NEW METHODOLOGIES FOR IDENTIFYING CUSTOMER NEEDS FROM USER-GENERATED CONTENTS .pptx

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1. NEW METHODOLOGIES FOR IDENTIFYING CUSTOMER NEEDS FROM USER-GENERATED CONTENTS

2. Introduction COVID-19 E-Commerce Traditional Methods User-Generated Content (UGC) Marketing Issues NLP in Marketing

3. Research Gaps Review-based Recommendation Approaches Biased Reviews Imbalanced Classification Problem Context-dependent Customer Demands Best Class Weight for Minority Groups

4. Goal and Objectives Creating processes that allow businesses to keep an eye on the constantly changing User Generated Contents To improve analysts capacity to deduce what customers require from educational and non-repetitive user-generated content. To introduce and create new methods for encoding the qualities of reviews to improve their usefulness by including more details.

5. Goal and Objectives To create models for different review qualities so that knowledge of reviews can be enhanced according to various reviews' features. To provide an appropriate evaluation measure or procedure for minimizing potential biases so that accurate and fraudulent review data may be distinguished to lessen social injustice or inequality issues.

6. Methodology Data Gathering Reviews data for chosen companies will be crawled, and event-based data will be gathered via events calendars . Data Pre-Processing Data Cleaning T okenization Stop word removal Stemming POS tagging

7. Preprocessing- Example

8. Methodology Features Engineering Applying words Embedding technique Word2Vec fastText Identify Educational Content We would categorize sentences into small groups as informative or non-informative, train a CNN, and use it to remove non-informative sentences from the rest of the corpus.

9. Methodology Datasets Splitting Training Set (80%) Testing Set (20%) Sample Contents with Variety Assessment and Validation Following tools will used to validate the models Accuracy Precesion Recall F1- Score

10. Conclusion