Privacy Management in Agent-Based Social Networks

Authors: Nadin Kokciyan

AAAI 2016 | Conference PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Experimental We evaluate the scalability of our approach on generated as well as Facebook data. In a real-network of 4039 users with 88234 relations, it takes approximately 0.4 seconds to detect privacy violations on an ordinary computer. Our preliminary results are encouraging and show that our approach can scale to real-world networks.
Researcher Affiliation Academia Nadin K okciyan Department of Computer Engineering Bogazici University, 34342 Bebek, Istanbul, Turkey nadin.kokciyan@boun.edu.tr
Pseudocode No The paper does not contain any structured pseudocode or algorithm blocks.
Open Source Code No The paper states 'We build an open-source software tool PRIGUARDTOOL that implements the approach using ontologies' and 'A demonstration is available at http://mas.cmpe.boun.edu.tr/ nadin/priguard'. While it calls the tool 'open-source', it does not explicitly state that the source code is being released or available, and the provided URL is for a 'demonstration', not a direct link to a code repository.
Open Datasets No The paper mentions evaluating on 'generated as well as Facebook data' but does not provide concrete access information (e.g., URL, DOI, specific citation with authors/year) for these datasets, nor does it specify if the 'generated' data is publicly accessible.
Dataset Splits No The paper does not provide specific details regarding training, validation, or test dataset splits (e.g., percentages, sample counts, or references to predefined splits).
Hardware Specification No The paper vaguely states that experiments were run 'on an ordinary computer' but provides no specific hardware details such as GPU/CPU models, memory, or specific computer specifications.
Software Dependencies No The paper mentions technologies like 'description logic' and 'ontologies' and names its tool 'PRIGUARDTOOL', but it does not provide specific version numbers for any software components, libraries, or frameworks used.
Experiment Setup No The paper does not provide specific details about the experimental setup, such as hyperparameter values, training configurations, or other system-level settings.