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Fine-Grained Privacy Setting Prediction Using a Privacy Attitude Questionnaire and Machine Learning
Abstract : This paper proposes to recommend privacy settings to users of social networks (SNs) depending on the topic of the post. Based on the answers to a specifically designed questionnaire, machine learning is utilized to inform a user privacy model. The model then provides, for each post, an individual recommendation to which groups of other SN users the post in question should be disclosed. We conducted a pre-study to find out which friend groups typically exist and which topics are discussed. We explain the concept of the machine learning approach, and demonstrate in a validation study that the generated privacy recommendations are precise and perceived as highly plausible by SN users.
Cited literature [10 references]
https://hal.inria.fr/hal-01679834
Contributor : Hal Ifip <>
Submitted on : Wednesday, January 10, 2018 - 11:32:19 AM
Last modification on : Thursday, June 4, 2020 - 6:24:02 PM
Long-term archiving on: : Saturday, May 5, 2018 - 6:41:55 AM
Contributor : Hal Ifip <>
Submitted on : Wednesday, January 10, 2018 - 11:32:19 AM
Last modification on : Thursday, June 4, 2020 - 6:24:02 PM
Long-term archiving on: : Saturday, May 5, 2018 - 6:41:55 AM
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421765_1_En_48_Chapter.pdf
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