Clustering of Micro-Messages Using Similarity Upper Approximation
01 Jan 2017-International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems (World Scientific Pub Co Pte Lt)-Vol. 25, Iss: 01, pp 53-79
TL;DR: A large number of people believe that social media should be used as a medium of communication for all forms of communication, and social media companies should be considered as a channel for doing so.
Abstract: Microblogging platforms like Twitter, Tumblr and Plurk have radically changed our lives. The presence of millions of people has made these platforms a preferred channel for communication. A large a...
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TL;DR: The current study proposes to use upper approximation concept of rough sets for developing a solution for privacy preserving social network graph publishing that is capable of preserving the privacy of graph structure while simultaneously maintaining the utility or value that can be generated from the graph structure.
Abstract: With the advent of the online social network and advancement of technology, people get connected and interact on social network. To better understand the behavior of users on social network, we need to mine the interactions of users and their demographic data. Companies with less or no expertise in mining would need to share this data with the companies of expertise for mining purposes. The major challenge in sharing the social network data is maintaining the individual privacy on social network while retaining the implicit knowledge embedded in the social network. Thus, there is a need of anonymizing the social network data before sharing it to the third-party. The current study proposes to use upper approximation concept of rough sets for developing a solution for privacy preserving social network graph publishing. The proposed algorithm is capable of preserving the privacy of graph structure while simultaneously maintaining the utility or value that can be generated from the graph structure. The proposed algorithm is validated by showing its effectiveness on several graph mining tasks like clustering, classification, and PageRank computation. The set of experiments were conducted on four standard datasets, and the results of the study suggest that the proposed algorithm would maintain the both the privacy of individuals and the accuracy of the graph mining tasks.
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Cites methods from "Clustering of Micro-Messages Using ..."
..., 2015) and have been used for clustering of micro-messages in microblogging platforms like Twitter (Gupta et al., 2017)....
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...Rough set based approaches have also been used in recommendation systems of websites (Mishra et al., 2015) and have been used for clustering of micro-messages in microblogging platforms like Twitter (Gupta et al., 2017)....
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...Another avenue for further research includes the application of the proposed algorithm on very large datasets like Twitter data, Facebook data, and so on....
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778 citations
05 Jul 2011
TL;DR: This paper explores approaches for analyzing the stream of Twitter messages to distinguish between messages about real-world events and non-event messages, and relies on a rich family of aggregatestatistics of topically similar message clusters.
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761 citations