The Study of Recommending Friends to Organizations in Microblog Platform
Date Issued
2010
Date
2010
Author(s)
Lee, Chang-Ye
Abstract
Microblog becomes popular in Taiwan from 2009. There are tens of thousands of users to join plurk. They make friends, share information and gossip with one another in plurk. Plurk which can be regarded as an information highway can rapidly spread news. For example, Dell marks the wrong price to products in official homepage in June 2009 and plurk plays an important role in information dissemination.
For organizations in Taiwan, plurk is an outpost to achieve organizational purposes. In one way, plurk can detect and deal with emergency events quickly and unhurriedly. In another way, organizations can know more customers and friends, and obtain the first-hand real-time information by interaction with them.
This thesis analyzes properties in plurk at first including emotional topic, linguistic topic and real-time property. Then it builds a personalized friend recommendation system which selects suitable features for each organization and those features will form recommendation reasons to support making friends. Besides, this thesis also presents a concept of organization community. That can make the implementation feasible for each organization.
This thesis proposes a feature selection mechanism to select the customized features and uses Support Vector Machine (SVM) to train and predict data. Furthermore, this thesis makes experiments to discuss the influences of feature selection, robot services, and community in recommendation. Finally this thesis provides some issues for future works such as recommendation reasons and real-time recommendation.
Subjects
microblog
SVM
feature selection
plurk
recommend friend
Type
thesis
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