How easy is it to clean up a rumor

Rumor spreading in social networks could be considered as “infection of the mind” of people. It could be detrimental to the social structure and it would be useful if we could better understand how to control this spread. In this report we attempt to analyse what are some of the factors that can hel...

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Main Author: George, Kavya
Other Authors: Xiao Gaoxi
Format: Final Year Project
Language:English
Published: 2014
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Online Access:http://hdl.handle.net/10356/61294
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-612942023-07-07T16:16:07Z How easy is it to clean up a rumor George, Kavya Xiao Gaoxi School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering Rumor spreading in social networks could be considered as “infection of the mind” of people. It could be detrimental to the social structure and it would be useful if we could better understand how to control this spread. In this report we attempt to analyse what are some of the factors that can help control and clean up this rumor spread. Basic versions of Random and Scale Free network models have been used to depict the social networks in this project. SIR model has been used to spread the rumor and cleaning agent. We begin by examining the factors that affect the rumor spreading process. We observe that factors such as spread rate and network density have a strong impact on the spreading rate. These effects can be observed during cleaning as well. We experimented with spreading cleaning from multiple nodes which doesn’t increase the fraction of cleaned nodes but the process occurs at a slightly faster rate. Then, we experimented with introducing the cleaning agent at different intervals of the rumor spreading process. We find that the earlier we introduce the cleaning agent; we are left with a lesser number of infected nodes in the end. An element of trust is also incorporated into the network model as a special case and we find that the mistrust actually helps increase the number of infected nodes. Finally, we try an alternative spreading mechanism that is much less aggressive and observe how different factors affect this mechanism. We find that factors such as high spread rate and low recovery are necessary for this alternative mechanism to spread effectively. Bachelor of Engineering 2014-06-09T02:52:17Z 2014-06-09T02:52:17Z 2014 2014 Final Year Project (FYP) http://hdl.handle.net/10356/61294 en Nanyang Technological University 55 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering::Electrical and electronic engineering
spellingShingle DRNTU::Engineering::Electrical and electronic engineering
George, Kavya
How easy is it to clean up a rumor
description Rumor spreading in social networks could be considered as “infection of the mind” of people. It could be detrimental to the social structure and it would be useful if we could better understand how to control this spread. In this report we attempt to analyse what are some of the factors that can help control and clean up this rumor spread. Basic versions of Random and Scale Free network models have been used to depict the social networks in this project. SIR model has been used to spread the rumor and cleaning agent. We begin by examining the factors that affect the rumor spreading process. We observe that factors such as spread rate and network density have a strong impact on the spreading rate. These effects can be observed during cleaning as well. We experimented with spreading cleaning from multiple nodes which doesn’t increase the fraction of cleaned nodes but the process occurs at a slightly faster rate. Then, we experimented with introducing the cleaning agent at different intervals of the rumor spreading process. We find that the earlier we introduce the cleaning agent; we are left with a lesser number of infected nodes in the end. An element of trust is also incorporated into the network model as a special case and we find that the mistrust actually helps increase the number of infected nodes. Finally, we try an alternative spreading mechanism that is much less aggressive and observe how different factors affect this mechanism. We find that factors such as high spread rate and low recovery are necessary for this alternative mechanism to spread effectively.
author2 Xiao Gaoxi
author_facet Xiao Gaoxi
George, Kavya
format Final Year Project
author George, Kavya
author_sort George, Kavya
title How easy is it to clean up a rumor
title_short How easy is it to clean up a rumor
title_full How easy is it to clean up a rumor
title_fullStr How easy is it to clean up a rumor
title_full_unstemmed How easy is it to clean up a rumor
title_sort how easy is it to clean up a rumor
publishDate 2014
url http://hdl.handle.net/10356/61294
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