Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/69301
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dc.contributor.authorRabiah Raihan
dc.date.accessioned2016-12-12T08:07:59Z
dc.date.available2016-12-12T08:07:59Z
dc.date.issued2016
dc.identifier.urihttp://hdl.handle.net/10356/69301
dc.description.abstractLurkers in social networks are silent members in a social network who play passive roles and contribute very little in the network. The so-called lurkers make up close to 90% of the online social network users. This huge number of inactive users created an awareness to research in which is worth the exploration. Many lurking-related researches had been done under the category of social science, cognitive psychology and computer-human interaction. There had only been one study of this lurking phenomenon that is categorised as data mining and information retrieval. This project investigates the study of lurking phenomenon based on data mining in turn ranking the lurkers with different ranking methods such as Page Rank and Alpha-Centrality. This report records the investigation and derivation of all the definitions used to formulate the topology driven concept into the LurkerRank methods through programming and testing algorithm in MATLAB.en_US
dc.format.extent56 p.en_US
dc.language.isoenen_US
dc.rightsNanyang Technological University
dc.subjectDRNTU::Engineeringen_US
dc.titleLurkers in social networksen_US
dc.typeFinal Year Project (FYP)en_US
dc.contributor.supervisorTay Wee Pengen_US
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US
dc.description.degreeBachelor of Engineeringen_US
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Appears in Collections:EEE Student Reports (FYP/IA/PA/PI)
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