Social media is an important platform for brands to engage with their customers and collect feedback. Customer reviews provide valuable information to understand brand perception and customer satisfaction. In this project, we will determine users' feelings about the brand or product by analyzing user comments on Instagram, Facebook and Twitter. Sentiment analysis will help us distinguish positive, negative and neutral comments and develop strategies to increase customer satisfaction.
Dataset Description
The datasets used in this project include user comments and interactions on Instagram, Facebook and Twitter platforms. Each dataset includes metrics such as likes, comments, shares, and reach per post. Here are the details of the datasets:
Instagram Dataset
PostID: Unique post ID
PostDate: Post date
PostTime: Post time
Likes: Number of likes
Comments: Number of comments
Shares: Number of shares
Reach: Number of reaches
PostType: Post type (Video, Picture)
CommentText: User comments
Facebook Dataset
PostID: Unique post ID
PostDate: Post date
PostTime: Post time
Likes: Number of likes
Comments: Number of comments
Shares: Number of shares
Reach: Number of reaches
PostType: Post type (Video, Picture)
CommentText: User comments
Twitter Dataset
PostID: Unique post ID
PostDate: Post date
PostTime: Post time
Likes: Number of likes
Comments: Number of comments
Shares: Number of shares
Reach: Number of reaches
PostType: Post type (Video, Picture, Text)
CommentText: User comments
Project Steps
Step 1: Data Loading and First Look
First, we loaded the datasets and got an overview. We examined the structure of the data and identified missing or incorrect data. In this step, we got information about the overall status of the data.
Step 2: Cleaning Missing and Erroneous Data
We cleaned the missing and erroneous data in the data set. We filled in missing values and corrected incorrect data. This process is important to increase the accuracy of the analyses.
Step 3: Preparing Comments for Sentiment Analysis
To perform sentiment analysis, we cleaned the comments and made them ready for analysis. Cleaning comments involves removing unnecessary characters and symbols within the text. This step ensures that the analyzes provide more accurate results.
Step 4: Applying Sentiment Analysis Model
We identified positive, negative and neutral comments by performing sentiment analysis on the comments. In this step, we used a pre-trained sentiment analysis model. The model gave the results by determining the emotional state of each comment.
Step 5: Visualizing the Results
We presented the findings by visualizing the sentiment analysis results. This step is important to support the decision-making process. Visualizations helped us present the findings in a more understandable and impressive way.
Conclusion
In this project, we determined users' feelings about the brand or product by analyzing user comments on Instagram, Facebook and Twitter. Sentiment analysis helped us distinguish positive, negative and neutral reviews and develop strategies to increase customer satisfaction. By understanding customer feedback on social media, you can make your marketing strategies more effective and increase customer satisfaction.
Evaluation of Results
Based on sentiment analysis results, you can develop the following strategies to increase customer satisfaction on each platform:
Positive Reviews: Positive feedback can be used to increase brand loyalty. By thanking these customers and encouraging them to share their experiences, you can strengthen the positive perception of the brand.
Negative Comments: Negative feedback is critical to identify areas for improvement. By taking these comments into consideration, you can improve your products or services and reduce customer dissatisfaction.
Neutral Reviews: Neutral feedback may not point to a specific problem or praise, but is valuable for understanding the overall user experience. By analyzing these comments, you can develop strategies that will increase the overall satisfaction level.
Sentiment analysis is a valuable tool to make your social media marketing strategies more effective. This analysis allows you to understand customer feedback and develop strategies to increase customer satisfaction. By making data-based decisions, you can develop more effective and targeted marketing strategies on social media platforms.
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