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Social Media Engagement Sentiment
Social Media and Networking
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About
This dataset captures a vibrant tapestry of emotions, trends, and interactions across various social media platforms. It 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, and contentment—shared by individuals worldwide. It is designed to offer insights into social media dynamics and user sentiments.
Columns
- Unnamed: 0: An index column, typically for record identification within the dataset.
- Text: User-generated content, presenting the original social media post from which sentiments are derived.
- Sentiment: The categorised emotion or sentiment expressed in the 'Text' column, such as Positive, Negative, or Neutral.
- Timestamp: The exact date and time when the social media content was posted.
- User: A unique identifier for the individual user who contributed the content.
- Platform: The specific social media platform where the content originated (e.g., Twitter, Instagram, Facebook).
- Hashtags: Keywords or phrases prefixed with '#' that identify trending topics and themes within the content.
- Retweets: A numerical value reflecting the popularity of the content, indicating how many times it was shared or re-posted.
- Likes: A numerical value quantifying user engagement, representing the number of 'likes' the post received.
- Country: The geographical origin of the social media post.
- Year: The year the social media post was published.
- Month: The month the social media post was published.
- Day: The day of the month the social media post was published.
- Hour: The hour of the day the social media post was published.
Distribution
The dataset is typically provided as a data file, most often in CSV format. A sample file will be updated separately to the platform. The structure is tabular, organised into the columns described above. Specific numbers for rows or records are not available, but it represents a daily snapshot of social media activity.
Usage
This dataset is a rich source of information that can be leveraged for various analytical purposes:
- 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, and contentment.
- Temporal Analysis: Investigate trends over time using the 'Timestamp' column. Identify patterns, fluctuations, or recurring themes in social media content.
- User Behaviour Insights: Analyse user engagement through the 'Likes' and 'Retweets' columns to 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 analysing 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: Utilise the 'User' column to track specific users and their contributions. Analyse the impact of influential users on sentiment trends.
- Cross-Analysis: Combine multiple features for in-depth insights. For example, analyse sentiment trends over time or across different platforms and countries.
Coverage
The dataset offers global geographical coverage, capturing posts from individuals worldwide. Examples in the sample data include content originating from the USA, Canada, the UK, Australia, and India. The data represents a snapshot of user-generated content, with the provided sample covering a few days in January 2023. The demographic scope is tied to general social media users, with no specific demographic breakdowns noted.
License
CCO
Who Can Use It
This dataset is ideal for:
- Data scientists and machine learning engineers looking to train and validate models for sentiment analysis, natural language processing, and social media analytics.
- Researchers and academics studying social trends, public opinion, digital communication, and user engagement patterns.
- Marketing and brand analysts seeking to understand consumer sentiment, track brand mentions, and evaluate the reception of campaigns across different social platforms.
- Anyone interested in gaining insights into the emotional landscape and dynamic interactions occurring within social media environments.
Dataset Name Suggestions
- Social Media Sentiments Analysis Dataset
- Global Social Sentiment Tracker
- User-Generated Content Emotion Data
- Digital Conversation Sentiment Snapshot
- Social Media Engagement Sentiment
Attributes
Original Data Source: Social Media Sentiments Analysis Dataset 📊
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