help them to find other users that they can trust in some context and also qualitative and useful content. Reputation systems offer such mechanisms and are thus essential in Social Networks (SNs). Due to their open and social nature and to their different objectives, reputation systems for SN-based applications comprise of various different mechanisms which fulfill the different objectives in the specific application context. There is thus the need for a systematic study of the specific aspects of these systems, which can provide insights for the design of reputation systems in specific application contexts. In our paper we present a taxonomy of reputation systems for various SN applications based on their specific aspects. We then use this taxonomy to design a reputation system for microblogging systems and present our implementation for a reputation system for Twitter which estimates a specific notion of reputation; the influence of users and of specific subjects of discussion.
- Marti, S., and Garcia-Molina, H. 2006. Taxonomy of trust: categorizing P2P reputation systems. Comput. Netw. 50, 4 (March 2006), 472--484. Google ScholarDigital Library
- Jøsang, A., Ismail, R., and Boyd, C. 2007. A survey of trust and reputation systems for online service provision. Decis. Support Syst. 43, 2 (March 2007), 618--644. Google ScholarDigital Library
- Khalid, O., Khan, S. U., Madani, S. A., Hayat, K., Khan, M. I., Min-Allah, N., Kolodziej, J., Wang, L., Zeadally, S. Chen, D. 2013. Comparative Study of Trust and Reputation Systems for Wireless Sensor Networks. Secur. Commun. Netw. 6, 6, 669--688.Google ScholarCross Ref
- YouTube, www.youtube.com {last accessed on 30/6/2016}Google Scholar
- Flickr, www.flickr.com {last accessed on 30/6/2016}Google Scholar
- Techcrunch, www.techcrunch.com {last accessed on 30/6/2016}Google Scholar
- Mashable, www.mashable.com {last accessed on 30/6/2016}Google Scholar
- Twitter, www.twitter.com {last accessed on 30/6/2016}Google Scholar
- Yelp, www.yelp.com {last accessed on 30/6/2016}Google Scholar
- Epinions, www.epinions.com {last accessed on 30/6/2016}Google Scholar
- Facebook, www.facebook.com {last accessed on 30/6/2016}Google Scholar
- Ahmed, S. and Ezeife, C. I. Discovering Influential Nodes from Trust Network. In Proceedings of the 28th Annual ACM Symposium on Applied Computing (Coimbra, Portugal, March 18-22, 2013). SAC '13. ACM, New York, NY, USA, 121--128. Google ScholarDigital Library
- Agarwal, N, Liu, H., Tang, L. and Yu, P. S. Identifying the Influential Bloggers in a Community. In Proceedings of the International Conference on Web Search and Web Data Mining (2008). (Palo Alto, California, USA, Feb. 11-12, 2008). WSDM '08. ACM, New York, NY, 207--218. Google ScholarDigital Library
- Reddit, www.reddit.com {last accessed on 30/6/2016}Google Scholar
- Dellarocas, C. 2010. Online Reputation Systems: How to Design One That Does What You Need. MIT Sloan Management Review, 51, 3 (Issue of Summer 2010), 33--38.Google Scholar
- Farmer, R. and Glass, B. 2010. Building Web Reputation Systems (1st ed.). Yahoo! Press, USA. Google ScholarDigital Library
- Nickerson, R., Muntermann, J., Varshney, U, and Isaac, H. Taxonomy Development in Information Systems: Developing a Taxonomy of Mobile Applications. In Proceedings of the European Conference on Information Systems (2009). ECIS 2009 Proceedings, Paper 388.Google Scholar
- Hendrikx, F., Bubendorfer, K., and Chard, R. 2015. Reputation Systems: A survey and taxonomy. J. Parallel Distrib. Comput. 75, C (Jan. 2015) 184--197. Google ScholarDigital Library
- Digg, www.digg.com {last accessed on 30/6/2016}Google Scholar
- Delicious, www.delicious.com {last accessed on 30/6/2016}Google Scholar
- Han, Y., Kim, L., and Cha, J. Evaluation of User Reputation on YouTube. In Proceedings of the 3d International Conference on Online Communities and Social Computing (Jul. 19-24, 2009). OCSC '09. LNCS, 346--353. Google ScholarDigital Library
- TrackMaven retweet report, http://trackmaven.com/resources/retweet-report/ {last accessed on 30/6/2016}Google Scholar
- Wikipedia, www.wikipedia.com {last accessed on 30/6/2016}Google Scholar
- Klout, http://klout.com/ {last accessed on 30/6/2016}Google Scholar
- Amazon, www.amazon.com {last accessed on 30/6/2016}Google Scholar
- LinkedIn, www.linkedin.com {last accessed on 30/6/2016}Google Scholar
- Twitter widgets, https://dev.twitter.com/web/overview {last accessed on 30/6/2016}Google Scholar
- https://www.javascript.com/ {last accessed on 30/6/2016}Google Scholar
- https://jquery.com/ {last accessed on 30/6/2016}Google Scholar
- http://www.css3.info/modules/ {last accessed on 30/6/2016}Google Scholar
- https://www.w3.org/TR/html5/ {last accessed on 30/6/2016}Google Scholar
Recommendations
Designing social translucence over social networks
CHI '12: Proceedings of the SIGCHI Conference on Human Factors in Computing SystemsSocial translucence is a landmark theory in social computing. Modeled on physical life, it guides designers toward elegant social technologies. However, we argue that it breaks down over modern social network sites because social networks resist its ...
Leveraging Social Networks to Combat Collusion in Reputation Systems for Peer-to-Peer Networks
In peer-to-peer networks (P2Ps), many autonomous peers without preexisting trust relationships share resources with each other. Due to their open environment, the P2Ps usually employ reputation systems to provide guidance in selecting trustworthy ...
Trends in Social Media Usage: An Investigation of its Growth in the Arab World
In the present era of Web 2.0 and Web 3.0, Social Networking Sites have given us means of providing real-time services. Recent years have brought a massive growth in the social networking phenomenon. The use of social media in the Arab World has been ...
Comments