Items with full text/Total items : 49288/83828 (59%)
Visitors : 7158966
Online Users : 74
Please use this identifier to cite or link to this item:
|Title: ||Estimating trust value : a social network perspective|
|Other Titles: ||估算信任值 : 一個社會網絡的視角|
|Authors: ||狄愛林;Castillo, Arleen Nicole Diaz|
|Keywords: ||信任;社會網絡;集群;自組織映射圖網路;網路建議系統;社會媒體;Trust;Social Network;Clustering;SOM;ORS;Social media|
|Issue Date: ||2013-04-13 11:28:35 (UTC+8)|
Information overload is an increasing problem, and as information available
continues to grow in volume, current filtering techniques are proving inefficient.
Social network users and people in general, tend to prioritize recommendations
coming from people they are acquainted to. The purpose of this study was to
investigate if it was possible to measure trust within individuals in a social network,
as well as find out if data clustering methods could help to achieve said goal. Another
aim was to develop a trust model that would estimate a trust value for content creators
on an online rating system with social network capabilities.
This research introduces the concept of social distance, which is drawn from
clustering methods applied to the social network user base; and incorporates said
distance in the estimation of trust, as well as user generated ratings. The trust value
estimated will serve as a metric for filtering and sorting content of any kind based on
the trustworthiness of the creator.
The results of the study revealed that it is possible to provide an estimate
measure of trust within individuals in a social network and that clustering methods
were of significant help into said evaluation as well as the integration of other
variables affecting the building of trust. It was found that the model proposed by this
study was able to integrate various variables and provide a more complete and
integrated, multidimensional value to an estimated trust. Results also showed, that
higher rating scores combined with shorter social distances provide satisfactory trust
values, while the opposite happened for subjects presenting lower rating scores in
combination with longer distances.
The principal conclusion was that our model provides a multidimensional
estimated value for trust on content from the Internet, that integrates some of the
variables necessary for the building of trust in online setting, as are: social distance,
weight of relationship, time, and ratings from an online rating system; as well trust
levels between individuals within a social network. This study contributes to the
current literature on trust estimation and social networks role in such endeavors. This
will provide also an alternative for current information overload issues as well.
|Appears in Collections:||[企業管理學系暨研究所] 學位論文|
Files in This Item:
All items in 機構典藏 are protected by copyright, with all rights reserved.