Social Media Sentiments Analysis Dataset 📊

The Social Media Sentiments Analysis Dataset captures a vibrant tapestry of emotions, trends, and interactions across various social media platforms. This dataset provides a snapshot of user-generated content, encompassing text, timestamps, hashtags, countries, likes, and retweets. Each entry unveils unique stories—moments of surprise, excitement, admiration, thrill, contentment, and more—shared by individuals worldwide.

Key Features

Feature Description Text User-generated content showcasing sentiments Sentiment Categorized emotions Timestamp Date and time information User Unique identifiers of users contributing Platform Social media platform where the content originated Hashtags Identifies trending topics and themes Likes Quantifies user engagement (likes) Retweets Reflects content popularity (retweets) Country Geographical origin of each post Year Year of the post Month Month of the post Day Day of the post Hour Hour of the post How to Use The Social Media Sentiments Analysis Dataset 📊

The Social Media Sentiments Analysis Dataset is a rich source of information that can be leveraged for various analytical purposes. Below are key ways to make the most of this dataset:

Sentiment Analysis:

Explore the emotional landscape by conducting sentiment analysis on the "Text" column. Classify user-generated content into categories such as surprise, excitement, admiration, thrill, contentment, and more.

Temporal Analysis:

Investigate trends over time using the "Timestamp" column. Identify patterns, fluctuations, or recurring themes in social media content.

User Behavior Insights:

Analyze user engagement through the "Likes" and "Retweets" columns. Discover popular content and user preferences.

Platform-Specific Analysis:

Examine variations in content across different social media platforms using the "Platform" column. Understand how sentiments vary across platforms.

Hashtag Trends:

Identify trending topics and themes by analyzing the "Hashtags" column. Uncover popular or recurring hashtags.

Geographical Analysis:

Explore content distribution based on the "Country" column. Understand regional variations in sentiment and topic preferences.

User Identification:

Use the "User" column to track specific users and their contributions. Analyze the impact of influential users on sentiment trends.

Cross-Analysis:

Combine multiple features for in-depth insights. For example, analyze sentiment trends over time or across different platforms and countries.

Original Data Source: Social Media Sentiments Analysis Dataset 📊