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Social media user recommendation
Sruteesh Dinesh Kumar,
Published in IOS Press
2016
Volume: 284
   
Pages: 197 - 202
Abstract
This work aims at creating a user recommender system that recommends relevant people to follow for twitter users. We propose to use a novel topic modeling method Biterm Topic Model (BTM) to profile users into vectors of bag of words. We then propose an algorithm that uses both social network relationship information and the user-generated content modeled through BTM to recommend twitter followees. A preliminary evaluation is carried out on the implementation of this technique that shows BTM performs well in making valid recommendations to twitter users. We also found that considering both user generated content and social relationships for recommending followees helped improve the results. © 2016 The authors and IOS Press.
About the journal
JournalFrontiers in Artificial Intelligence and Applications
PublisherIOS Press
ISSN09226389
Open AccessNo
Concepts (11)
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    Information retrieval
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    Recommender systems
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    Social media
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    SOCIAL RELATIONS
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    SOCIAL RELATIONSHIPS
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    TOPIC MODEL
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    Topic modeling
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    Tweets
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    USER RECOMMENDATIONS
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    USER-GENERATED CONTENT
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    Social networking (online)