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Social Media Product Sentiment Dataset
Social Media and Networking
Tags and Keywords
Trusted By
"No reviews yet"
Free
About
This dataset contains tweets posted for various services and products along with the emotion contained in each tweet. It is designed to be used for training various machine learning models focused on analysing sentiments in tweets. The dataset includes key information such as the tweet text, the specific product or service the tweet references, and the emotion expressed within the tweet.
Columns
- tweet_text: The actual text content of the tweet.
- emotion_in_tweet_is_directed_at: Identifies the product or service that is the subject of the tweet's emotion.
- Example values include "iPad" (10% of values), and "Other" (2345 entries, 26% of values).
- is_there_an_emotion_directed_at_a_brand_or_product: Indicates the type of emotion present in the tweet.
- There are 9066 unique values for this column.
- Emotion distribution:
- 64% of entries show no emotion toward a brand or product.
- 59% of entries indicate positive emotion.
- 33% of entries are categorised as "Other" (726 entries).
Distribution
The dataset is typically provided in a tabular format, suitable for data analysis and machine learning tasks. While the exact number of rows or records is not specified in the provided information, it consists of a collection of tweet entries. Data files are usually in CSV format.
Usage
This dataset is ideally suited for:
- Developing and training machine learning models for sentiment analysis.
- Analysing customer feedback and public opinion towards products and services expressed on social media.
- Research into natural language processing (NLP) and text classification.
- Understanding trends in public sentiment related to specific brands or industries.
Coverage
The dataset has a global coverage, making it applicable for analysis of tweets from various regions. Specific time ranges or demographic scopes are not detailed in the available information.
License
CCO
Who Can Use It
This dataset is intended for:
- Machine Learning Engineers and Data Scientists for model development.
- Researchers in natural language processing, social media analysis, and marketing.
- Businesses looking to analyse public sentiment regarding their products or market trends.
- Students learning about data analysis, NLP, and machine learning.
Dataset Name Suggestions
- Product Tweets Sentiment Dataset
- Tweet Emotion Analysis Data
- Social Media Product Sentiment
- Tweets for Sentiment Models
- Brand Sentiment Tweet Data
Attributes
Original Data Source: Product Tweets Dataset
QUALITY