Social media platforms are powerful tools for brands and individuals to reach large audiences. Analyzing the performance of content shared on these platforms is critical to developing effective marketing strategies. In this blog post, we will perform social media analysis step by step using Instagram, Facebook and Twitter data. Our goal is to determine the effects of different post types and time periods on engagement and make data-driven strategic decisions.
Dataset Description
The datasets used in this project include post 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)
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)
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)
Data Analysis 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: Exploratory Data Analysis (EDA)
We examined the data sets and calculated important metrics. For example, we obtained basic statistics such as the total number of likes, comments and shares. We analyzed the overall health of these metrics for each platform.
Step 4: Analysis by Platform and Post Type
We compared engagement across different social media platforms and post types. We've observed that video posts generally get more engagement. We calculated the average number of likes, comments and shares for each post type.
Step 5: Time Analysis
We analyzed the time periods in which the posts were made. We examined the effects of posting hours on engagement. For example, we observed that posts made in the morning received more likes than posts made in the evening.
Step 6: Visualizing Results and Decision Making
We presented the findings by visualizing the analysis results. This step is important to support the decision-making process. We presented the findings visually using graphs.
Conclusion
In this project, we aimed to make data-based strategic decisions by analyzing user interactions on social media platforms. We compared and analyzed interactions across platforms, post types, and time periods. This type of analysis is extremely valuable for optimizing social media marketing strategies and increasing user engagement. By making data-based decisions, you can make your social media marketing strategies more effective and better reach your target audience.
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