Please use this identifier to cite or link to this item:
http://hdl.handle.net/20.500.12188/19996
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Gievska, Sonja | en_US |
dc.contributor.author | Kosinski, Michal | en_US |
dc.contributor.author | Stillwell, David | en_US |
dc.contributor.author | Markovikj, Dejan | en_US |
dc.date.accessioned | 2022-06-29T09:24:30Z | - |
dc.date.available | 2022-06-29T09:24:30Z | - |
dc.date.issued | 2013 | - |
dc.identifier.uri | http://hdl.handle.net/20.500.12188/19996 | - |
dc.description.abstract | Beyond being facilitators of human interactions, social networks have become an interesting target of research, providing rich information for studying and modeling user’s behavior. Identification of personality-related indicators encrypted in Facebook profiles and activities are of special concern in our current research efforts. This paper explores the feasibility of modeling user personality based on a proposed set of features extracted from the Facebook data. The encouraging results of our study, exploring the suitability and performance of several classification techniques, will also be presented. | en_US |
dc.title | Mining facebook data for predictive personality modeling | en_US |
dc.type | Proceeding article | en_US |
dc.relation.conference | International AAAI Conference on Web and Social Media | en_US |
item.fulltext | With Fulltext | - |
item.grantfulltext | open | - |
crisitem.author.dept | Faculty of Computer Science and Engineering | - |
Appears in Collections: | Faculty of Computer Science and Engineering: Conference papers |
Files in This Item:
File | Description | Size | Format | |
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14466-Article Text-17984-1-2-20201228.pdf | 390.81 kB | Adobe PDF | View/Open |
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