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A Framework for profiling and friend prediction on Twitter
KTH, School of Information and Communication Technology (ICT).
KTH, School of Information and Communication Technology (ICT).
2013 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

The internet is being integrated in nearly every aspect of daily life of individuals. Social networks are made up of user profiles which are collection of user’s personal data and its relation with other users. Many relations between users are based on trust but trust and privacy are not captured and presented in profiles and personalized recommendations.This introduces a need for an intelligent social mining service which can analyze a person’s profile or related data on the basis of matching corresponding interests or likings.In this work, we have proposed for a generic architecture for social web mining where we can create a user model for users based on their tweets and mine their data to infer relationships among them and based on them we make suggestions. Our framework captures the trust between individuals based on their user models, while to preserve their privacy, trust is used to further filter out more valuable connections. We present (initial) experimental results with a 2009 twitter dataset.

Place, publisher, year, edition, pages
2013. , 75 p.
Series
Trita-ICT-EX, 2013:280
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:kth:diva-137686OAI: oai:DiVA.org:kth-137686DiVA: diva2:679626
Examiners
Available from: 2013-12-16 Created: 2013-12-16 Last updated: 2013-12-16Bibliographically approved

Open Access in DiVA

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