Project Description
Social media has become an important communication and marketing tool for individuals and businesses today. In this project, we will evaluate user behavior and the performance of the platform by analyzing interaction data of a social media platform. Our aim is to examine users' post interactions, like and comment activities, identify popular content types and make strategic decisions to increase the overall interaction level of the platform. This analysis will help social media managers and marketing teams understand engagement trends and optimize content strategies.
Project Usage Areas
This project has several uses for social media platforms and marketing teams:
Analysis of User Behavior: Determining which types of content attract more attention by examining users' interactions on the platform.
Content Strategies: Optimizing content strategies by analyzing popular content types and engagement rates.
Determining Interaction Trends: Making seasonal and periodic content plans by determining interaction trends over time.
User Segmentation: Creating special campaigns and offers for the target audience by analyzing the interaction behavior of different user groups.
Marketing Campaigns: Developing effective marketing campaigns and creating customer loyalty programs using social media interaction data.
Dataset Description
The data set to be used in this project includes interaction data from a social media platform. The dataset consists of four main files in total:
Users
UserID: User ID
UserName: Username
JoinDate: Join date
Country: Country
Posts
PostID: Post ID
UserID: User ID
PostDate: Post date
Content: Post content
Likes: Number of likes
Likes
LikeID: Like ID
PostID: Post ID
UserID: User ID
LikeDate: Like date
Comments
CommentID: Comment ID
PostID: Post ID
UserID: User ID
CommentDate: Comment date
Content: Comment content
There are various dirty data problems in this dataset, such as missing data, outlier data, and wrong data type. This is an ideal data set to experience data cleaning and processing processes commonly encountered in real life.
Student Benefits
This project provides many benefits for students:
Data Manipulation: Students develop skills in examining, cleaning, and analyzing data sets.
Using Pandas: They learn to use the data processing and analysis methods of the Pandas library effectively.
Data Cleaning: They gain skills in cleaning missing data, outliers and incorrect data types.
Business Intelligence: By analyzing data sets, they improve their ability to evaluate platform performance and make strategic decisions.
Reporting: Provides skills to effectively report and present analysis results.
Real Life Applications: Provides practical information about data problems and analysis processes encountered in real life.
Steps
- Determine the purpose and objectives of the project.
- Determine what questions you are looking for answers to and what decisions they will help make.
-Which company's stock has the highest closing price?
- Which company has the highest transaction volume?
-Which company's stock price has increased the most over time?
- Which sector has the highest total market value?
- Which sector has the highest number of employees?
- Is there a correlation between GDP and stock prices?
- Is there a correlation between the inflation rate and stock prices?
- Is there a correlation between the unemployment rate and stock prices?
- Is there a correlation between interest rate and stock prices?
- What is the impact of company news on stock prices?
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