Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/69146
Title: Identifying minimal number of seed influencers in social networks
Authors: Goh, Jesse Jian Hui
Keywords: DRNTU::Engineering
Issue Date: 2016
Abstract: Social networks are prevalent. They contain large pools of users whom exist in communities. While a social network could seem harmless with the mere participation of human beings, there should not be an underestimate towards the influence a social network can exert. Social media today has had vast impact on our culture, ideologies and beliefs. Not only has it changed the way we think, it has also affected the way we communicate and socialized on the Web. The effect that social media has caused, can either aid the society or harm it by circulating negative or unhealthy ideas to any community. In other words, social media has the ability to infect (with negative ideas) or purify the communities (with positive benefits to aid growth). These effect spans from boosting business economy to changing views on politics to socialization to cyber bullying as well as to invasion of privacy; much less, anything can be done via utilizing the social media (network). Thus, if social networks could influence the communities and eventually the world to a better future, the benefits obtained could be out of this world. Hence, it is often useful to identify nodes that exert more influences over the other nodes. These nodes could be the keys to generate the large influence over multiple communities. This project aims to develop software tools for such purposes via a web-based application, designed for analytical users only since this information would be useful for government officials or business executives that wish to exert the some (positive) influence over the network. This application would be able to filter and pick the most influential node(s) based on centrality algorithms. Subsequently, a selected group of nodes could very well generate a large influence of more than a certain percentage, also known as Coverage Percentage (CP). The application user would have a CP he/she wants to achieve in mind. Via the use of the product application, the user would be able to select each node, one at a time, such that he/she could revise the CP after each subsequent node. The aim of the application is to filter possible subsequent nodes so that the final CP achieved would meet his/her aim of CP.
URI: http://hdl.handle.net/10356/69146
Rights: Nanyang Technological University
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Student Reports (FYP/IA/PA/PI)

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