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https://hdl.handle.net/10356/137944
Title: | Mining social media data | Authors: | Yak, Kenneth Yong Seng | Keywords: | Engineering::Computer science and engineering::Computing methodologies::Document and text processing | Issue Date: | 2020 | Publisher: | Nanyang Technological University | Project: | SCSE19-0331 | Abstract: | Businesses are slowly shifting to social networking channels to market their products such as Twitter rather than traditional marketing and advertising. Brands create content to disseminate information to consumers. They use various methods to attract a large number of audiences such as likes and comments to gain popularity. These insights can prove useful to smaller start-up companies which can help them to generate new marketing ideas as well as advertisements. This project aims to develop a web platform to generate a popularity distribution among different data retrieved from Twitter. This will allow the smaller organization to find out various approaches of larger companies of their high level of interaction and audiences, and the difference in their interactivity level compared to those smaller companies. | URI: | https://hdl.handle.net/10356/137944 | Schools: | School of Computer Science and Engineering | Research Centres: | Centre for Computational Intelligence | Fulltext Permission: | restricted | Fulltext Availability: | With Fulltext |
Appears in Collections: | SCSE Student Reports (FYP/IA/PA/PI) |
Files in This Item:
File | Description | Size | Format | |
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MINING SOCIAL MEDIA DATA.pdf Restricted Access | 1.08 MB | Adobe PDF | View/Open |
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