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http://hdl.handle.net/11718/26246
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DC Field | Value | Language |
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dc.contributor.advisor | Kapoor, Anuj | - |
dc.contributor.author | Verma, Shyamal | - |
dc.contributor.author | Jakhar, Ankit Kumar | - |
dc.date.accessioned | 2023-04-02T06:39:01Z | - |
dc.date.available | 2023-04-02T06:39:01Z | - |
dc.date.issued | 2021-09-07 | - |
dc.identifier.uri | http://hdl.handle.net/11718/26246 | - |
dc.description.abstract | The rise of the internet based economy and social media usage has helped a brand or content producer to get direct feedback from the user in the form of comments, likes or dislikes about the functionality or the experience provided by the same product or service. The data generated through these platforms has high Volume & variety, but with the help of machine learning algorithms which can generate non-linear relationships, these qualitative insights can be used to gain useful quantitative insights. We carry out sensitivity analysis on the comments or reviews posted by customers of PlayStation4 and analyse the change in behaviour and attitude of purchaser over the course of lifecycle of PS4. We identified that during the growth stage the consumers are more centric towards product features and specifications and during the maturity stage they become more experienced centric. We also find that repeat upgrades and intervention in terms of new game launces can prolong the lifecycle of PS4 and in turn result an increase in total sales. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Indian Institute of Management Ahmedabad | en_US |
dc.subject | Internet based economy | en_US |
dc.subject | Social media usage | en_US |
dc.subject | Social media | en_US |
dc.subject | AI/ML methods | en_US |
dc.title | Use of AI/ML methods on qualitative data to derive quantitative insights | en_US |
dc.type | Student Project | en_US |
Appears in Collections: | Student Projects |
Files in This Item:
File | Description | Size | Format | |
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Use_of_AIML_methods_on_qualitative_data_to_derive_quantitative_insights.pdf Restricted Access | 1.26 MB | Adobe PDF | View/Open Request a copy |
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