Type of Publication: | Journal article |
Publication status: | Published |
Author: | Nasim, Mehwish; Charbey, Raphael; Prieur, Christophe; Brandes, Ulrik |
Year of publication: | 2016 |
Published in: | IEEE Transactions on Computational Social Systems ; 3 (2016), 3. - pp. 113-119. - eISSN 2329-924X |
DOI (citable link): | https://dx.doi.org/10.1109/TCSS.2016.2618998 |
Summary: |
While privacy preserving mechanisms, such as hiding one's friends list, may be available to withhold personal information on online social networking sites, it is not obvious whether to which degree a user's social behavior renders such an attempt futile. In this paper, we study the impact of additional interaction information on the inference of links between nodes in partially covert networks. This investigation is based on the assumption that interaction might be a proxy for connectivity patterns in online social networks. For this purpose, we use data collected from 586 Facebook profiles consisting of friendship ties (conceptualized as the network) and comments on wall posts (serving as interaction information) by a total of 64 000 users. The link-inference problem is formulated as a binary classification problem using a comprehensive set of features and multiple supervised learning algorithms. Our results suggest that interactions reiterate the information contained in friendship ties sufficiently well to serve as a proxy when the majority of a network is unobserved.
|
Subject (DDC): | 004 Computer Science |
Bibliography of Konstanz: | Yes |
Files | Size | Format | View |
---|---|---|---|
There are no files associated with this item. |
NASIM, Mehwish, Raphael CHARBEY, Christophe PRIEUR, Ulrik BRANDES, 2016. Investigating Link Inference in Partially Observable Networks : Friendship Ties and Interaction. In: IEEE Transactions on Computational Social Systems. 3(3), pp. 113-119. eISSN 2329-924X. Available under: doi: 10.1109/TCSS.2016.2618998
@article{Nasim2016-09Inves-36638, title={Investigating Link Inference in Partially Observable Networks : Friendship Ties and Interaction}, year={2016}, doi={10.1109/TCSS.2016.2618998}, number={3}, volume={3}, journal={IEEE Transactions on Computational Social Systems}, pages={113--119}, author={Nasim, Mehwish and Charbey, Raphael and Prieur, Christophe and Brandes, Ulrik} }
<rdf:RDF xmlns:dcterms="http://purl.org/dc/terms/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:bibo="http://purl.org/ontology/bibo/" xmlns:dspace="http://digital-repositories.org/ontologies/dspace/0.1.0#" xmlns:foaf="http://xmlns.com/foaf/0.1/" xmlns:void="http://rdfs.org/ns/void#" xmlns:xsd="http://www.w3.org/2001/XMLSchema#" > <rdf:Description rdf:about="https://kops.uni-konstanz.de/rdf/resource/123456789/36638"> <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/> <dc:language>eng</dc:language> <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2017-01-12T15:53:40Z</dcterms:available> <dc:contributor>Brandes, Ulrik</dc:contributor> <dc:creator>Charbey, Raphael</dc:creator> <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2017-01-12T15:53:40Z</dc:date> <dc:creator>Nasim, Mehwish</dc:creator> <foaf:homepage rdf:resource="http://localhost:8080/jspui"/> <dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/rdf/resource/123456789/36"/> <dc:contributor>Charbey, Raphael</dc:contributor> <dcterms:title>Investigating Link Inference in Partially Observable Networks : Friendship Ties and Interaction</dcterms:title> <dc:creator>Brandes, Ulrik</dc:creator> <dc:contributor>Prieur, Christophe</dc:contributor> <dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/rdf/resource/123456789/36"/> <bibo:uri rdf:resource="https://kops.uni-konstanz.de/handle/123456789/36638"/> <dcterms:abstract xml:lang="eng">While privacy preserving mechanisms, such as hiding one's friends list, may be available to withhold personal information on online social networking sites, it is not obvious whether to which degree a user's social behavior renders such an attempt futile. In this paper, we study the impact of additional interaction information on the inference of links between nodes in partially covert networks. This investigation is based on the assumption that interaction might be a proxy for connectivity patterns in online social networks. For this purpose, we use data collected from 586 Facebook profiles consisting of friendship ties (conceptualized as the network) and comments on wall posts (serving as interaction information) by a total of 64 000 users. The link-inference problem is formulated as a binary classification problem using a comprehensive set of features and multiple supervised learning algorithms. Our results suggest that interactions reiterate the information contained in friendship ties sufficiently well to serve as a proxy when the majority of a network is unobserved.</dcterms:abstract> <dc:creator>Prieur, Christophe</dc:creator> <dc:contributor>Nasim, Mehwish</dc:contributor> <dcterms:issued>2016-09</dcterms:issued> </rdf:Description> </rdf:RDF>