Faculdade de Letras da Universidade do Porto - OCS, 15th INTERNATIONAL ISKO CONFERENCE

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Ojo Stephen Aderibigbe, Bernard Ijesunor Akhigbe, Babajide Samuel Afolabi, Emmanuel Rotimi Adagunodo

Last modified: 2018-01-31


In this age of information; knowledge creation, sharing and idea generation are critical to enhancing productivity and adaptation to global changes. The currency of the 21st century digital economy is one’s personal information. Adding to this importance is the fact that information has no transaction costs and does not decrease in value when the supply increases. Even contrary to the laws of economics, it may even increase in value with greater supply. This in our opinion suggests the need for better ways to share information such that when internalized - absorbed and understood by the human mind; it becomes knowledge (Liew, 2007). One barrier to knowledge sharing is the huge societal divide in terms of the myriads of culture and beliefs in the world. This divide spells the societal challenge of trust, which can hinder access to knowledge in a global scale (Hanson and Kararach, 2011). This is so since in the sharing of knowledge between people, especially on a global scale the expectation is high in terms of mutuality (Wu et al., 2007). Interestingly, mutuality attracts reciprocity. This makes trust an issue to consider since people are very likely going to show aversion when they interact in the global society. This cannot be ruled out in the current world, which has become even more interconnected, and both the receiving and sharing of knowledge continue to be from (so many) different sources (Ali et al., 2015). We believe the problems, which can arise as a result of the foregoing can be minified. This paper therefore, seeks to contribute more attributes as parameters that can strengthen existing trust models to allow people (and services) interacts online (Hendrikx et al., 2015).

The foregoing aim will be pursued by leveraging on the potentials of trust-based paradigm to propose a trust system of collaboration that will ensure a non-break in mutuality. This is because when “non-break” mutuality is achieved; trust as a societal challenge would be controlled and minified. This paper will take a cue from the theoretics of trust-aware collaborative modelling based on a Friend-to-Friend Network (F2FN) scenario. As a result, a trust-aware system that uses an F2FN collaborative scenario will be presented. This will be highlighted as an effective management platform to test trust with respect to a robust collaborative knowledge sharing paradigm. The system will use the trustworthiness of collaborators explicitly to be able to grant access. We believe that trust is mutable. So, how the trustworthiness of peers is upheld as a priority (Aderibigbe et al., 2016) will be demonstrated by how the system updates itself during and after collaborations. Aside the ability of the system to update itself, this update will be followed by trust computation, which result can be looked up and updated accordingly in preparation for fresh or continuous collaboration. Metrics like reputational accuracy, convergence and effectiveness will be used to assess the level of trust among collaborating and knowledge sharing peers. This will also be used to validate the specific tasks that are needed to ensure trust during knowledge sharing. We envisage the possibility of churn, which is normal in an F2FN situation. We also foresee a situation in a social media network context, when communication will be direct with peers, and most times without considering the level of trust they have towards one another. It will be imperative to therefore make trust data available to aid trust computation. The distributed hash table in synergy with the chord technique and the symmetric replication technique will therefore be introduced. Using an architectural approach, the trust-based system will be highlighted to show the function of peer update of trust after a collaborative session. Based on the foregoing architectural provision a prototype system will be presented to demonstrate the presence of a significant improvement in reputational accuracy and convergence when deployed to manage trust using an F2F scenario.

This paper will show the possibility of minifying the societal challenge of lack of social trust in a knowledge sharing context. The plausibility of the foregoing possibility is in the fact that the trust-aware model’s prototype - system dealt with trust issue(s). We submit to the fact that this can inspire a connotative inference for better Knowledge Organization System (KOS). This implies that where trust issue(s) is rife (e.g. in the social media and other related networks); trust can be minified. The overall corollary from the presentations so far will be the trust-aware system as a prototype. Its application will be used to unequivocally infer the imperatives that are needful in minifying trust issue(s) in KOS. It will therefore be concluded that trust as an obvious societal challenge can be minified using appropriate techniques, cognizance of an appropriate scenario and context(s) of KOS.


Aderibigbe, S O., Akhigbe, B, I., Afolabi, B.S., and Adagunodo, E.R. (2016). Towards a Sustained Collaborative Knowledge Sharing: The F2F Interactive Sharing Paradigm, Advances in Knowledge Organization, Vol. 15: pp. 420-428.

Ali, S.M., Saleem, U., and Sikandar, S.M. (2015). Knowledge Sharing Prominence and Role in the 21 Century Organizations. Researcher, 7(1),

Hanson, K. T., and Kararach, G. (2011). The challenges of knowledge harvesting and the promotion of sustainable development for the achievement of the MDGs in Africa.

Hendrikx, F., Bubendorfer, K., & Chard, R. (2015). Reputation systems: A survey and taxonomy. Journal of Parallel and Distributed Computing75, 184-197.

Liew, A. (2007). Understanding Data, Information, Knowledge and Their Inter-relation -ships. Journal of Knowledge Management Practice, Vol. 8 (2), 1-10.

Wu, W. L., Hsu, B. F., and Yeh, R. S. (2007). Fostering the determinants of knowledge transfer: A team-level analysis. Journal of Information Science, 33(3), 326−339.