An adaptive neuro-fuzzy inference system for a location based social network

dc.contributorGraduate Program in Management Information Systems.
dc.contributor.advisorTanrıkulu, Zuhal.
dc.contributor.authorAyyılmaz, Aycan.
dc.date.accessioned2023-03-16T12:51:29Z
dc.date.available2023-03-16T12:51:29Z
dc.date.issued2019.
dc.description.abstractLocation Based Social Networks (LSBNs) has started with broadcasting the location via text messages long before the mobile applications and mobile data. Due to the technological developments, a notable number of technologies we use today are location-aware, and they are available to more people. When one of the most popular LSBN, Foursquare, has brought together both motivation of gameplay and social networks, and it introduced a new business model to the market. They have used points and badges to motivate users for “checking in” to locations. After that point, LSBNs started to be a useful tool that effected purchase decision and became vital for information research, evaluation of alternatives and post-purchase evaluation. Typically, the score of the venues is a significant decision-making parameter for most of the users for a purchase decision. Due to the complex and undisclosed score calculation method of Foursquare, it has been a wonder to users and venue owners. Purpose of the research is to build a model that can predict venue scores based on variables such as check-in counts, review, tip and photo counts of venues.
dc.format.extent30 cm.
dc.format.pagesx, 61 leaves ;
dc.identifier.otherMIS 2019 A88
dc.identifier.urihttps://digitalarchive.library.bogazici.edu.tr/handle/123456789/18076
dc.publisherThesis (M.A.) - Bogazici University. Institute for Graduate Studies in the Social Sciences, 2019.
dc.subject.lcshSocial media.
dc.subject.lcshLocation-based services -- Social aspects.
dc.titleAn adaptive neuro-fuzzy inference system for a location based social network

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