Mining social media data
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 co...
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| Format: | Final Year Project (FYP) |
| Language: | English |
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Nanyang Technological University
2020
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| Online Access: | https://hdl.handle.net/10356/137944 |
| _version_ | 1826123761016897536 |
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| author | Yak, Kenneth Yong Seng |
| author2 | Ke Yiping, Kelly |
| author_facet | Ke Yiping, Kelly Yak, Kenneth Yong Seng |
| author_sort | Yak, Kenneth Yong Seng |
| collection | NTU |
| description | 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. |
| first_indexed | 2024-10-01T06:09:37Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/137944 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T06:09:37Z |
| publishDate | 2020 |
| publisher | Nanyang Technological University |
| record_format | dspace |
| spelling | ntu-10356/1379442020-04-20T05:28:54Z Mining social media data Yak, Kenneth Yong Seng Ke Yiping, Kelly School of Computer Science and Engineering Centre for Computational Intelligence ypke@ntu.edu.sg Engineering::Computer science and engineering::Computing methodologies::Document and text processing 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. Bachelor of Engineering (Computer Science) 2020-04-20T05:28:53Z 2020-04-20T05:28:53Z 2020 Final Year Project (FYP) https://hdl.handle.net/10356/137944 en SCSE19-0331 application/pdf Nanyang Technological University |
| spellingShingle | Engineering::Computer science and engineering::Computing methodologies::Document and text processing Yak, Kenneth Yong Seng Mining social media data |
| title | Mining social media data |
| title_full | Mining social media data |
| title_fullStr | Mining social media data |
| title_full_unstemmed | Mining social media data |
| title_short | Mining social media data |
| title_sort | mining social media data |
| topic | Engineering::Computer science and engineering::Computing methodologies::Document and text processing |
| url | https://hdl.handle.net/10356/137944 |
| work_keys_str_mv | AT yakkennethyongseng miningsocialmediadata |