--- tags: - emoji_extraction - bluesky_emoji_extraction - emojis - emoji_analysis - emoji --- ### Dataset Card for Emoji Extraction from Bluesky Posts ## Dataset Description # Overview This dataset contains extracted emojis from Bluesky social media posts, totaling 11.2 GB per file, with a total of 10 JSONL files. Each file is structured to include emojis along with their frequency, name, and Unicode code. The dataset is a valuable resource for researchers and developers working on natural language processing (NLP), large language models (LLMs), generative AI, and data analysis. # Dataset Size Total Size: 112 GB (11.2 GB per file × 10 files) Format: JSONL (JSON Lines) ## Dataset Structure # Each line in the JSONL files contains the following fields: emoji: The actual emoji character. frequency: The frequency of the emoji in the dataset. name: The name or description of the emoji. code: The Unicode code point for the emoji # Dataset Source The data is sourced from Bluesky social media posts, capturing the usage of emojis across various posts. # Dataset Usage Potential Applications This dataset can be utilized for a variety of purposes, including but not limited to: ## Large Language Models (LLMs): # Training : The dataset can be used to train LLMs to understand and generate text that includes emojis. # Fine-tuning: Fine-tune existing LLMs to better interpret and produce emojis in context. ## Generative AI: # Text Generation: Enhance text generation models to include emojis that are contextually relevant. # Chatbots: Improve chatbot responses by incorporating emojis that match the tone and context of the conversation. ## Data Analysis: # Trend Analysis: Analyze the popularity and usage trends of emojis over time. # Sentiment Analysis: Use emojis as a proxy for sentiment in social media posts. # User Behavior: Study how users interact with emojis in different contexts. ## AI Research: # Emoji Prediction: Develop models that predict the most appropriate emoji to accompany a given text. # Multimodal Learning: Combine text and emoji data to improve multimodal models that understand both textual and visual (emoji) content. ## Social Media Analysis: # Content Moderation: Identify and moderate content based on the presence of specific emojis. # Engagement Analysis: Analyze how the use of emojis affects user engagement on social media platforms. ## Access and Usage The dataset is available for research and commercial use. Users are encouraged to cite the source when using the dataset in their work. ## Ethical Considerations # Privacy: Ensure that the dataset does not contain any personally identifiable information (PII). # Bias: Be aware of potential biases in emoji usage and consider how these might affect model training and analysis. ## License The dataset is released under the MIT License, allowing for free use, modification, and distribution, provided that the original license is included. ## Dataset Details # File Naming Convention # File Names: emoji_df_.jsonl where ranges from 1 to 10. ## Data Fields emoji: The emoji character itself. frequency: The number of times the emoji appears in the dataset. name: A descriptive name for the emoji. code: The Unicode representation of the emoji. ## Dataset Creation # Data Collection The data was collected from Bluesky social media posts, focusing on the extraction of emojis and their metadata. ## Data Processing # Emoji Extraction: Emojis were extracted from the text of each post. # Frequency Counting: The frequency of each emoji was calculated. # Metadata: Additional metadata such as the name and Unicode code point were added for each emoji. # Data Storage The processed data was stored in JSONL format, with each emoji entry on a new line. # Citation If you use this dataset in your research, please cite it as follows: Martin Rivera [DeepSeek-V2.5-1210]. (2024). Emoji Extraction from Bluesky Posts [TroglodyteDerivations/Bluesky_Emoji_Extraction]. Available at https://huggingface.co/datasets/TroglodyteDerivations/Bluesky_Emoji_Extraction ## Acknowledgments We would like to thank Bluesky for providing the platform and data, and all contributors who helped in the collection and processing of this dataset.