Python based event management analytics system (part A)

A social network is a group of people (or organisations or other social entities) linked by social interactions such as friendship, co-working, or information sharing. Social Network Analysis (SNA) is the process of investigating social structures using networks and graph theory. SNA studies pattern...

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Main Author: Ng, Han Sen
Other Authors: Andy Khong W H
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2022
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Online Access:https://hdl.handle.net/10356/157865
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1578652023-07-07T19:05:51Z Python based event management analytics system (part A) Ng, Han Sen Andy Khong W H School of Electrical and Electronic Engineering AndyKhong@ntu.edu.sg Engineering::Electrical and electronic engineering A social network is a group of people (or organisations or other social entities) linked by social interactions such as friendship, co-working, or information sharing. Social Network Analysis (SNA) is the process of investigating social structures using networks and graph theory. SNA studies patterns of relationships among people, companies, states, and other social entities. It characterises network structures in terms of nodes (individual actors, people, or things within the network) and the ties, edges, or links (relationships or interactions) that connect them. The visual and statistical examination of human relationships is provided by social network analysis. In this paper, we explore the use of Python to perform Social Network Analysis in our use case; to understand the interactions and relationships of participants who have attended Nanyang Technological University (NTU) open-house events. Bachelor of Engineering (Electrical and Electronic Engineering) 2022-05-24T12:16:42Z 2022-05-24T12:16:42Z 2022 Final Year Project (FYP) Ng, H. S. (2022). Python based event management analytics system (part A). Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/157865 https://hdl.handle.net/10356/157865 en A3018-211 application/pdf Nanyang Technological University
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Electrical and electronic engineering
spellingShingle Engineering::Electrical and electronic engineering
Ng, Han Sen
Python based event management analytics system (part A)
description A social network is a group of people (or organisations or other social entities) linked by social interactions such as friendship, co-working, or information sharing. Social Network Analysis (SNA) is the process of investigating social structures using networks and graph theory. SNA studies patterns of relationships among people, companies, states, and other social entities. It characterises network structures in terms of nodes (individual actors, people, or things within the network) and the ties, edges, or links (relationships or interactions) that connect them. The visual and statistical examination of human relationships is provided by social network analysis. In this paper, we explore the use of Python to perform Social Network Analysis in our use case; to understand the interactions and relationships of participants who have attended Nanyang Technological University (NTU) open-house events.
author2 Andy Khong W H
author_facet Andy Khong W H
Ng, Han Sen
format Final Year Project
author Ng, Han Sen
author_sort Ng, Han Sen
title Python based event management analytics system (part A)
title_short Python based event management analytics system (part A)
title_full Python based event management analytics system (part A)
title_fullStr Python based event management analytics system (part A)
title_full_unstemmed Python based event management analytics system (part A)
title_sort python based event management analytics system (part a)
publisher Nanyang Technological University
publishDate 2022
url https://hdl.handle.net/10356/157865
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