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Global Layoff Sentiment Data
Data Science and Analytics
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About
This dataset features scraped LinkedIn posts from professionals and users, offering insights into ongoing layoff trends. It provides a snapshot of current reactions from various professionals regarding layoffs, collected from recent LinkedIn activity. This data is suitable for data science and analytics purposes, allowing for an examination of public sentiment and discourse around this significant professional event.
Columns
The dataset is structured with the following key columns, where each row represents a distinct LinkedIn post:
- index: An internal identifier for each post.
- text: The textual content of the LinkedIn post. Please note, this may include content in languages other than English.
- role: Describes the professional role of the individual who posted. This column may contain null values if the role was not available during scraping. In some instances, if the role isn't present, it might instead indicate the number of followers for that LinkedIn profile.
- num_reactions: The total count of reactions a post received, encompassing all emotion types available on LinkedIn.
- num_comments: The total number of comments made on a specific post.
- num_reposts: The total number of times a post was reposted by others.
Distribution
The data file is typically provided in a CSV format. Each row in the dataset corresponds to an individual LinkedIn post. Specific numbers detailing the total rows or records for this dataset are not currently available.
Usage
This dataset is ideally suited for:
- Analysing the current sentiment and reactions of professionals regarding layoffs.
- Conducting exploratory data analysis on social media content related to employment trends.
- Developing and testing Natural Language Processing (NLP) models to understand public discourse.
- Gaining insights into the impact of layoffs on various professional groups.
Coverage
The dataset focuses on ongoing layoff trends, particularly those from 2022, as indicated by its name. Its geographic scope is global, capturing posts from LinkedIn users worldwide. The data encompasses posts from a wide range of professionals and users, with specific roles sometimes identified, offering a varied demographic perspective on the subject.
License
CC0
Who Can Use It
This dataset is beneficial for a variety of users, including:
- Data Scientists and Analysts: For sentiment analysis, trend identification, and NLP projects.
- Researchers: Studying the socio-economic impact of layoffs and professional reactions.
- Human Resources Professionals: To understand employee sentiment and industry trends.
- Journalists and Media Outlets: For reporting on real-time professional perspectives during economic shifts.
Dataset Name Suggestions
- Layoffs NLP 2022 (Existing)
- LinkedIn Layoff Reactions
- Global Layoff Sentiment Data
- Professional Layoff Discourse 2022
- Social Media Layoff Trends
Attributes
Original Data Source: Layoffs NLP 2022
QUALITY