Food Delivery Sentiment Analysis

Key Finding

Positive sentiment towards Swiggy over Zomato was observed in our analysis of 50,000 tweets from official handles.

Objectives

1. Factors for App Selection: Identify key factors influencing food delivery app selection.
2. Sentiment Analysis: Analyze sentiments in tweets toward Swiggy and Zomato.
3. Recommendations: Provide insights and recommendations.

Data

We collected 50,000 tweets from official Swiggy and Zomato handles.

Analysis Steps

1. Word Clouds: Identified critical factors such as "Restaurant," "Refund," "Money," and "Waiting."
2. Bar Charts: Quantified and verified word repetition counts, confirming identified factors' prominence.
3. Co-Occurrence Graphs: Connected tokens to reveal closely related issues and customer sentiments.
4. Sentiment Analysis: Used valence shifters and Bing lexicon to identify key positive and negative contributors.

Recommendations

1. App Environment: Enhance the overall user experience.
2. Third-Party Issues:Address concerns related to third-party services.

Road Ahead

1. Data Expansion: Include a larger dataset for comprehensive sentiment analysis.
2. Demographic Study: Consider geographical locations and time zones for regional sentiment variations.