Mining Indirect Antagonistic Communities from Social Interactions
Antagonistic communities refer to groups of people with opposite tastes, opinions, and factions within a community. Given a set of interactions among people in a community, we develop a novel pattern mining approach to mine a set of antagonistic communities. In particular, based on a set of user-spe...
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sg-smu-ink.sis_research-25582018-06-13T04:08:19Z Mining Indirect Antagonistic Communities from Social Interactions ZHANG, Kuan LO, David LIM, Ee Peng Prasetyo, Philips Kokoh Antagonistic communities refer to groups of people with opposite tastes, opinions, and factions within a community. Given a set of interactions among people in a community, we develop a novel pattern mining approach to mine a set of antagonistic communities. In particular, based on a set of user-specified thresholds, we extract a set of pairs of communities that behave in opposite ways with one another. We focus on extracting a compact lossless representation based on the concept of closed patterns to prevent exploding the number of mined antagonistic communities. We also present a variation of the algorithm using a divide and conquer strategy to handle large datasets when main memory is inadequate. The scalability of our approach is tested on synthetic datasets of various sizes mined using various parameters. Case studies on Amazon, Epinions, and Slashdot datasets further show the efficiency and the utility of our approach in extracting antagonistic communities from social interactions. 2013-01-01T08:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/1559 info:doi/10.1007/s10115-012-0519-4 https://ink.library.smu.edu.sg/context/sis_research/article/2558/viewcontent/Mining_Indirect_Antagonistic_Communities_from_Soci.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University antagonistic group frequent pattern mining closed pattern social network mining Software Engineering |
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antagonistic group frequent pattern mining closed pattern social network mining Software Engineering ZHANG, Kuan LO, David LIM, Ee Peng Prasetyo, Philips Kokoh Mining Indirect Antagonistic Communities from Social Interactions |
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Antagonistic communities refer to groups of people with opposite tastes, opinions, and factions within a community. Given a set of interactions among people in a community, we develop a novel pattern mining approach to mine a set of antagonistic communities. In particular, based on a set of user-specified thresholds, we extract a set of pairs of communities that behave in opposite ways with one another. We focus on extracting a compact lossless representation based on the concept of closed patterns to prevent exploding the number of mined antagonistic communities. We also present a variation of the algorithm using a divide and conquer strategy to handle large datasets when main memory is inadequate. The scalability of our approach is tested on synthetic datasets of various sizes mined using various parameters. Case studies on Amazon, Epinions, and Slashdot datasets further show the efficiency and the utility of our approach in extracting antagonistic communities from social interactions. |
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text |
author |
ZHANG, Kuan LO, David LIM, Ee Peng Prasetyo, Philips Kokoh |
author_facet |
ZHANG, Kuan LO, David LIM, Ee Peng Prasetyo, Philips Kokoh |
author_sort |
ZHANG, Kuan |
title |
Mining Indirect Antagonistic Communities from Social Interactions |
title_short |
Mining Indirect Antagonistic Communities from Social Interactions |
title_full |
Mining Indirect Antagonistic Communities from Social Interactions |
title_fullStr |
Mining Indirect Antagonistic Communities from Social Interactions |
title_full_unstemmed |
Mining Indirect Antagonistic Communities from Social Interactions |
title_sort |
mining indirect antagonistic communities from social interactions |
publisher |
Institutional Knowledge at Singapore Management University |
publishDate |
2013 |
url |
https://ink.library.smu.edu.sg/sis_research/1559 https://ink.library.smu.edu.sg/context/sis_research/article/2558/viewcontent/Mining_Indirect_Antagonistic_Communities_from_Soci.pdf |
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