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Global Offensive Player Sentiment Data
Reviews & Ratings
Tags and Keywords
Trusted By
"No reviews yet"
Free
About
This dataset offers a deep dive into player feedback for Counter-Strike: Global Offensive. It captures user opinions, highlighting various aspects such as game mechanics, developer responsiveness, and the overall player community experience. The dataset is suitable for analysing player sentiment and identifying key areas of player satisfaction and dissatisfaction within a popular online first-person shooter.
Columns
review_id: A unique identifier for each individual review.title: The title of the game being reviewed, consistently 'Counter-Strike: Global Offensive'.year: The year in which the user review was published.user_review: The textual content of the player's review.
Distribution
The dataset is typically provided in a CSV file format. Specific details regarding the exact number of rows or records are not available from the provided information.
Usage
- Performing sentiment analysis on player reviews to gauge overall player mood.
- Identifying recurring themes and common complaints or praises from the player base.
- Understanding the impact of game updates and developer decisions on player satisfaction.
- Conducting market research for video game development and community management strategies.
- Developing and testing natural language processing (NLP) models for tasks like text classification and topic modelling.
Coverage
- Game: Exclusively covers reviews for Counter-Strike: Global Offensive.
- Time Range: Reviews span from 2013 to 2018, offering a historical perspective on player sentiment over several years.
- Demographic Scope: The reviews reflect feedback from a global player base, implicitly capturing diverse experiences and linguistic nuances (e.g., discussions about Russian players).
- Specific Notes: The reviews address a broad spectrum of topics including game performance, cheating issues, community behaviour (e.g., toxicity, smurfing), and specific weapon or gameplay changes.
License
CCO
Who Can Use It
- Game Developers: To understand player feedback directly and prioritise development efforts (e.g., addressing cheating, improving server performance).
- Market Researchers: To gauge player sentiment and identify market trends within the online gaming sector.
- Data Scientists/Analysts: For text analysis projects, training machine learning models (e.g., sentiment classification), and conducting trend analysis.
- Community Managers: To monitor player discussions, identify key issues, and address community concerns effectively.
Dataset Name Suggestions
- CS:GO Player Review Data
- Counter-Strike Global Offensive User Feedback
- Steam CS:GO Game Reviews
- Global Offensive Player Sentiment Data
Attributes
Original Data Source: Steam Game Review Dataset
QUALITY