task_categories:feature-extraction task_categories:text-classification language:en license:mit size_categories:100K<n<1M format:json modality:text library:datasets library:pandas library:mlcroissant library:polars region:us art
---
license: mit
task_categories:
- feature-extraction
- text-classification
language:
- en
tags:
- art
---
<div align="center">
  <img src="2pac.jpg" alt="2pac" width="250" height="250">
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*Hit 'Em Up* by 2Pac (Tupac Shakur) stands as one of the most influential and iconic diss tracks in the history of rap. Written and performed by the legendary Tupac Shakur, the song embodies his raw, unfiltered artistry and fearless commentary. Known not only as a rapper but as a poet, Tupac consistently tackled social issues, justice, and the realities of life through his music. His unparalleled lyrical genius has inspired generations of artists, including Eminem, Kendrick Lamar, and J. Cole, and continues to leave an indelible mark on the global rap community.

We are proud to release a dataset comprising **comments from the official music video of *Hit 'Em Up***. This dataset offers a unique opportunity to explore the emotional and cultural depth present in the discourse surrounding one of rap's most defining tracks. 

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## **Dataset Overview**  

- **Release Date:** November 17, 2024  
- **Artist Name:** 2Pac (Tupac Shakur)  
- **Original Music Video:** [Watch Here](https://youtu.be/41qC3w3UUkU?si=Jk621GjYL5vMOSo-)  
- **Total Comments:** 251,488  

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## **Applications in AI**  

This dataset is a treasure trove for researchers, developers, and enthusiasts in **natural language processing (NLP)** and **machine learning (ML)**. Its diversity in sentiment and language provides a fertile ground for multiple AI applications:  

- **Sentiment Analysis:** Analyze the spectrum of emotions, from admiration and nostalgia to criticism and debate.  
- **Historical and Cultural Context:** Extract insights into the cultural impact of 2Pac's music, capturing the essence of its influence on listeners across decades.  
- **Emotion Classification:** Train models to recognize and classify a wide range of human emotions embedded in text.  
- **Linguistic Study:** Explore linguistic patterns, slang, and evolving language trends within the rap community.  
- **Content Moderation:** Develop tools to filter and manage online discourse effectively by leveraging comments spanning both positive and negative interactions.  

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## **Why This Dataset Matters**  

This dataset encapsulates not just the *Hit 'Em Up* legacy but also a piece of hip-hop history, offering ML researchers access to a richly nuanced data source filled with sentiment, passion, and controversy. It is an invaluable resource for bridging AI with cultural and artistic studies, enabling new possibilities in the analysis of social and emotional dynamics.  

We look forward to seeing how this dataset will inspire innovative applications and push the boundaries of AI research!