Social listening analytics for marketing content creation

Social content is available everywhere on the Internet today. Performing text analytics provides meaning to the unstructured data gathered from the social content. It is opportune to tap into online content given how the social media is thriving worldwide currently, generating more data than before....

Full description

Saved in:
Bibliographic Details
Main Author: Leong, Yik Sheng
Other Authors: Chen Lihui
Format: Final Year Project
Language:English
Published: 2018
Subjects:
Online Access:http://hdl.handle.net/10356/75198
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Nanyang Technological University
Language: English
id sg-ntu-dr.10356-75198
record_format dspace
spelling sg-ntu-dr.10356-751982023-07-07T15:54:02Z Social listening analytics for marketing content creation Leong, Yik Sheng Chen Lihui School of Electrical and Electronic Engineering FWD Yao Yuhui DRNTU::Library and information science::Libraries::Information retrieval and analysis Social content is available everywhere on the Internet today. Performing text analytics provides meaning to the unstructured data gathered from the social content. It is opportune to tap into online content given how the social media is thriving worldwide currently, generating more data than before. To aid businesses in market research using automation, two main ideas were explored in this project. Specifically focusing on data regarding travel and insurance, topic modelling by Latent Dirichlet Allocation (LDA) and Sentiment Analysis were implemented on forum posts data and Twitter data respectively. The results derived from LDA picked out a few topics that were general features that travel insurance encompassed and could be extended to other areas of concern, while sentiments towards and against similar brands in the insurance industry were studied to provide a visualisation of how members of the public view these competing brands. These analytics provided insight to the collaborating company that would otherwise require more manpower to collate and analyse. More work could be done in terms of tailoring the models to the insurance industry. These tested methods could be adopted for similar use cases accordingly. Bachelor of Engineering 2018-05-30T02:47:36Z 2018-05-30T02:47:36Z 2018 Final Year Project (FYP) http://hdl.handle.net/10356/75198 en Nanyang Technological University 52 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::Library and information science::Libraries::Information retrieval and analysis
spellingShingle DRNTU::Library and information science::Libraries::Information retrieval and analysis
Leong, Yik Sheng
Social listening analytics for marketing content creation
description Social content is available everywhere on the Internet today. Performing text analytics provides meaning to the unstructured data gathered from the social content. It is opportune to tap into online content given how the social media is thriving worldwide currently, generating more data than before. To aid businesses in market research using automation, two main ideas were explored in this project. Specifically focusing on data regarding travel and insurance, topic modelling by Latent Dirichlet Allocation (LDA) and Sentiment Analysis were implemented on forum posts data and Twitter data respectively. The results derived from LDA picked out a few topics that were general features that travel insurance encompassed and could be extended to other areas of concern, while sentiments towards and against similar brands in the insurance industry were studied to provide a visualisation of how members of the public view these competing brands. These analytics provided insight to the collaborating company that would otherwise require more manpower to collate and analyse. More work could be done in terms of tailoring the models to the insurance industry. These tested methods could be adopted for similar use cases accordingly.
author2 Chen Lihui
author_facet Chen Lihui
Leong, Yik Sheng
format Final Year Project
author Leong, Yik Sheng
author_sort Leong, Yik Sheng
title Social listening analytics for marketing content creation
title_short Social listening analytics for marketing content creation
title_full Social listening analytics for marketing content creation
title_fullStr Social listening analytics for marketing content creation
title_full_unstemmed Social listening analytics for marketing content creation
title_sort social listening analytics for marketing content creation
publishDate 2018
url http://hdl.handle.net/10356/75198
_version_ 1772828247365517312